Resiliency plays a critical role in designing future communication networks. How to make edge computing systems resilient against unpredictable failures and fluctuating demand is an important and challenging problem. To this end, this paper investigates a resilient service placement and workload allocation problem for a service provider (SP) who can procure resources from numerous edge nodes to serve its users, considering both resource demand and node failure uncertainties. We introduce a novel two-stage adaptive robust model to capture this problem. The service placement and resource procurement decisions are optimized in the first stage, while the workload allocation decision is determined in the second stage after the uncertainty realization. By exploiting the special structure of the uncertainty set, we develop an efficient iterative algorithm that can converge to an exact optimal solution within a finite number of iterations. However, the running time of this iterative algorithm heavily depends on the uncertainty set. Therefore, we further present an affine decisions rule approximation approach, which exhibits greater insensitivity to the uncertainty set, to tackle the underlying problem. Extensive numerical results demonstrate the advantages of the proposed model and approaches, which can help the SP make proactive decisions to mitigate the impacts of the uncertainties.

Edge Computing (EC) offers a superior user experience by positioning cloud resources in close proximity to end users. The challenge of allocating edge resources efficiently while maximizing profit for the EC platform remains a sophisticated problem, especially with the added complexity of the online arrival of resource requests. To address this challenge, we propose to cast the problem as a multi-armed bandit problem and develop two novel online pricing mechanisms, the Kullback-Leibler Upper Confidence Bound (KL-UCB) algorithm and the Min-Max Optimal algorithm, for heterogeneous edge resource allocation. These mechanisms operate in real-time and do not require prior knowledge of demand distribution, which can be difficult to obtain in practice. The proposed posted pricing schemes allow users to select and pay for their preferred resources, with the platform dynamically adjusting resource prices based on observed historical data. Numerical results show the advantages of the proposed mechanisms compared to several benchmark schemes derived from traditional bandit algorithms, including the Epsilon-Greedy, basic UCB, and Thompson Sampling algorithms.

Edge computing has emerged as a key technology to reduce network traffic, improve user experience, and enable numerous Internet of Things applications. In this article, we study an optimal resource procurement problem for a service provider (SP), who can purchase resources from various edge nodes in the edge computing market to serve its users’ requests. How to jointly optimize the service placement, resource sizing, and workload allocation decisions is a challenging problem, which becomes even more complicated when considering demand uncertainty. To this end, we propose a novel two-stage adaptive robust optimization framework to help the SP optimally determine the locations for installing its service (i.e., placement) and the amount of computing resource to purchase from each location (i.e., sizing). The proposed placement and sizing solution can hedge against any possible realization within a predefined demand uncertainty set. Given the first-stage robust solution, the optimal resource and workload allocation decisions are computed in the second stage after the uncertainty is revealed. To solve the two-stage model, this article presents an iterative solution approach by employing the column-and-constraint generation method that decomposes the underlying problem into a master problem and a max–min subproblem associated with the second stage. Extensive numerical results are shown to illustrate the efficacy of the proposed model.

The emerging edge computing (EC) paradigm promises to provide low latency and ubiquitous computation to numerous mobile and Internet of Things (IoT) devices at the network edge. How to efficiently allocate geographically distributed heterogeneous edge resources to a variety of services is a challenging task. While this problem has been studied extensively in recent years, most of the previous work has largely ignored the preferences of the services when making edge resource allocation decisions. To this end, this article introduces a novel bilevel optimization model, which explicitly takes the service preferences into consideration, to study the interaction between an EC platform and multiple services. The platform manages a set of edge nodes (ENs) and acts as the leader while the services are the followers. Given the service placement and resource pricing decisions of the leader, each service decides how to optimally divide its workload to different ENs. The proposed framework not only maximizes the profit of the platform but also minimizes the cost of every service. When there is a single EN, we derive a simple analytic solution for the underlying problem. For the general case with multiple ENs and multiple services, we present a Karush–Kuhn–Tucker-based solution and a duality-based solution, combining with a series of linearizations, to solve the bilevel problem. Extensive numerical results are shown to illustrate the efficacy of the proposed model.

The availability of thousands of assays of epigenetic activity necessitates compressed representations of these data sets that summarize the epigenetic landscape of the genome. Until recently, most such representations were cell type-specific, applying to a single tissue or cell state. Recently, neural networks have made it possible to summarize data across tissues to produce a pan-cell type representation. In this work, we propose Epi-LSTM, a deep long short-term memory (LSTM) recurrent neural network autoencoder to capture the long-term dependencies in the epigenomic data. The latent representations from Epi-LSTM capture a variety of genomic phenomena, including gene-expression, promoter-enhancer interactions, replication timing, frequently interacting regions, and evolutionary conservation. These representations outperform existing methods in a majority of cell types while yielding smoother representations along the genomic axis due to their sequential nature.

The emerging edge computing paradigm promises to deliver superior user experience and enable a wide range of Internet of Things (IoT) applications. In this paper, we propose a new market-based framework for efficiently allocating resources of heterogeneous capacity-limited edge nodes (EN) to multiple competing services at the network edge. By properly pricing the geographically distributed ENs, the proposed framework generates a market equilibrium (ME) solution that not only maximizes the edge computing resource utilization but also allocates optimal resource bundles to the services given their budget constraints. When the utility of a service is defined as the maximum revenue that the service can achieve from its resource allotment, the equilibrium can be computed centrally by solving the Eisenberg-Gale (EG) convex program. We further show that the equilibrium allocation is Pareto-optimal and satisfies desired fairness properties including sharing incentive, proportionality, and envy-freeness. Also, two distributed algorithms, which efficiently converge to an ME, are introduced. When each service aims to maximize its net profit (i.e., revenue minus cost) instead of the revenue, we derive a novel convex optimization problem and rigorously prove that its solution is exactly an ME. Extensive numerical results are presented to validate the effectiveness of the proposed techniques.

We study the ratio-of-distance estimation from the difference of received signal strength (DRSS) when the source transmission power is unknown. Due to fluctuations in the wireless medium, the path loss exponent is also considered unknown and is modelled statistically as a uniformly distributed random variable. When maximum-likelihood estimation is employed, we are required to solve a highly non-linear function which contains a summation of exponential and Q-function terms in the log-ratio-of-distances. In the state-of-the-art [8], the Q-function terms are ignored in order to derive an approximate but erroneous solution in closed-form. In this work, we firstly expose the adverse impact of ignoring the Q-function terms on the estimation performance. Next, we propose a uniform search root finder (USRF) method which solves the original non-linear function without ignoring any of the underlying terms. Numerical studies reveal that the proposed method not only provides much more accurate ratio-of-distance estimates than the state-of-the-art, but also provides significantly better localization accuracy.

We consider the problem of detecting and localizing the time-frequency span of unmanned aerial vehicles (UAVs) which transmit Wi-Fi-type [1] signals in the ISM band. Interference is assumed to be present ubiquitously in the form of Bluetooth and microwave oven signals. We firstly expose that simple edge detection algorithms based on morphological processing, which are conventionally used to detect signals in spectrogram matrices, do not provide a scalable performance beyond a few RF captures because they suffer from limited hyperparameter generalizability. To overcome this limitation, we propose a support vector machine (SVM) classification algorithm, wherein, we run a sliding detection window across the spectrogram and extract the histogram of ordered gradient (HOG) features. The extracted feature vectors are used to classify the windows as positive or negative, depending on whether a signal of interest is present or not. For experimental evaluation, we generate a synthetic RF dataset containing 150 training captures and 50 test captures, each of duration 90ms, bandwidth 56MHz, and containing about 4.5 Wi-Fi signals on average. The proposed SVM algorithm achieves a mean average precision (mAP) of up to 0.4835, which is significantly higher than the state-of-the-art morphological processing algorithm [11] which only achieves an mAP of 0.3676.

In this paper, we propose a blind timefrequency localization method for wireless signals present in a wideband radio frequency (RF) spectrum. The signal detection problem is transformed into an object detection problem by converting the RF time-series captures into spectrogram images. A deep learning system based on the Faster RCNN [2] is then configured to suit the signal detection task. Guidelines are provided to make design choices in terms of both data pre-processing and the FRCNN modeling, for example, on the Short Time Fourier Transform (STFT) parameters, the spectrogram sizes, and the anchor sizes. Experiments with artificially generated WiFi high throughput data [3] reveal that (i) the proposed framework can achieve up to a mean average precision (mAP) of 0.9 for captures with positive signal-to-noise ratio (SNR), (ii) the proposed framework is fairly robust to the number and size of the anchors, and (iii) the proposed framework is sensitive to the disparity in the signal sizes, giving us few insights into possible future extensions.

We propose a wideband spectrum sensing technique to detect and localize wireless radio frequency (RF) signals of interest in time and frequency when uninteresting signals cause RF interference (RFI). Specifically, we adopt and downscale the existing Faster-RCNN (FRCNN) framework to achieve better signal detection and localization than the state-of-the-art. For experimental evaluation, we present a data generation framework for Wi-Fi as the signals of interest and the Bluetooth and microwave oven signals as the RFI. Experiments reveal that (i) the downscaled FRCNN model can achieve up to a mean average precision (mAP) of 0.8, significantly outperforming the state-of-the-art, (ii) feature extraction with the VGG-13 architecture gives the best mAP with pretrained weights and configured as trainable, (iii) for signal detection in real RF traces, when compared to training purely with synthetic RF data, a better mAP can be achieved by training with a mixture of synthetic and real RF traces or by fine tuning the synthetically-trained weights with an additional round of training on a small amount of real RF traces, and (iv) the mAP performance decreases as the signal to noise ratio (SNR) is lowered.

We consider positioning multiple users si- multaneously in a distributed massive multiple-input multiple-output (MIMO) system from the uplink re- ceived signal strength (RSS) information. The trans- mission power of the users, although available from the telecommunication protocol specifications, is con- sidered unknown due to the uncertainty arising from hardware component losses and/or battery voltage fluctuations. The pathloss exponent is also assumed to be unknown due to environmental fluctuations and/or infrequent calibration campaigns. Taking these con- straints into account, we propose a positioning algo- rithm which uses the concept of differential RSS to handle the transmit power uncertainty and derives a linear least squares solution from the ratio-of-distance estimates, which are in turn obtained by assuming that the pathloss exponent is a uniformly distributed random variable. Numerical studies reveal that the proposed positioning algorithm achieves meter-level accuracy even though the transmit power and the pathloss exponent are unknown. The best localization performance is achieved when the differential RSS is calculated using the remote radio head (RRH) with the lowest RSS as the reference. Also, the observed localization performance is consistent across different pathloss exponent values.

Environmental monitoring is a practical application where a wireless sensor network (WSN) may be utilized effectively. However, the energy consumption issues have become a major concern in using a WSN, particularly in remote locations without readily accessible electrical power supply. In general, the activities of data transmission among sensor nodes and the gateway (GW) can be a significant fraction of the total energy consumption within a WSN. Hence, reducing the number and the duration of transmissions as much as possible while maintaining a high level of data accuracy can be an effective strategy for saving energy. To achieve this objective, a least mean square (LMS) filter is used for a dual prediction scheme (DPS), in this paper. The DPS is data quality-based, allowing both the sensor nodes and the GW to predict the data simultaneously. Only when the error between the predicted data and the real sensed data exceeds a predefined threshold, the sensor nodes will send the sensed data to the GW/another node and consequently will update the coefficients of the filter. It is observed that, with this scheme, the total number of transmissions and their overall duration can be effectively reduced, and therefore, further energy savings can be realized. With the developed methodologies, at least 62.3% of the total energy for data transmission could be saved while achieving a 93.1% prediction accuracy.

Fog computing is transforming the network edge into an intelligent platform by bringing storage, computing, control, and networking functions closer to end users, things, and sensors. How to allocate multiple resource types (e.g., CPU, memory, bandwidth) of capacity-limited heterogeneous fog nodes to competing services with diverse requirements and preferences in a fair and efficient manner is a challenging task. To this end, we propose a novel market-based resource allocation framework in which the services act as buyers and fog resources act as divisible goods in the market. The proposed framework aims to compute a market equilibrium (ME) solution at which every service obtains its favorite resource bundle under the budget constraint, while the system achieves high resource utilization. This paper extends the general equilibrium literature by considering a practical case of satiated utility functions. In addition, we introduce the notions of non-wastefulness and frugality for equilibrium selection and rigorously demonstrate that all the non-wasteful and frugal ME are the optimal solutions to a convex program. Furthermore, the proposed equilibrium is shown to possess salient fairness properties, including envy-freeness, sharing-incentive, and proportionality. Another major contribution of this paper is to develop a privacy-preserving distributed algorithm, which is of independent interest, for computing an ME while allowing market participants to obfuscate their private information. Finally, extensive performance evaluation is conducted to verify our theoretical analyses.

Hybrid precoding, a combination of digital and analog precoding, is an alternative to traditional precoding methods in massive MIMO systems with a large number of antenna elements and has shown promising results recently. In this paper, we implement a parallel framework to make hybrid precoding competitive in fast-fading environments. A low-complexity algorithm which exploits the block diagonal phase-only nature of the analog precoder in a partially connected structure is proposed to arrive at a hybrid precoding solution for a multi-carrier single-user system using orthogonal frequency division multiplexing (OFDM). The original problem is broken down into two subproblems of finding the magnitude and the phase components which are solved independently. A per-RF chain power constraint is introduced instead of the sum power constraint over all antennas which are much more practical in real systems. An alternating version of the same algorithm is proposed for increased spectral-efficiency gains. Complexity and run-time analysis demonstrate the advantage of the proposed algorithm over existing hybrid precoding schemes for partially connected structure in an OFDM setting. The simulation results reveal certain insights about the partially connected structure and the tradeoffs that have to be made to make it workable in a real wideband system.

We jointly optimize resource allocation with the dynamic activation of energy harvesting base stations in a two-tier orthogonal frequency-division multiple access-based heterogeneous network. We consider both energy harvesting constraints and interference constraints along with time-variation in channel condition, user activity, and energy arrival. We optimize the trade-off between throughput performance of the small cell (or hotspot) users and the associated power cost by maximizing the net reward, where positive reward is associated with achievable throughput of the hotspot users and negative reward with the corresponding non-renewable power consumption. Quality-of-service requirements of hotspot users as well as macrocell users are considered in the optimization problem. Assuming the availability of non-causal information, we propose offline resource allocation algorithm using discrete binary particle swarm optimization and dual decomposition technique. Assuming the availability of statistical information of future values, we propose dynamic programming-based online algorithm. Finally, we propose simple and greedy online algorithm assuming lack of any kind of future information. Numerical results demonstrate the performances of the proposed offline, dynamic programming-based online, and greedy online algorithms and highlight the scenarios, where the performance of the proposed algorithms is significantly better than the baseline schemes.

We propose a supervised machine learning (ML) approach based on Gaussian process (GP) regression to position users in a distributed massive multiple-input multiple-output (DM-MIMO) system from their uplink received signal strength (RSS). The proposed approach serves as a proof-of-concept that we can localize users by training an ML model with noise-free RSS and using the trained model to estimate the test user locations from their noisy RSS. We consider two GP methods for localization, namely, the conventional GP (CGP) and the numerical approximation GP (NaGP). We find that the CGP provides unrealistically small 2σ error-bars on the location estimates. Therefore, we derive the true predictive distribution and employ NaGP to obtain realistic 2σ error-bars on the location estimates. Next, we derive a Bayesian Cramer-Rao lower bound (BCRLB) on the root-mean-squared-error (RMSE) performance of the two GP methods. Numerical studies reveal that: 1) the NaGP indeed provides realistic 2σ error-bars on the estimated locations; 2) both the CGP and NaGP achieve RMSEs that are close to the BCRLBs; 3) the presence of correlated shadowing improves the RMSE performance; and 4) extrapolation to the zero input noise scenario can significantly improve the RMSE achieved by the NaGP.

Non-orthogonal multiple access (NOMA) is an essential enabling technology for the fifth-generation (5G) wireless networks to meet the heterogeneous demands on low latency, high reliability, massive connectivity, improved fairness, and high throughput. The key idea behind NOMA is to serve multiple users in the same resource block, such as a time slot, subcarrier, or spreading code. The NOMA principle is a general framework, and several recently proposed 5G multiple access schemes can be viewed as special cases. This survey provides an overview of the latest NOMA research and innovations as well as their applications. Thereby, the papers published in this special issue are put into the context of the existing literature. Future research challenges regarding NOMA in 5G and beyond are also discussed.

To keep the hardware costs of future communications systems manageable, the use of low-cost hardware components is desirable. This is particularly true for the emerging massive multiple-input multiple-output (MIMO) systems which equip base stations (BSs) with a large number of antenna elements. However, low-cost transceiver designs will further accentuate the hardware impairments, which are present in any practical communication system. In this paper, we investigate the impact of hardware impairments on the secrecy performance of downlink massive MIMO systems in the presence of a passive multiple-antenna eavesdropper. Thereby, for the BS and the legitimate users, the joint effects of multiplicative phase noise, additive distortion noise, and amplified receiver noise are taken into account, whereas the eavesdropper is assumed to employ ideal hardware. We derive a lower bound for the ergodic secrecy rate of a given user when matched filter data precoding and artificial noise (AN) transmission are employed at the BS. Based on the derived analytical expression, we investigate the impact of the various system parameters on the secrecy rate and optimize both the pilot sets used for uplink training and the AN precoding. Our analytical and simulation results reveal that: 1) the additive distortion noise at the BS may be beneficial for the secrecy performance, especially if the power assigned for AN emission is not sufficient; 2) all other hardware impairments have a negative impact on the secrecy performance; 3) despite their susceptibility to pilot interference in the presence of phase noise, so-called spatially orthogonal pilot sequences are preferable unless the phase noise is very strong; and 4) the proposed generalized null-space AN precoding method can efficiently mitigate the negative effects of phase noise.

This paper presents the use of recursive least squares for online estimation of the self interference channel for an In Band Full Duplex communications link without the use of half duplex pilot signals. By using a long effective filter length it is possible to overcome the extra interference of the receieved signal, and it proves to be an effective way to estimate the channel in all scenarios, but it provides the greatest efficiency gain over current methods with a short channel coherence time. Recursive least squares estimation provides a way to take advantage of the constant knowledge of the transmitted signal to track the channel while consuming relatively few computational resources. Introducing online RLS estimation for In-Band Full Duplex communication provides a way to take advantage of the self interference cancellation gains from digital cancellation without introducing additional protocol overhead to the transmissions.

Wireless energy transfer capability and multi-tier network architecture are both envisioned as inherent features of the next generation wireless networks, on account of exponentially increasing low power connected devices and the rising concern about their limited battery life. In this paper, we investigate joint resource allocation problem, for wireless information and energy transfer in small cells overlaid by macrocell. Using scalarization technique of multi-objective programming, we jointly optimize energy harvesting rate and achievable throughput of small-cell users while ensuring that minimum throughput requirement of macrocell user is satisfied. The formulated MINLP problem is converted to convex optimization problem by relaxing some variables and introducing auxiliary variables. We highlight the condition at which the obtained solution is the optimal solution of the original problem. Numerical results are presented to analyze the performance of the proposed resource allocation framework and show the improvement in achieved energy harvesting rate, by comparing with a benchmark scheme.

Wireless information and energy transfer in multitier cellular networks is a new research paradigm in wireless communications. While interference mitigation is one of the major challenges in conventional multi-tier networks, wireless energy harvesting capability considers interference signal as a source of energy. In this paper, we consider simultaneous wireless information and energy transfer in two-tier cellular networks and perform downlink power allocation with two different objectives. To maximize the sum of energy harvesting rate of small cell users, we formulate a linear programming problem whereas to maximize the sum of their information rate, we formulate a non-convex optimization problem. We solve the non-convex optimization problem by using convex-concave procedure and dual decomposition method. Numerical results indicate that the small cell users are exposed to high interference signal when maximum energy harvesting rate is desired and that received interference contributes a large portion of their total harvested energy. The trade-off between information rate and energy harvesting rate is found to be more prominent in terms of the interference signal rather than the power splitting factor since both information rate and energy harvesting rate are maximized when infinitesimally small power is split to the information decoder circuit.

In this paper, resource allocation for energy-efficient communications in a pilot-contaminated uplink multi-cell massive MIMO system with MRC detectors is investigated. The problem of maximizing energy efficiency (EE) of data transmissions in the system is studied by optimizing the number of antennas per BS, the pilot signal power, and the data signal power. The considered optimization problem takes into account the circuit power consumption, pilot contamination, and budget constraints in the number of antennas per Base Station (BS) and the average transmission power per symbol. The resulting optimization problem has a non-convex fractional objective function which is difficult to solve in its original form. Therefore, principles from fractional programming are used to first transform the problem into an equivalent parametric form and then to derive an iterative resource allocation algorithm. In each iteration, an alternating optimization technique is used to solve the objective function by decomposing it into a sequence of solvable difference of convex (D.C) programming subproblems. Simulation results show that higher EE levels can be achieved by optimizing the pilot and data powers separately. Also, increasing the number of antennas per BS with the power budget may or may not be energy-efficient, depending on the range of operation.

We propose a distributed beamforming for cooperative cognitive radio (CR) networks, that reduces the required feedback overhead in terms of sharing the channel state information (CSI) between the cooperating CR relays. Assuming the reciprocity of the channels of each cooperating CR node toward the CR receiver, as well as toward the primary receiver, the proposed beamforming technique only requires sharing the location information of the CR relays among the cooperating CR relays, rather than the global CSI. Reducing the required feedback overhead provides enhanced scalability of the cooperative CR network with lower deployment cost. In this paper, we also propose two autonomous decision making strategies that can help each CR user to independently decide whether to participate in the cooperative transmission or not. This participation decision is tackled from a game theoretic approach, by quantifying the reward and cost functions of each CR relay. The first proposed strategy, named regret testing-based strategy, is proved to asymptotically achieve an approximate Nash equilibrium state of the system. However, it has higher complexity and slower convergence time. So we also propose a suboptimal decision making strategy, named learning-based strategy, that has lower complexity and faster convergence time.

Adaptive link selection for buffer-aided relaying can provide significant performance gains compared to conventional relaying with fixed transmission schedule, when perfect channel state information (CSI) is available for link selection. However, in practice, link selection may have to be performed based on outdated CSI, because of infrequent feedback of CSI and/or feedback delay. In this paper, we study the effect of outdated CSI on the error rate performance of adaptive link selection for a three node decode-and-forward (DF) relay network with fixed-rate transmission. In particular, we propose two protocols for link selection based on whether the reliability of the CSI estimates is known or not. For both protocols, we provide a unified error-rate analysis in terms of a decision threshold β, which can be adjusted to maintain buffer stability, and derive asymptotic approximations, which reveal the diversity and coding gains. Since packet transmission delay is unavoidable for opportunistic link selection, we analyze the average delay and throughput considering both finite and infinite buffer size. The average delay and throughput are functions of the decision threshold β, which can be optimized to minimize the error rate while satisfying average delay and/or throughput constraints. Numerical results manifest that even with outdated CSI, adaptive link selection provides a significant coding gain advantage over conventional DF relaying. Furthermore, we show that a diversity gain of two can be achieved for perfect CSI and the optimum error rate can be approached with small delay and/or high throughput.

We study the downlink resource allocation problem for simultaneous wireless information and power transfer (SWIPT) in small cells underlaying a macrocell in a two-tier heterogeneous network. For SWIPT, we consider both time-switching and power-splitting approaches. We determine downlink transmit power of small cell base stations along with time-switching/power-splitting variables for SWIPT to jointly optimize energy harvesting rate and achievable throughput of small cell users while ensuring minimum throughput of macrocell user. In the time-switching approach, the resource allocation problem is formulated as a mixed-integer non-linear programming (MINLP) problem. The formulated MINLP problem is solved by relaxing the binary integer constraint and then identifying the condition at which the obtained solution satisfies that constraint. In both the time-switching and power-splitting approaches, in the presence of non-negligible co-tier interference, the formulated problem is solved sub-optimally by iteratively maximizing the minorant of the non-convex objective function. A special case with negligible co-tier interference is considered in the time-switching approach and the optimal solution is obtained by using convex optimization techniques. Numerical results demonstrate significant gain in energy harvesting rate when macrocell users have flexible interference tolerance levels in time-switching approach, highlight the improvement in energy harvesting rate in the presence of co-tier interference signal, and reveal interesting trade-off in achievable throughput and energy harvesting rate.

We propose relay-based wireless-powered uplink cellular networks in which users first harvest energy from RF transmissions of base station/relay nodes and then use that energy for uplink transmission. Given the limited total transmission time and available energy at the relay node, we propose different resource allocation frameworks for the proposed relay-based networks considering two different relay-based harvest-then-transmit scenarios. We first propose iterative algorithm to determine time and relay node power allocation (for downlink wireless charging and uplink data transmission/relaying) for both scenarios. We then perform joint optimal time and power allocation for one scenario. Resource allocation results show that most of the available resources (transmission time and relay node energy) are allocated for wireless energy harvesting which is similar to that observed for downlink simultaneous wireless information and power transfer (SWIPT) in the existing literature. Simulation results on comparison of different relay-based scenarios reveal interesting insights and demonstrate remarkable improvement of different performance metrics of wireless-powered cellular networks in the presence of relay node.

In this paper, we propose quality-of-service (QoS) based resource allocation (RA) schemes for energy harvesting (EH) systems. We consider a system model with a single source and multiple destination nodes or users, in which the source node harvests energy from the environment. Our goal is to develop efficient RA policies for EH systems when the harvested energy at the source node is uncertain and insufficient to satisfy the QoS of the users completely. We develop two different schemes and RA policies to address this problem. In the first scheme, we minimize the total dissatisfaction of the users over a finite period of time through goal programming approach. In the second scheme, we maximize the number of admitted users and provide guaranteed QoS to them. For both schemes, we first develop offline algorithms assuming the availability of perfect and complete information about the harvested energy and channel state information (CSI). Next, we devise online algorithms based on dynamic programming (DP) considering the availability of causal information about the harvested energy and CSI. Numerical results demonstrate the effectiveness of our proposed algorithms and the importance of QoS provisioning based RA schemes in EH systems.

In this paper, we consider the resource allocation in two-tier wireless systems in which small-cell base stations harvest energy from renewable sources in addition to the conventional power grid. Moreover, we assume that each cell has access to an energy storage system with a limited battery capacity. We introduce new mechanisms that enable an efficient allocation of the available energy over time across the network. In doing so, we take into account the time-varying fading channel, the inter-cell interference and the fluctuations of harvested energy. In particular, we propose convergent offline algorithms to maximize the network energy efficiency while satisfying an average sum-rate constraint at each cell. Furthermore, we extend the resource allocation scheme by enabling an energy cooperation between the cells. By cooperating, they can exchange their harvested energy through a smart-grid power infrastructure. Using numerical simulations, we verify the convergence of the proposed algorithms and analyze the efficacy of the resource allocation and energy cooperation schemes.

The problem of joint downlink cell association (CA) and wireless backhaul bandwidth allocation (WBBA) in two-tier cellular heterogeneous networks (HetNets) is investigated. Large-scale antenna array is implemented at the macro base station (BS), while the small cells within the macro cell range are single-antenna BSs and they rely on over-the-air links to the macro BS for backhauling. A sum logarithmic user rate maximization problem is studied under the wireless backhaul constraints. Duplex and spectrum sharing with co-channel reverse time-division duplex (TDD) and dynamic soft frequency reuse is considered for interference management in the two-tier HetNet employing large-scale antenna arrays at the macro BS and wireless backhauling for small cells. Two in-band WBBA scenarios, namely, unified bandwidth allocation and per-small-cell bandwidth allocation, are investigated for joint CA-WBBA in the HetNet. A two-level hierarchical decomposition method for relaxed optimization is employed to solve the mixed-integer nonlinear program (MINLP). Solutions based on the General Algorithm Modeling System (GAMS) optimization solver and fast heuristics are also proposed for cell association in the per-small-cell WBBA scenario. It is shown that when all small cells have to use in-band wireless backhaul, the system load has more impact on both the sum logarithmic rate and per-user rate performance than the number of small cells deployed within the macro cell range. The proposed joint CA-WBBA algorithms have an optimal load approximately equal to the size of the large-scale antenna array at the macro BS. The cell range expansion (CRE) strategy, which is an efficient cell association scheme for HetNets with ideal backhauling, is shown to be inefficient when in-band wireless backhauling for small cells comes into play.

In this paper, we consider the robust transceiver design for a multi-hop full-duplex decode-and-forward (DF) relay system employing single-carrier transmission with frequency-domain equalization (SC-FDE). We take into account the effect of imperfect channel state information (CSI) where the CSI errors are modeled as Gaussian random variables with known statistics. The design of the precoding at the transmitter and the equalization at the receiver is formulated as an optimization problem with the objective to minimize two relevant performance metrics, namely, the sum mean-square error (MSE) and the maximum MSE across the different hops, subject to separate transmit power constraints for the nodes. We show that the equalization filters can be optimized individually at the receiving nodes and take the form of robust Wiener filters. However, due to the loopback/backward interference, the transmit signals in the different hops are coupled and the transmit precoding problem leads to a nonconvex power allocation problem in the frequency domain. To find the optimal power allocation, we first employ a sequential geometric programming (sGP) approach, which uses the condensation technique to transform the objective function into a posynomial and then solves a sequence of standard GP problems. The sGP approach requires global channel knowledge at a central node and the involved subproblems admit only numerical solutions. To gain further insight into the structure of the problem, we also consider an alternating optimization (AO) approach for power allocation where convex programming problems and difference of convex programming problems are solved in an alternating manner. The resulting AO algorithm admits closed-form solutions in each iteration step and requires less signaling overhead compared to the centralized sGP scheme. Numerical results for the MSEs and achievable rates of the proposed robust schemes are provided, showing that the proposed sGP and AO algorithms yield significant performance gains compared to conventional half-duplex relay systems and nonrobust full-duplex designs.

In this paper, we consider secure downlink transmission in a multicell massive multiple-input multiple-output (MIMO) system where the numbers of base station (BS) antennas, mobile terminals, and eavesdropper antennas are asymptotically large. The channel state information of the eavesdropper is assumed to be unavailable at the BS and hence, linear precoding of data and artificial noise (AN) are employed for secrecy enhancement. Four different data precoders (i.e., selfish zero-forcing (ZF)/regularized channel inversion (RCI) and collaborative ZF/RCI precoders) and three different AN precoders (i.e., random, selfish/collaborative null-space-based precoders) are investigated and the corresponding achievable ergodic secrecy rates are analyzed. Our analysis includes the effects of uplink channel estimation, pilot contamination, multicell interference, and path-loss. Furthermore, to strike a balance between complexity and performance, linear precoders that are based on matrix polynomials are proposed for both data and AN precoding. The polynomial coefficients of the data and AN precoders are optimized, respectively, for minimization of the sum-mean-squared-error of and the AN leakage to the mobile terminals in the cell of interest using tools from free probability and random matrix theory. Our analytical and simulation results provide interesting insights for the design of secure multicell massive MIMO systems and reveal that the proposed polynomial data and AN precoders closely approach the performance of selfish RCI data and null-space-based AN precoders, respectively.

In a cognitive radio (CR) network, a group of CR users can act as relays for a given user to improve the quality of communications for this user. To achieve such cooperative transmission, we propose a distributed beamforming technique that reduces the required feedback overhead in terms of sharing the channel state information between the cooperating CR relays. In return for their cooperation, the assisted CR user can lease its own channel, for a certain amount of time, to the cooperating CR relays for their opportunistic access. However, a particular CR relay spends a certain amount of power to forward the data to the assisted CR user. Therefore, we also propose an autonomous decision making strategy that can help each CR user to independently decide whether to participate in the cooperative transmission or not, by quantifying the reward and cost functions of each CR relay. The presented numerical results show an enhancement in the achievable sum rate of the cooperative CR network up to 43% for a primary channel occupancy probability of 0.3, compared to the case of non cooperative transmission.

In this paper, we address the problem of resource allocation with quality-of-service (QoS) provisioning for an energy harvesting system with a single source node and multiple users (destination nodes). We consider that the source node harvests energy from the environment, which is insufficient to satisfy the QoS of the users due to its random nature. We develop resource allocation schemes to minimize the dissatisfaction of the users through goal programming approach. First, we develop an offline scheme assuming that complete information about the harvested energy and channel state information (CSI) is available. The optimization problem is formulated as convex and efficient solution is provided based on dual decomposition algorithm. Next, we devise an online scheme considering the availability of causal and incomplete information about the harvested energy and CSI. We propose an algorithm based on dynamic programming to obtain the online optimal solution. Numerical results demonstrate the effectiveness of our proposed schemes in terms of fairness and the importance of QoS provisioning in energy harvesting systems.

In this paper, we consider the robust transceiver design for a two-hop full-duplex decode-and-forward relay system employing single-carrier transmission with frequency-domain equalization (SC-FDE). The design problem for the transmit precoding and receive equalization is formulated as an optimization problem with the objective to minimize the sum mean-squared error (MSE) of the two hops subject to separate node transmit power constraints. We show that the equalization filters can be optimized individually at the receiving nodes and take the form of robust Wiener filters. However, due to the loopback interference, the transmissions in the two hops are coupled and the transmit precoding problem boils down to a non-convex power allocation problem in the frequency domain. An alternating optimization approach is proposed to obtain the power allocation where convex programming problems and difference of convex programming problems are solved in an alternating manner. Numerical results are provided to validate the MSE and the achievable rate of the proposed robust schemes, showing that significant performance gains can be achieved compared to conventional half-duplex systems and non-robust full-duplex designs.

This paper addresses the cell association problem in the downlink of a multi-tier heterogeneous network (HetNet), where base stations (BSs) have finite number of resource blocks (RBs) available to distribute among their associated users. Two problems are defined and treated in this paper: sum utility of long term rate maximization with long term rate quality of service (QoS) constraints and global outage probability minimization with outage QoS constraints. The first problem is well-suited for slow fading environments, while the second problem provides a framework to deal with environments with fast fading. The defined optimization problems in this paper are solved in two phases: cell association phase followed by the optional RB distribution phase. We show that the cell association phase of both problems have the same structure. Based on this similarity, we propose a unified distributed algorithm with low levels of message passing for the cell association phase. This distributed algorithm is derived by relaxing the association constraints and using Lagrange dual decomposition method. In the RB distribution phase, the remaining RBs after the cell association phase are distributed among the users. Simulation results show that our distributed cell association scheme outperforms schemes that are based on maximum signal to interference plus noise ratio (SINR).

This paper addresses a joint downlink and uplink aware cell association problem in a multi-tier heterogeneous network in which base stations (BSs) have finite number of resource blocks (RBs) to distribute among the users. An optimization problem is defined to maximize the sum of weighted utility of long term data rate in downlink and uplink through cell association and RB distribution while maintaining quality of service (QoS). Separate outage requirements are considered as QoS constraints for downlink and uplink of a user. Using outage QoS constraints renders the problem suitable for fast fading environments. We propose a distributed scheme for the cell association problem. As users cannot measure the uplink attributes by listening to the reference signals of BSs, a limited amount of feedback is added to the reference signals of the BSs to inform the users of the uplink interference and make the distributed algorithm design possible. Moreover, by assigning different weights to the downlink and uplink data rates, the proposed scheme can be downlink oriented, uplink oriented, or both downlink and uplink aware. Comparing the proposed scheme with the downlink oriented maximum signal to interference plus noise ratio (SINR) scheme, significant uplink rate gains are observed in the simulations as well as for the downlink rates.

We develop robust resource-allocation schemes for a cognitive radio network (CRN), where the secondary users (SUs) try to communicate with each other from different small cell primary user (PU) networks. User cooperation technique is considered for communication among the SUs since PUs are in close proximity and there are tight interference constraints on the PU bands. Power allocation and relay selection schemes are optimized with the provision of quality of service to each SU considering different channel uncertainty models. We incorporate the channel outage events that have resulted from the imperfect channel state information under slow-fading channels in our resource optimization algorithms. We maximize the system goodput of the CRN while satisfying the interference constraints of the PU bands both probabilistically and for the worst case scenario. The original probabilistic optimization problem is approximated and transformed into a convex deterministic form, and a closed-form analytical solution for power allocation is derived. The closed-form power allocation solution helps us to develop an efficient relay selection scheme based on Hungarian algorithm. Simulation results reveal the effectiveness of our proposed schemes and the implications of ignoring the imperfectness among different channels when developing resource-allocation algorithms for CRNs.

To support the surge in wireless data traffic, the spectrum and energy efficiencies of cellular networks should be largely increased. Heterogeneous two-tier architecture has been identified as one key solution. However, small-cell deployment raises questions about the resulting energy efficiency and interference mitigation. Therefore, we propose an energy-efficient and cognitive spectrum sharing scheme between primary macrocell and secondary small cells. Specifically, the small cells allocate their transmission power to maximize their total energy efficiency while respecting some interference constraints imposed by macrocell users. We solve this centralized optimization in two steps. First, assuming that the small-cell transmissions are noninterfering, the solution of this nonconvex optimization is characterized using a convex parametric approach. Using this characterization, we derive an algorithm based on Newton method, which converges to a global optimal solution. Second, when the small-cell transmissions are not necessarily orthogonal, we derive an algorithm, which converges at least to a local optimum, using the minorization-maximization principle and Newton method. Through simulations, we validate the convergence of these algorithms and compare their performance with existing schemes. We also analyze the effects of the interference and of the number of users on the energy efficiency.

In this paper, we study the robust design of the relay beamforming (rBF) and destination equalization (dEQ) filters for broadband multiuser multi-relay networks employing single-carrier frequency-division multiple access (SC-FDMA) and orthogonal frequency-division multiple access (OFDMA). Thereby, we consider the realistic case where only imperfect channel state information is available for rBF and dEQ filter optimization. Our goal is to maximize a lower bound for the weighted achievable bit rate (ABR) of the network, subject to either individual relay power constraints (Ind-PCs) or an aggregate relay power constraint (Agg-PC). We first derive the optimal dEQ filters and the phases of the optimal rBF filter coefficients, which are independent of the power constraints. For the Agg-PC, the amplitude optimization of the rBF filter coefficients is decomposed into two subproblems, which correspond to the optimization of the power allocation across the relays and the power allocation across the users and subcarriers, respectively. We obtain a closed-form structural solution for the first subproblem by fixing the powers across users and subcarriers, and the global optimal solution for the second subproblem. For the Ind-PCs, the corresponding optimization problem is formulated as a reverse-convex problem with convex constraints. Subsequently, the constrained convex concave procedure is applied to approximate the original non-convex problem with a sequence of convex problems, which can be efficiently solved using convex optimization techniques. Simulation results validate the excellent performance of the proposed robust rBF and dEQ filter designs and show their superiority compared to conventional non-robust and naive relaying schemes.

This paper addresses the cell association problem in the downlink of a multi-tier heterogeneous network (HetNet), where base stations (BSs) have finite number of resource blocks (RBs) available to distribute among their associated users. We define the global outage probability as the event where at least one user in the network experiences outage. An optimization problem is defined to minimize this global outage probability while maintaining quality of service (QoS) through two phases: Cell association phase followed by the optional RB distribution phase. The cell association problem is an NP-hard problem. We transform the cell association problem into a linear program, for which we propose a distributed cell association algorithm by using Lagrange dual decomposition method. An admission control scheme is also proposed to address the infeasibility problem and achieve load balancing. Finally, the effectiveness of our proposed distributed algorithm is examined through numerical simulations.

In this work, we propose a robust cooperative relay beamforming (rBF) design for single-carrier frequency-division multiple access (SC-FDMA) based multiuser multi-relay systems with imperfect channel state information. We maximize a lower bound on the achievable bit rate (ABR) of the network, subject to an aggregate relay transmit power constraint. Employing the primal decomposition technique, we decompose the problem into two subproblems: the rBF coefficient optimization and the relay power allocation. For a given power allocation across the frequency tones, a closed-form solution for the rBF matrices is obtained first. Subsequently, the convexity of the remaining power allocation problem is then proved, and efficient convex optimization methods are employed to find the global optimum. Simulation results validate the excellent performance of the proposed rBF schemes and show their superiority compared to conventional non-robust designs.

In this paper, we develop joint resource allocation algorithm for selective user cooperation based OFDMA systems with energy harvesting technology. When relaying is beneficial for the network, mobile users with good channel conditions and low traffic demands can play the role of relays. The mobile user equipments are capable of energy harvesting using "wireless power transfer" technology and only the harvested energy is used for cooperation. The joint optimization problem of power and subcarrier allocation and relay selection is a mixed integer nonlinear program, which is very difficult to solve in general. We propose a novel scheme to solve the problem optimally with polynomial time complexity using dual decomposition approach. Numerical results demonstrate the effectiveness of the proposed scheme in terms of energy efficiency compared to the other existing models in the literature.

Recent studies have shown that buffer-aided relaying with adaptive link selection can provide significant performance gains compared to conventional relaying using a fixed transmission schedule. In this paper, we focus on error rate analysis of adaptive link selection for a three node decode-and-forward (DF) relay network with fixed-rate transmission. As in practice link selection may be performed based on outdated channel state information (CSI) because of a delay in the feedback link, we study the error rate performance for both perfect and outdated CSI. Since a packet transmission delay is unavoidable with opportunistic link selection, we provide a unified error-rate analysis in terms of a decision threshold β which can be adjusted to achieve buffer stability and a desired average system delay. We show that a diversity gain of two can be achieved for perfect CSI and the optimum BER can be approached even if only a small delay is tolerated.

In this paper, a joint resource optimization scheme is designed for orthogonal frequency division multiple access (OFDMA) cellular wireless networks with multi-user cooperation. Joint relay selection, subcarrier allocation and pairing and power allocation algorithms are developed with the objective of maximizing the total capacity of the system considering the quality of service (QoS) requirements of the users. The optimization problem is a mixed integer nonlinear program (MINLP), which is often very difficult to solve in its original form. We provide a novel optimization framework to solve such non-linear optimization problems. The joint relay selection and subcarrier allocation problem is modified to a linear assignment problem and an efficient algorithm is developed to obtain the optimal assignment solution based on the Hungarian method. We propose computationally efficient solution to the joint resource optimization problem via dual decomposition method. Numerical results demonstrate the effectiveness of our proposed scheme.

In this work, we investigate the robust energy-efficient transmission for the cognitive uplink wireless system. Precisely, we propose an optimization framework for maximizing the sum energy efficiency while taking into account the uncertainty of the channel between the primary and secondary users. Here, we assume that the base station has multiple antennas and employs a zero-forcing receive filter to eliminate the inter-user interference. We handle the intractability of the probabilistic interference constraints by approximating them with convex and linear surrogate constraints. Despite the non-convexity of the utility function, we propose a parametric convex programming approach to derive an optimal algorithm based on Newton method. Through numerical simulations, we show the convergence and effectiveness of the proposed method and analyze the effect of channel uncertainty on the energy efficiency of the cognitive uplink system.

In this paper, we study the application of bit-interleaved coded modulation (BICM) and orthogonal frequency division multiplexing (OFDM) to reap the benefits of wireless multiuser network coding in practical frequency-selective fading channels. We propose a mapping based symbol level network coding (SLNC) scheme for a cooperative diversity system comprising multiple sources, multiple relays, and one common destination. A simple cooperative maximum-ratio combining scheme is used at the destination and is shown to successfully exploit both the full spatial and the full frequency diversity offered by the channel for arbitrary numbers of sources, arbitrary numbers of relays, and arbitrary linear modulation schemes. To gain analytical insight for system design, we derive a closed-form upper bound for the asymptotic worst-case pairwise error probability (PEP) and obtain the diversity gain of the considered SLNC scheme for BICM-OFDM systems. These analytical results reveal the influence of the various system parameters, such as the number of sources, the free distance of the code, and the frequency diversity of the involved links, on performance. Furthermore, we propose two different relay selection schemes for the considered system: a) bulk selection, i.e., a single best relay is selected to transmit on all sub-carriers, and b) per-subcarrier selection, where a best relay is selected on each sub-carrier. Last but not least, we exploit the derived PEP expression for selecting a subset of sources from the set of active sources when the number of active sources is larger than the number of available orthogonal relay channels. We study the achievable diversity gain for the proposed relay and source subset selection schemes. Numerical results corroborate the derived diversity gain expressions and confirm the performance gains.

In this paper, an energy-efficient resource allocation scheme is designed for orthogonal frequency-division multiple-access cellular wireless networks with multiuser cooperation. Joint relay selection, subcarrier allocation and pairing, and power-allocation algorithms are developed with the objective of maximizing the energy efficiency of the system considering the quality-of-service requirements of the users. The optimization problem is a mixed-integer nonlinear program (MINLP), which is generally very difficult to solve in its original form. The energy efficiency metric is a fractional and nonlinear function, which complicates the problem further. We provide a novel optimization framework to solve such nonlinear and nonconvex optimization problems. The MINLP optimization problem is reformulated to a convex problem by relaxing the integer variables and by introducing the "Dinkelbach" method to tackle the nonlinear fractional objective function. We prove that our proposed solution of the relaxed problem is optimal and has integer values. Based on the dual-decomposition method, we propose a solution to the joint optimization problem, which is optimal and computationally efficient with polynomial-time complexity. Numerical results demonstrate the effectiveness of our proposed scheme.

We investigate the trade-off between performance and energy efficiency in cooperative cognitive underlay systems. By cooperating, cognitive base stations mitigate the interference and serve their users more effectively at the cost of spending more power. With a flexible cooperation scheme, we thus jointly optimize the clustering and the beamforming to minimize the overall power consumption while satisfying the secondary users' quality of service and respecting the primary users' interference limits. We formulate this problem as a mixed-integer nonlinear program and decompose it into a master problem and a beamforming subproblem. Then, we derive an iterative algorithm based on the generalized Benders decomposition method to find an optimal solution. Moreover, we propose simple techniques to speed up its convergence. When the clusters are fixed and non-overlapping, we also propose a decentralized algorithm with limited signaling schemes using the alternating direction method of multipliers. In contrast to previous works, our distributed algorithm handles the total interference power constraints coupling the cognitive base stations. Through simulations, we analyze the effectiveness and convergence of the proposed algorithms and show the benefits of the cooperation in cognitive wireless networks.

In this paper, we consider physical layer security provisioning in multicell massive multiple-input-multiple-output (MIMO) systems. Specifically, we consider secure downlink transmission in a multicell massive MIMO system with matched-filter precoding and artificial noise (AN) generation at the base station (BS) in the presence of a passive multiantenna eavesdropper. We investigate the resulting achievable ergodic secrecy rate and the secrecy outage probability for the cases of perfect training and pilot contamination. Thereby, we consider two different AN shaping matrices, namely, the conventional AN shaping matrix, where the AN is transmitted in the null space of the matrix formed by all user channels, and a random AN shaping matrix, which avoids the complexity associated with finding the null space of a large matrix. Our analytical and numerical results reveal the following, in multicell massive MIMO systems employing matched-filter precoding: 1) AN generation is required to achieve a positive ergodic secrecy rate if the user and the eavesdropper experience the same path loss; 2) even with AN generation, secure transmission may not be possible if the number of eavesdropper antennas is too large and not enough power is allocated to channel estimation; 3) for a given fraction of power allocated to AN and a given number of users, in case of pilot contamination, the ergodic secrecy rate is not a monotonically increasing function of the number of BS antennas; and 4) random AN shaping matrices provide a favorable performance/complexity tradeoff and are an attractive alternative to conventional AN shaping matrices.

In this paper, we consider a multisource multirelay network where relays employ buffers to store the received user data packets before forwarding them to a common destination. The transmission schedule, i.e., when each source and each relay transmit, is not a priori fixed, but rather depends on the link qualities. In particular, we consider adaptive link selection and adaptive rate transmission for the considered network. For simple three node relay networks, it was shown before that buffer-aided relaying with adaptive link selection yields significant throughput gains compared to conventional relaying protocols using a fixed transmission schedule. In this work, we consider a general multisource multirelay framework where operations are more complex and analysis is more involved. First, we consider average sum rate maximization for adaptive rate transmission and derive an adaptive link selection policy which exploits the channel state information. As fairness is an important issue in multisource networks, we also consider max-min fairness constrained throughput optimization and derive the corresponding link selection policy. Numerical results show that the proposed link selection policies yield significantly higher throughputs compared to conventional relaying schemes where source and relay transmission schedules are a-priori fixed.

In this paper, we propose distributed subcarrier pairing and relay selection for OFDM based cooperative systems. Our objective is to maximize the throughput of the network using minimal signaling overhead when uniform power allocation is performed at the subcarriers. Since the optimal centralized solution for the formulated problem requires high signaling overhead and processing complexity, we propose two suboptimal distributed algorithms scalable and suitable for practical implementation. The first proposed algorithm is based on Hungarian method and is efficient in terms of signaling overhead reduction. The performance of this algorithm is extremely close to the optimal solution for large number of subcarriers. The second proposed distributed algorithm has lower complexity and it significantly reduces the signaling overhead at the expense of a small degradation in performance. Numerical results reveal the effectiveness of the proposed algorithms and demonstrate the superiority over other existing algorithms in the literature.

Energy-aware power allocation in cooperative communication systems depends on the availability of channel state information (CSI), which is often imperfect in practice. This paper proposes energy-aware, optimal power allocation schemes for an amplify-and-forward cooperative communication system in the presence of imperfect CSI, to i) minimize the total transmit power; ii) maximize the end-to-end signal-to-noise ratio (SNR). Energy awareness is incorporated in the schemes either by avoiding over-provisioning of quality-of-service (QoS) or, by preventing unsuccessful transmissions, depending on the application. In both the schemes, the source and relay nodes share a fixed total transmit power budget, and transmission is allowed only if the minimum required end-to-end SNR can be achieved with the available power budget. Closed-form expressions for the source and relay optimal transmit powers are derived for both these schemes. Performance of the systems under the proposed schemes are investigated through simulations.

In this paper, we propose robust power allocation and admission control schemes for providing probabilistically constrained quality of service (QoS) in selective relaying based decode-and-forward (DF) cooperative cellular systems. The proposed schemes are robust against imperfect channel state information (CSI) in slow fading while optimizing the total uplink transmit power in these cooperative wireless networks. At first, we derive novel closed-form solutions for the optimization problem, where the objective is to minimize total uplink transmit power while meeting the probabilistic QoS guarantees for a given number of admitted users. This is achieved by approximating the probabilistic optimization problem into a convex deterministic form and then by deriving closed form analytical solutions for power allocation using Karush-Kuhn-Tucker (KKT) conditions. The closed-form property of these solutions allows us later to develop a very low-complexity suboptimal algorithm for joint admission control and power allocation in presence of imperfect CSI and selective relaying. We also conduct comprehensive simulation experiments to demonstrate the effectiveness of our proposed schemes and to highlight the benefits gained from considering channel estimation errors in resource allocation for cooperative cellular systems.

User cooperation although improves performance of wireless systems, it requires incentives for the potential cooperating nodes to spend their energy acting as relays. Moreover, these potential relays are better informed than the source about their transmission costs, which depend on the exact channel conditions on their relay-destination links. This results in asymmetry of available information between the source and the relays. In this paper, we use contract theory to tackle the problem of relay selection under asymmetric information in OFDM-based cooperative wireless system that employs decode-and-forward (DF) relaying. We first design incentive compatible offers/contracts, consisting of a menu of payments and desired signal-to-noise-ratios (SNR)s at the destination. The source then broadcasts this menu to nearby mobile nodes. The nearby mobile nodes which are willing to relay, notify back the source with the contracts they agree to accept in each subcarrier. We show that when the source is under a budget constraint, the problem of relay selection in each subcarrier with the goal of maximizing capacity is a nonlinear non-separable knapsack problem. We propose a heuristic relay selection scheme to solve this problem. We compare the performance of our overall mechanism and the heuristic solution with a simple relay selection scheme. Selected numerical results show that our solution performs better and is close to optimal. The benefits of the overall mechanism introduced in this thesis is that it is simple to implement, needs limited interaction with potential relays and hence it requires minimal signalling overhead.

In this paper, we study a cooperative diversity scheme for wireless systems where the relay is equipped with a buffer. We consider practical frequency—selective channels and adopt the combination of bit interleaved coded modulation and orthogonal frequency division multiplexing (BICM—OFDM). We propose a novel link selection protocol for BICM—OFDM systems where the relay either transmits or receives in a given time slot depending on the quality of the links. We derive a closed—form upper bound for the asymptotic worst—case pairwise error probability (PEP) and the diversity gain of the considered buffer—aided relaying scheme for both infinite and finite buffer size. We show that significant diversity gains can be achieved with buffer—aided relaying compared to conventional relaying at the expense of larger packet delays. In fact, for buffers of infinite (or very large) size, the diversity gain is doubled for links with identical frequency diversity, and an even higher diversity gain advantage is possible for links with non—identical frequency diversities. Furthermore, we perform an exact closed—form average delay analysis for buffers of both finite and infinite size which provides important insight into the achieved delay—performance tradeoff. The derived analytical results and performance gains are corroborated by extensive simulation results.

In this paper, we propose a joint transceiver design for single-carrier frequency-domain equalization (SC-FDE) based multiple-input multiple-output (MIMO) relay systems. To this end, we first derive the optimal minimum mean-squared error linear and decision-feedback frequency-domain equalization filters at the destination along with the corresponding error covariance matrices at the output of the equalizer. Subsequently, we formulate the source and relay precoding matrix design problem as the minimization of a family of Schur-convex and Schur-concave functions of the mean-squared errors at the output of the equalizer under separate power constraints for the source and the relay. By exploiting properties of the error covariance matrix and results from majorization theory, we derive the optimal structures of the source and relay precoding matrices, which allows us to transform the matrix optimization problem into a scalar power optimization problem. Adopting a high signal-to-noise ratio approximation for the objective function, we obtain the global optimal solution for the power allocation variables. We illustrate the excellent performance of the proposed system and compare it to that of conventional orthogonal frequency-division multiplexing MIMO relay systems based on computer simulations.

In this paper, we propose a joint transceiver design for multiple-input multiple-output (MIMO) relay systems employing single-carrier frequency-domain equalization (SC-FDE). We first derive the optimal minimum mean-squared error (MMSE) frequency-domain linear equalization filter at the destination and the associated stream-wise MSEs at the output of the equalizer. Subsequently, we optimize the source and relay precoding matrices for various optimality criteria by minimizing a general function of the MSEs subject to separate source and relay power constraints. The structures of the optimal source and relay precoding matrices are obtained in closed form and the remaining power allocation problems are solved using an alternating optimization algorithm. Simulation results show that the proposed SC-FDE designs outperform orthogonal frequency-division multiplexing based MIMO relay systems in terms of both uncoded and coded bit error rate.

In this paper, we formulate an optimization problem for joint transmit beamforming, resource allocation, and user scheduling for multi-cell multi-user multiple-input multiple-output (MIMO) orthogonal frequency division multiple access (OFDMA) networks aiming at total average weighted system throughput maximization. Despite the non-convex and combinatorial characteristics of the resulting problem, we transform it into a standard convex optimization problem by introducing an extra sum interference constraint and certain relaxations, which leads to a lower bound for the original problem. Applying Lagrange dual decomposition, we successfully solve the transformed problem in a distributed manner with closed-form expressions for the optimal beamformers, power adaptation, and subcarrier allocation. Numerical results show that our proposed scheme provides a considerable performance gain compared to other existing strategies in terms of weighted system throughput.

In this paper, we develop robust power allocation schemes for cognitive radio networks (CRNs) that can operate in multiple bands with cooperative relays considering uncertainty among the channels of secondary user (SU) network and among the channels of SU transmitters to primary user (PU) receivers. Our objective is to formulate the robust design optimization problems taking into account the interference threshold in the PU band specified by the regulatory guidelines. To optimally allocate power with channel uncertainty, two robust algorithms are developed: (i) the worst-case optimization, where the interference constraints are satisfied for all channels contained in some bounded uncertainty regions, and (ii) the probabilistically constrained optimization, where interference constraints are satisfied with certain probabilities. We show that the formulated problems are convex, which can be efficiently solved. Numerical results show the effectiveness of the proposed schemes and the implications of ignoring the uncertainties among different channels when designing power allocation schemes for CRNs.

We consider the energy-efficient design of transmit beamforming in the downlink of a cognitive multi-cell wireless system. In this system, multiple secondary cells minimize their total transmit power while satisfying given SINR requirements for the secondary users. At the same time, the secondary base stations are not allowed to exceed aggregate interference temperature limits to the users of a primary system. We propose a distributed optimization framework to decompose this multi-cell problem into parallel single-cell beamforming subproblems. As a result, the cognitive cells independently compute their beamformers using only local channel information. Moreover, they coordinate their inter-cell interference as well as the interference temperature to the primary users by exchanging some signaling information through a backhaul. This coordination is achieved through a consensus-based optimization. In contrast to classical decomposition methods, our approach is based on the alternating direction method of multipliers. Therefore, it leverages the augmented Lagrangian technique to accelerate the interference coordination between the secondary cells, thanks to the quadratic penalty terms that are added in the objective function with the standard pricing terms. Numerical results are provided to verify the effectiveness of this distributed algorithm.

In this paper, we develop a power allocation scheme that works robustly under channel uncertainty for a decode-and-forward (DF) cooperative cellular multi-user network with multiple fixed relays. We propose a method for selective relaying, where cooperation takes place only if it is beneficial for the network in terms of total transmit power minimization or source power savings. Our objective is to provide energy efficiency by minimizing the power consumption of the network while meeting the rate requirements of the users. We consider the probabilistically constrained optimization approach, in which quality of service (QoS) constraint is satisfied for all users with certain probabilities. We transform the probabilistic optimization problem into a deterministic one and derive closed form analytical solutions. Simulation results show the effectiveness of our proposed algorithm.

Cooperative communication when other mobile nodes could act as potential relays, poses significant challenge in designing relay selection algorithms due to the information asymmetry between the source and the potential relays. The potential relays in this case are better informed about their channel conditions than the source. Therefore, the source must provide them with incentive to reveal their information and hence for their participation in relaying. In this paper, we study the problem of relay selection under a budget constraint when there is such an information asymmetry. By leaving the bargaining power only to the source, we propose a simple relay selection mechanism that requires limited interaction with potential relays and their participation is also voluntary. We will first use contract theory to formulate incentive compatible contracts that can be broadcasted to nearby mobile nodes which can act as potential relays. Once these mobile nodes notify the contracts they are willing to accept, source then optimally selects a set of relays based on this information. We analyze the performance of this mechanism by simulations and discuss the effect of information asymmetry.

We study a cellular system scenario where multiple data streams originating from a base station (BS) targeted to multiple cell-edge mobile stations (MSs) are transmitted via pre-installed cooperative relay stations (RSs) with multiple antennas. Our objective is to guarantee quality-of-service (QoS) in terms of predefined signal-to-noise ratio at such users within the transmit power budgets at BS and RSs while minimizing total transmit power. We propose a novel precoder design method for power allocation between multiple data streams at BS and RS by using joint zero-forcing strategy in order to avoid multiuser interference (MUI) in the signal received by MSs via both the direct and relay links. We also propose low-complexity suboptimal power allocation algorithm. We focus on analyzing the significance of direct link transmission in providing QoS to cell-edge MSs specially when RS is not situated directly between BS and MSs. Simulation results show that considering direct link and using the proposed scheme in such case significantly improves system outage performance compared to existing schemes in the literature which do not consider direct link.

Superposition modulation makes it possible for transmitting a node's own data along with its neighbors' relay data in a single time-slot and frequency, which can improve spectral efficiency of cooperative wireless communication system. First, we consider a two-user scenario and propose a design criterion for two-dimensional superposition modulation based cooperative transmission where the users cooperate to transmit their data to a base station. We investigate M-PSK superposition modulation based cooperative scenario for Rayleigh fading channels and thoroughly derive the average symbol error rate (SER) of such system with decode-and-forward relaying. Furthermore, we introduce a design parameter called power allocation ratio (PAR) which can be adaptively changed within the derived limits. We derive SER expressions in terms of the PAR and demonstrate its effect on average SER. Based on analytical and simulation results, we show that the proposed scheme provides reduced SER and increased spectral efficiency per link compared to existing schemes in practical scenarios. Finally, we investigate multi-user scenario, propose an adaptive power allocation scheme for superposition modulation, and confirm that SER is decreased with our proposed scheme.

There are two main approaches, static and dynamic, to broadcast algorithms in wireless ad hoc networks. In the static approach, local algorithms determine the status (forwarding/nonforwarding) of each node proactively based on local topology information and a globally known priority function. In this paper, we first show that local broadcast algorithms based on the static approach cannot achieve a good approximation factor to the optimum solution (an NP-hard problem). However, we show that a constant approximation factor is achievable if (relative) position information is available. In the dynamic approach, local algorithms determine the status of each node "on-the-fly” based on local topology information and broadcast state information. Using the dynamic approach, it was recently shown that local broadcast algorithms can achieve a constant approximation factor to the optimum solution when (approximate) position information is available. However, using position information can simplify the problem. Also, in some applications it may not be practical to have position information. Therefore, we wish to know whether local broadcast algorithms based on the dynamic approach can achieve a constant approximation factor without using position information. We answer this question in the positive-we design a local broadcast algorithm in which the status of each node is decided "on-the-fly” and prove that the algorithm can achieve both full delivery and a constant approximation to the optimum solution.

Energy consumption in wireless communication system is rapidly increasing due to growing wireless multimedia access. Combating adverse effects of excessive energy consumption demands for energy-aware system design, leading to a new research paradigm called green communication. In this paper, we propose user selection and power allocation schemes for a multi-user, multi-relay cooperative cellular system in order to minimize the cost of transmission. In the proposed schemes, the cost function is first formulated to optimize the weighted sum powers of base and relay stations. It is then extended to a more general multi-objective scheme which jointly optimizes the sum power and throughput keeping a balance between them. In both of the schemes, quality-of-service is guaranteed in terms of end-to-end signal-to-noise ratio. To make the proposed schemes realistic, we assume the presence of estimation errors in channel state information. An algorithm to enhance fairness among users in these schemes is also presented. Simulation results are presented to confirm the performance of proposed schemes in terms of energy efficiency, system throughput, outage probability, and fairness to end users.

In this paper, we study a cooperative diversity scheme for wireless systems employing network coding and the combination of bit-interleaved coded modulation (BICM) and orthogonal frequency division multiplexing (OFDM). The considered system comprises multiple sources, one relay, and one destination. The relay decodes the signal received from all sources and performs network coding before forwarding the signal to the destination. We propose a simple cooperative maximum-ratio combining scheme for the destination which can successfully exploit the full spatial and frequency diversity offered by the channel for arbitrary numbers of sources and arbitrary linear modulation schemes. Furthermore, we propose techniques to reduce the signaling overhead and the decoding complexity at the destination. To gain insight for system design, we derive a closed-form upper bound for the asymptotic worst-case pairwise error probability and the diversity gain of the considered network coded cooperative BICM-OFDM system. These analytical results reveal the influence of various system parameters, including the number of sources, the free distance of the code, and the frequency diversity of the involved links, on performance. Based on the derived analytical results, we develop schemes for optimal relay placement and power allocation. Simulation results corroborate the derived analytical results and confirm the effectiveness of the developed optimization framework.

In this letter, we investigate power allocation schemes for OFDM-based cognitive radio (CR) systems while taking errors due to imperfect sensing of primary user (PU) into account. The interference is introduced into PU band by CR user not only because of co-existence in side-by-side bands but also by missed detection due to imperfect sensing. We propose an optimal scheme such that the transmission capacity of CR users is maximized while keeping the total interference within a prescribed threshold and keeping the total power within a budget. As the optimal scheme can have a high complexity, low complexity suboptimal schemes have also been proposed. The performance of the proposed schemes is compared to the schemes that do not take sensing errors into consideration. Presented numerical results demonstrate the strength of our proposed schemes.

In this paper, we propose joint relay selection and power allocation algorithms that can work robustly under imperfect channel knowledge for a decode-and-forward (DF) cellular relay network. The objective is to minimize the uplink transmit power of the network taking each user's target data rate as the quality of service (QoS) constraint in the presence of imperfect channel state information (CSI). We consider the worst-case optimization approach, in which QoS constraint is satisfied for all users assuming both probabilistic and deterministic channel estimation error models. In this optimization framework, equivalent convex formulations are derived for the nonlinear optimization problems that are often combinatorially hard to solve in their original forms. After relay selection, efficient centralized as well as distributed power allocation algorithms scalable with respect to the size of the networks are developed. We also consider the case of power constrained networks where the objective is to provide QoS in the presence of limited power budgets on source and relays. The robust optimization problem is reformulated accordingly and efficient solution is provided. Numerical results show the effectiveness of the proposed algorithms and demonstrate the implications of ignoring channel estimation errors while developing relay selection and power allocation algorithms.

Superposition modulation provides an alternative approach to transmit a node's own data packets along with its neighbor's relay packets in the same time- slot and frequency, which can improve spectral efficiency of cooperative wireless communication system. We propose a design criterion for two- dimensional superposition modulation based cooperative transmission where two users cooperate to transmit their data to a base station. We investigate M-PSK superposition modulation based cooperative scenario for Rayleigh fading channels and thoroughly derive the average symbol error rate (SER) of such system with decode-and-forward relaying. Furthermore, we introduce a design parameter called power allocation ratio, i.e., ratio of transmit power for relay data to total power, which can be adaptively changed within the derived limit. We also derive SER expressions in terms of the power allocation ratio and demonstrate its effect on average SER. Based on analytical results and computer based simulations, we show that the proposed scheme provides reduced SER and increased goodput compared to existing schemes in practical scenarios.

In this paper, we study a cooperative diversity scheme for wireless systems employing network coding and the combination of bit-interleaved coded modulation (BICM) and orthogonal frequency division multiplexing (OFDM). The considered system comprises multiple sources, one relay, and one destination. The relay decodes the signal received from all sources and performs network coding before forwarding the signal to the destination. We propose a simple cooperative maximum-ratio combining scheme for decoding at the destination which can successfully exploit the full spatial and frequency diversity offered by the channel for arbitrary number of sources and arbitrary modulation schemes. We derive a closed-form upper bound for the asymptotic worst-case pairwise error probability and the diversity gain of the considered network coded cooperative BICM-OFDM scheme. Simulation results corroborate the derived diversity gain and show the effectiveness of a low complexity decoding scheme.

In this paper, we propose a joint relay selection and power allocation algorithm for a multi-user, multi relay cellular network using decode-and-forward cooperation strategy with imperfect knowledge of channels. The objective is to minimize the total uplink power of the network taking each user's target data rate as the quality of service constraint under imperfect channel state information (CSI), assuming some statistical knowledge is known about the channel estimation error. Joint relay selection and power allocation is a mixed integer programming problem which is combinatorially hard. For that an efficient sub-optimal solution with low complexity using convex relaxation approach is proposed. After relay selection, a centralized power allocation scheme is developed to optimally allocate the power among the users and the selected relay nodes. Then a low-complexity distributed algorithm is proposed based on a standard primal decomposition approach, where each selected relay can independently minimize its own power. Numerical results demonstrate the effectiveness of the proposed algorithms.

We address the problem of designing efficient resource allocation schemes for an OFDMA based multiuser cooperative communication system that uses amplify and forward relaying. With a two-phase relaying protocol, we assume that both source and the relay have fixed power constraints and that the source employs a selective relaying mechanism. That is, the source adaptively decides on which frequency subcarriers relaying has to performed. We first formulate the problem as a capacity maximizing integer programming optimization problem and then propose a heuristic solution that is composed of several subproblems. The first part is to suboptimally allocate subcarriers to different users based on proportional rate fairness. The next part is a two step iterative approach to find relay decisions and power allocation at the source during the first phase and at the relay during the second phase. The last step is a water-filling algorithm to allocate power at the source during the second phase to all non-relaying subcarriers. Simulation results show that this selective relaying mechanism outperforms the always relay case while also providing an approximate proportional rate fairness.

In this paper, we propose centralized and distributed power allocation algorithms for a multi-user, multi relay cellular network using decode-and-forward (DF) cooperation strategy taking channel uncertainty into account. The objective is to minimize the total uplink power of the network taking each user's target data rate as the quality of service (QoS) constraint under imperfect channel state information (CSI). We consider the worst-case optimization approach, in which QoS constraint is satisfied for all channels contained in some uncertainty region. First, a centralized power allocation scheme is developed to optimally allocate the power among the users and the relay nodes. Then, a suboptimal distributed algorithm is proposed based on a standard primal decomposition approach, where each relay can independently and separately minimize its own power. The proposed solutions are based on second order cone programming (SOCP), which is computationally efficient. Simulation results show that the performance of the suboptimal distributed solution is near-optimal and reveals the fact that DF cooperation strategy is more efficient in total power reduction and more robust under channel uncertainty over non-cooperative systems.

Relay-based cooperative transmission in cellular wireless networks has been an area of tremendous research recently. Since MIMO technique has been shown to increase the spectral efficiency significantly, relays with MIMO antennas seem to be potential candidate for future cooperative cellular system in order to achieve reliable transmission, high system throughput and extended network coverage. In this paper, we study a cellular system scenario where quality of service (QoS) of multiple data streams originating from a base station (BS) targeted to multiple mobile stations (MSs) is guaranteed by using pre-installed relay stations (RSs) with MIMO antennas. We propose a low-complexity algorithm to design precoder matrices at BS and RS by using joint zero-forcing strategy to avoid multiuser interference in the signal received at the MSs via both the direct path (BS-MS) and the relay path (BS-RS-MS). The proposed algorithm guarantees a predefined signal-to-noise ratio at each user within the transmit power constraint at BS and with the minimal sum transmit power of BS and RS. Simulation results show that proposed algorithm outperforms the singular value decomposition (SVD)-based scheme existing in the literature by keeping the outage probability lower. Moreover, the performance of proposed algorithm compared to that of SVD-based scheme is further improved when the RS is not situated directly between the BS and the MSs.

In this paper, we propose a novel cooperative diversity scheme for wireless systems employing the combination of bit-interleaved coded modulation (BICM) and orthogonal frequency division multiplexing (OFDM). The proposed scheme utilizes an amplify-and-forward protocol where relays are assigned to multiple groups. Relays in the same group transmit concurrently over disjoint sets of sub-carriers and relays in different groups transmit in different time slots. We derive closed-form expressions for the asymptotic worst-case pairwise error probability and the diversity gain of the proposed cooperative BICM-OFDM scheme. Based on the derived analytical results we develop design guidelines for sub-carrier allocation, relay grouping, and relay selection. Simulation results corroborate the derived analytical results and confirm the effectiveness of the developed optimization framework.

The paper presents design of a linear precoder for orthogonal space-time block coded orthogonal frequency division multiplexing (OFDM)-based multiple-input multiple-output (MIMO) antenna cognitive radio (CR) when operating in correlated Rayleigh fading channels. Unlike previous studies on precoder design for CR, this proposed linear precoder is capable of handling both transmit and receive correlation in a multi-carrier based CR system. The linear precoder is designed to minimize an upper bound on the average pairwise error probability, constrained to a set of per subcarrier transmit power constraints at the CR transmitter and a set of interference power thresholds at primary user receivers. The CR transmitter exploits the knowledge of transmit and receive correlation matrices while designing the precoder. It is shown that the linear precoder design problem is convex with these constraints, and convex optimization techniques are exploited to derive an efficient algorithm to obtain the optimal precoder matrices. Computer simulations are performed to investigate the performance of the proposed linear precoder in a CR system.

In this letter, we develop an optimal power allocation algorithm for the orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems with different statistical interference constraints imposed by different primary users (PUs). Given the fact that the interference constraints are met in a statistical manner, the CR transmitter does not require the instantaneous channel quality feedback from the PU receivers. A suboptimal algorithm with reduced complexity has been proposed and the performance has been investigated. Presented numerical results show that with our proposed optimal power allocation algorithm CR user can achieve significantly higher transmission capacity for given statistical interference constraints and a given power budget compared to the classical power allocation algorithms namely, uniform and water-filling power allocation algorithms. The suboptimal algorithm outperforms both water-filling algorithm and uniform power loading algorithm. The proposed suboptimal algorithm give an option of using a low complexity power allocation algorithm where complexity is an issue with a certain amount of transmission rate degradation.

In this letter, we investigate the relay and power allocation problem for OFDM-based cognitive radio (CR) systems with single antennae. We propose a method where the capacity of CR user employing relays is maximized while total transmission power is kept within a budget and the interference introduced to the primary user (PU) band is kept within a prescribed threshold. The optimization problem is a mixed-integer problem, which is NP-hard. Hence in this letter, we have proposed three sub-optimal schemes. The presented numerical results show that the performance of proposed suboptimal schemes is close to the optimal solution.

This paper investigates a decode-and-forward two-hop relaying system consisting of one source, one relay and one destination, in which orthogonal frequency division multiplexing is used. The relay forwards the message received from the source on a subset of available subcarriers in the second time slot. Firstly, a subcarrier pairing and selection algorithm is proposed, assuming that perfect channel state information (CSI) is available at all nodes, then, power is allocated to both the source and relay stations under individual power constraints in order to maximize the capacity. Secondly, subcarrier selection and pairing, and power allocation (PA) under partial CSI assumption along with individual power constraints are addressed. The result is a novel distributed algorithm with low complexity maximizing the expected value of capacity at the source and relay nodes. Finally, the simulation results show that selective relaying combined with subcarrier pairing and PA improves the system capacity to a considerable extent in both perfect and partial CSI cases.

Dynamic resource availability and lack of central control unit offer many challenges while designing medium access control (MAC) protocol for a distributed cognitive radio network (DCRN). In this paper, we propose a novel MAC design for DCRN which provides an efficient approach to address quality of service (QoS) requirements of delay sensitive applications by defining higher priority to such applications during channel reservation. It also combats other major challenges such as efficient spectrum utilization, multi-channel hidden terminal problem (MHTP) and collision with primary user (PU) due to sensing error at SU. We develop an analytical framework to study the performance of the proposed protocol. We then compare the performance of proposed protocol with those of two existing protocols. Comparison results show that proposed MAC outperforms the existing protocols by providing better throughput and reducing DCRN users' collision probability with PUs in presence of sensing error. The results achieved from the analytical model and validated by simulations show that our simple yet efficient design identifies and fulfils the QoS requirements of delay sensitive applications, achieves excellent spectrum utilization, shows superb robustness in presence of sensing errors and handles MHTP effectively.

We investigate cooperative sensing schemes for a cognitive radio (CR) network operating in multiple primary bands. The CR spectrum sensors use energy detection to identify the presence of the primary signals. We consider a parallel fusion architecture in which all the sensing devices send their binary quantized sensing information to an access point, which then applies a fusion rule to determine the presence of a primary user in each band. In this paper, we first propose schemes to assign sensors to various primary bands. We then study efficient quantization schemes when `OR' fusion rule is used in each band at the access point. We show that the optimal quantization scheme is, in general, non-convex and propose a suboptimal solution based on convex restriction of the original problem. We further study quantization schemes for general k-out-of-N fusion rule. We compare the performance of the proposed schemes using simulations.

This paper presents a blind parameter estimation algorithm for orthogonal frequency division multiplexing (OFDM) signal affected by a time-dispersive channel, timing offset, carrier frequency offset and additive Gaussian noise. Unlike the previous studies, this paper presents the second-order cyclostationarity of OFDM signal considering the effect of time-dispersive channel. The cyclostationarity properties of received OFDM signal in time-dispersive channel is exploited to estimate the OFDM parameters. These parameters includes OFDM symbol period, useful symbol period, cyclic prefix factor, number of subcarriers and carrier frequency offset. Simulations are performed to investigate the performance of OFDM parameter estimation algorithm in diverse channel conditions.

This paper presents a lower-bound on the ergodic sum capacity of single-input single-output (SISO) opportunistic spectrum sharing multiple access channel (MAC) in Rayleigh fading channels with imperfect channel estimates. Unlike the previous studies, this paper considerers the channel estimation errors for both sets of SISO channels between the secondary user (SU) transmitters and the SU receiver and between the SU transmitters and the primary user receivers. By considering these channel estimation errors, an optimal power allocation policy for each SU transmitter is derived to achieve a lower-bound of the ergodic sum capacity of opportunistic spectrum sharing MAC, subject to a set of SUs transmit power constraints and a set of interference power constraints at each PU receiver. Furthermore, convex optimization techniques are exploited to derive an efficient algorithm to obtain the optimal power allocation for each SU transmitter. Numerical results are presented to illustrate the influences of the channel estimation errors on the ergodic sum capacity.

In this paper, we propose a novel amplify-and- forward cooperative diversity scheme for wireless systems using the combination of bit-interleaved coded modulation (BICM) and orthogonal frequency division multiplexing (OFDM). In the proposed scheme, multiple relays transmit concurrently over disjoint sets of sub-carriers. A careful joint design of the sub- carrier allocation at the relays and the interleaver at the source ensures that the proposed scheme can exploit the maximum spatial and frequency diversity offered by the wireless channel. An upper bound on the asymptotic worst-case pairwise error probability of the proposed cooperative diversity scheme is developed which provides insight into to the influence of various code and channel parameters on performance. Simulation results corroborate the analytical results regarding the diversity gain of the system and confirm the effectiveness of a newly developed relay selection criterion.

This paper investigates a Decode-and-Forward (DF) two-hop relaying system in which Orthogonal Frequency Division Multiplexing (OFDM) is used. The relay forwards the message received from the source on a subset of available subchannels in the second time slot. Firstly, a pairing and selecting algorithm is proposed. Then, power will be allocated to the both base station and relay station under individual power constraints in order to maximize the capacity. The pairing and selecting algorithm and resource allocation is based on instantaneous channel state information (ICSI). Finally, the simulation results show that selective relaying combined with subcarrier pairing and power allocation will improve the system capacity to a considerable extent.

In this paper, we propose a novel multiuser cooperative communication scheme using random network coding for uplink wireless transmissions. The participating users transmit a linear combination of their new data packet and the packets successfully decoded due to preceding transmissions by other users, thus sending the new information as well as relaying the information for other users at the same time. The coefficients used for linear combination are selected at random from the finite field used to carry out the network coding. At the base station, original data packets are recovered from the received packets by solving the system of linear equations in the finite field. The proposed scheme is very robust against inter-user channel noise and can offer very high diversity gain in moderate inter-user channel conditions. Moreover, the transmission delay required by the proposed scheme is 2N as compared to N² in the traditional Time Division Multiple Access (TDMA) cooperative systems. The performance benefits of the proposed scheme are demonstrated through simulation analysis.

In this paper, we investigate joint sensing and power allocation schemes for OFDM-based cognitive radio (CR) systems. A CR system employing cooperative sensing based on energy detection is considered. Each primary user (PU) band is assigned a subset of sensors and equal gain combining is used at the access point to detect the presence of PU in that particular band. For such a system, we propose algorithms to jointly allocate sensing thresholds at the access point and power at the CR transmitters so that the throughput of the CR system is maximized while taking total transmit power, CR quality of service (QoS) constraints, and interference introduced to the PU band into consideration. The performance of the proposed schemes is compared to the schemes that only optimize either sensing thresholds or transmitted power. Presented numerical results demonstrate the strength of our proposed schemes.

Our contribution, in this paper, is two-fold. First, we analyze the performance of a hierarchical modulation-assisted two-best user opportunistic scheduling (TBS) scheme, which was proposed by the authors, in a fading environment where different users have different average link gains. Specifically, we present a new expression for the spectral efficiency (SE) of the users and using this expression, we compare the degrees of fairness (DOF) of the TBS scheme with that of classical single user opportunistic scheduling schemes, namely, absolute carrier-to-noise ratio (CNR) based single-best user scheduling (SBS) and normalized CNR based proportional fair scheduling (PFS) schemes. The second contribution is that we propose a new hybrid two-user opportunistic scheduling (HTS) scheme based on our earlier proposed TBS scheme. This HTS scheme selects the first user based on the largest absolute CNR value among all the users while the second user is selected based on the ratios of the absolute CNRs to the corresponding average CNRs of the remaining users. The total transmission rate i.e., the constellation size is selected according to the absolute CNR of the first best user. The total transmission rate is then allocated among these selected users by joint consideration of their absolute CNRs and allocated number of information bit(s) are transmitted to them using hierarchical modulations. Numerical results are presented for a fading environment where different users experience independent but non-identical (i.n.d.) channel fading. These selected numerical results show that the proposed HTS scheme can considerably increase the system?s fairness without any degradation of the link spectral efficiency (LSE) i.e., the multiuser diversity gain compared to the classical SBS scheme. These results also show that the proposed HTS scheme has a lower fairness in comparison to the PFS scheme which suffers from a considerable degradation in LSE.

In our earlier works, we proposed rate adaptive hierarchical modulation-assisted two-best user opportunistic scheduling (TBS) and hybrid two-user scheduling (HTS) schemes. The proposed schemes are innovative in the sense that they include a second user in the transmission opportunistically using hierarchical modulations. As such the frequency of information access of the users increases without any degradation of the system spectral efficiency (SSE) compared to the classical opportunistic scheduling scheme. In this paper, we analyze channel access delay of an incoming packet at the base station (BS) buffer when our proposed TBS and HTS schemes are employed at the BS. Specifically, using a queuing analytic model we derive channel access delay as well as buffer distribution of the packets that wait at BS buffer for down-link (DL) transmission. We compare performance of the TBS and HTS schemes with that of the classical single user opportunistic schemes namely, absolute carrier-to-noise ratio (CNR)-based single user scheduling (ASS) and normalized CNR-based single user scheduling (NSS). For an independent and identically distributed (i.i.d.) fading environment, our proposed scheme can improve packet's access delay performance compared to the ASS. Selected numerical results in an independent but non-identically distributed (i.n.d.) fading environment show that our proposed HTS achieves overall good channel access delay performance.

This paper deals with the clipping method used in orthogonal frequency-division multiplexing (OFDM) systems to reduce the peak-to-average power ratio (PAPR). An iterative soft compensation method is proposed to mitigate the clipping distortion, which can outperform conventional treatments. The impact of signaling schemes on the residual clipping noise power is studied via the symbol variance analysis. It is found that superposition coded modulation (SCM) can minimize the residual clipping noise power among all possible signaling schemes. This indicates that SCM-based OFDM systems are more robust to clipping effect than other alternatives when soft compensation is applied. It is also shown that a multi-code SCM scheme can further reduce the clipping effect and its overall performance can be quickly evaluated using a semi-analytical evolution method. Numerical examples are provided to verify the analysis.

It has been a pleasure and an honor to serve for the last three years as Editor-in-Chief of the IEEE Transactions on Wireless Communications. This Transactions is clearly the leading journal in its field and continues to publish very high-quality, peer-reviewed original papers that advance the state of the art and applications in wireless communications.

We study the end-to-end capacity of a cooperative relaying scheme using OFDM modulation, under power constraints for both the base station and the relay station. The relay uses an amplify-and-forward cooperative relaying technique to retransmit messages on a subset of the available subcarriers. The power used in the base station and the relay station transmitters is allocated in such a manner that the overall system capacity is maximized. The subcarrier selection and power allocation are obtained based on convex optimization formulations and an iterative algorithm. The proposed technique outperforms nonselective relaying schemes over a range of relay power budgets.

Reliable detection of primary users (PUs) is an important task for cognitive radio (CR) systems. Cooperation among a few spectrum sensors has been shown to offer significant gain in the performance of the CR spectrum-sensing system by countering the shadow-fading effects. We consider a parallel fusion network in which the sensors send their sensing information to an access point which makes the final decision regarding presence or absence of the PU signal. It has been shown in the literature that the presence of malicious users sending false sensing data can severely degrade the performance of such a cooperative sensing system. In this paper, we investigate schemes to identify the malicious users based on outlier detection techniques for a cooperative sensing system employing energy detection at the sensors. We take into consideration constraints imposed by the CR scenario such as the lack of information about the primary signal propagation environment and the small size of the sensing data samples. Considering partial information of the PU activity, we propose a novel method to identify the malicious users. We further propose malicious user detection schemes that take into consideration the spatial information of the CR sensors. The performance of the proposed schemes are studied using simulations.

We investigate the probabilistic convergence behavior of minimum mean square error (MMSE) turbo equalization in space-time (ST) block-coded multiple-input multiple-output (MIMO) systems with finite block lengths. For this purpose, the extrinsic information transfer characteristics (EXIT)-band chart technique, which was originally proposed for analyzing turbo decoding of parallel concatenated codes is applied. The impact on the convergence behavior and performance due to the use of ST block coding is analyzed through the EXIT-band characteristics. The convergence behaviors of the exact and approximate implementations of MMSE equalization are compared. We show that in the hybrid equalization schemes, the EXIT-band chart analysis can be used to determine the number of iterations that should be performed using the exact implementation. Our results clearly demonstrate the usefulness of the EXIT-band chart technique as a simple tool to analyze the convergence behavior of turbo equalization in systems with finite block lengths.

Cognitive radio (CR) is a recent innovation based on an intelligent radio design paradigm that can vastly improve utilization of valuable radio spectrum. However, successful deployment of CR technology in next generation wireless networks requires many new research challenges to be addressed, especially in the medium access control (MAC) layer. In this paper, we propose a novel MAC design, referred as Opportunistic Multichannel Cognitive MAC (OMC-MAC), for distributed CR networks to address some of these most important design issues. We also develop an analytical framework to study the performance of our proposed protocol in terms of important performance measures. The results achieved from the analytical model and validated by simulation, show that our simple yet efficient design achieves excellent spectrum utilization, shows superb robustness in presence of sensing error and handles multichannel hidden terminal problem very effectively.

We propose a power loading scheme for multi- carrier cognitive radio (CR) network employing multiple-input multiple-output (MIMO) antennas. We allocate power to different transmitting antennas within different subcarriers maximizing the total system capacity while maintaining the interference to primary user within a prescribed limit. We formulate this as a convex optimization problem and use numerical methods to solve for optimal power allocation. We also compare the performance of power loading scheme proposed in this paper to conventional uniform power loading scheme with and without interference constraint. Simulation results show that the capacity of MIMO CR using our proposed power loading scheme increases significantly with increase in interference temperature limit and the number of transmit antennas. However, we also confirm that if we include interference constraint in the conventional uniform power loading schemes, the capacity does not increase proportionally with increase in number of transmit antennas as those schemes do not take the instantaneous channel condition between cognitive user transmitter and primary user receiver into account.

Adaptive modulation and antenna diversity are two important enabling techniques for future wireless network to meet the demand for high data rate transmission. We study a Markov decision process based cross-layer design of optimal adaptation policy over selection-combining and maximal-ratiocombining Nakagami-m fading channel for Markov modulated Poisson process traffic. Unlike most of the channel-dependent adaptation policies in the literature, proposed policy chooses modulation constellation dynamically depending on incoming traffic state and buffer state in addition to channel state. Because the channel-dependent policy is physical layer optimized, it does not guarantee upper-layer delay and overflow requirements. Furthermore, the throughput predicted in physical layer analysis without considering buffer and traffic is over-optimistic than the actual system-level throughput. Proposed cross-layer dynamic adaptation policy minimizes transmission power and also guarantees target bit error rate, delay and packet overflow rate requirements for specific application being considered.

The contribution of this letter is the computation of exact symbol error probability (SEP) of three-dimensional (3- D) signal constellations over an additive white Gaussian noise (AWGN) channel. The originality of the proposed method is that it can be applied to any arbitrary 3-D constellation whose decision regions may not meet at right angles. We express the SEP in a triple integral form which is further simplified. The simplified form requires a single integral evaluation of standard "erf" function. Using the derived exact SEP formula, we plot SEP for a number of selected 3-D constellations. The SEP obtained using the proposed formula is validated by simulation results. It is also compared with the union bound approximation, an upper bound for SEP.

This paper presents two efficient flooding algorithms based on 1-hop neighbor information. In the first part of the paper, we consider sender-based flooding algorithms, specifically the algorithm proposed by Liu et al. In their paper, Liu et al. propose a sender-based flooding algorithm that can achieve local optimality by selecting the minimum number of forwarding nodes in the lowest computational time complexity O(n logn), where n is the number of neighbors. We show that this optimality only holds for a subclass of sender-based algorithms. We propose an efficient sender-based flooding algorithm based on 1-hop neighbor information that reduces the time complexity of computing forwarding nodes to O(n). In Liu's algorithm, n nodes are selected to forward the message in the worst case, whereas in our proposed algorithm, the number of forwarding nodes in the worst case is 11. In the second part of the paper we propose a simple and highly efficient receiver-based flooding algorithm. When nodes are uniformly distributed, we prove that the probability of two neighbor nodes broadcasting the same messageneighbor nodes broadcasting the same message exponentially decreases when the distance between them decreases or when the node density increases. The analytical results are confirmed using simulation.

Efficient and reliable subcarrier power allocation in orthogonal frequency-division multiplexing (OFDM)-based cognitive radio networks is a challenging problem. Traditional waterfilling approach is inefficient for such networks due to the strict requirements on the interference generated to the primary users (PUs). In this paper, we present a solution to an energy-efficient resource allocation problem which maximizes the cognitive radio (i.e., secondary) link capacity taking into account the availability of the subcarriers (and hence the reliability of transmission by cognitive radios) and the limits on total interference generated to the PUs. We consider an energy-aware capacity expression by taking into account another factor called subcarrier availability. Optimizing such an expression saves valuable resources such as battery life by selectively allocating power to underutilized subcarriers. Based on a risk-return model, we formulate a convex optimization problem which incorporates a linear average rate loss function in the optimization objective to include the effect of subcarrier availability. Due to the complex structure of the optimal solution, we propose three suboptimal schemes, namely, the step-ladder, nulling, and scaling schemes. We compare the performances of optimal and suboptimal algorithms with the performance of a classical waterfilling scheme. We conclude that waterfilling, unable to satisfy the interference criterion, performs the worst amongst all the schemes considered in this paper.

In this paper, we analyze the effect of the wormhole attack on shortest-path routing protocols for wireless ad hoc networks. Using analytical and simulation results, we show that a strategic placement of the wormhole when the nodes are uniformly distributed can disrupt/control on average 32% of all communications across the network. We also analyze a scenario in which several attackers make wormholes between each other and a case where two malicious nodes attack a target node in the network. We show how to evaluate the maximum effect of the wormhole attack on a given network topology. Then, we compute the maximum effect of the wormhole attack on grid topology networks and show that the attackers can disrupt/control around 40% to 50% of all communications when the wormhole is strategically placed in the network. Finally, to defend against the wormhole attack, we propose a timing-based countermeasure that avoids the deficiencies of existing timing-based solutions. Using the proposed countermeasure, the nodes do not need synchronized clocks, nor are they required to predict the sending time or to be capable of fast switching between the receive and send modes. Moreover, the nodes do not need one-to-one communication with all their neighbors and do not require to compute a signature while having to timestamp the message with its transmission time.

We develop a queuing analytic model to study cross-layer effects on Quality of Service (QoS) performance for downlink transmission in a Vertical Bell Laboratories Layered Space-Time Architecture (V-BLAST) Multiple Input Multiple Output (MIMO) wireless system exploiting multiuser diversity. As in multiuser Single Input Single Output (SISO) systems, multiuser diversity has been shown to have a great potential in improving system throughput in multiuser MIMO systems as well. In a V-BLAST MIMO system, the transmit antennas can carry parallel streams and multiple users can be scheduled for transmissions at the same time. We consider a multiuser diversity scheme that can effectively exploit this extra dimension in multiuser scheduling. To investigate the cross-layer aspect of the performance improvement, we perform a queuing analysis to derive buffer statistics, queuing delay distribution, packet throughput and loss rate experienced in the data link layer when this multiuser diversity technique is deployed in the system. We also present selected numerical results to show how the queuing model can help us to relate these important QoS measures to relevant physical layer and traffic parameters. Usefulness of the developed analytical model is also demonstrated through example applications.

We develop a queueing analytic framework to study the data link layer quality-of-service performance measures for cognitive radio users in an infrastructure-based dynamic spectrum access environment. In order to allocate the available spectrum white spaces among the cognitive radio users in a spectrum overlay scenario, an opportunistic scheduling scheme is considered. The queueing model considers bursty traffic arrival pattern at the cognitive radio user ends, finite buffer size, activity of primary users (i.e., dynamic channel availability), and correlated channel fading. We present a step-by-step procedure to derive the delay distribution, average throughput, and packet loss rate for the cognitive radio users. The proposed framework facilitates cross-layer design for improved QoS experience in cognitive radio networks. Usefulness of the developed analytical model is demonstrated through example applications.

In this paper, we introduce a spectrum holes detection approach, which combines blind modulation classification, angle of arrival estimation and number of sources detection. We perform eigenspace analysis to determine the number of sources, and estimate their angles of arrival. In addition, we classify detected sources as primary or secondary users with their distinct second-order/one-conjugate cyclostationarity features. Extensive simulations carried out indicate that the proposed system identifies and locates individual sources correctly, even at -4 dB SNR.

Efficient and reliable power allocation algorithm in cognitive radio (CR) networks is a challenging problem. Traditional water-filling algorithm is inefficient for CR networks due to the interaction with primary users. In this paper, we consider reliability/availability of subcarriers or primary user activity for power allocation. We model this aspect mathematically with a risk-return model by defining a general rate loss function. We then propose optimal and suboptimal algorithms to allocate power under a fixed power budget for such a system with linear rate loss. These algorithms as we will see allocate more power to more reliable subcarriers in a water-filling fashion with different water levels. We compare the performance of these algorithms for our model with respect to water-filling solutions. Simulations show that suboptimal schemes perform closer to optimal scheme although they could be implemented with same complexity as water-filling algorithm. Finally, we discuss the linearity of loss function and guidelines to choose its coefficients by obtaining upper bounds on them.

In this paper, we investigate cooperative sensing schemes to identify primary signals in fading environment for cognitive radio (CR) networks employing energy detectors. We consider a parallel fusion architecture in which all the sensing devices send their quantized sensing information to an access point, which then applies a fusion rule to determine the presence of the primary signal. We assume independent and identically distributed fading at various CR sensing devices. Considering identical binary quantization at the sensing devices, we study the optimal quantization and data fusion scheme. We compare the performance of the optimal binary data fusion scheme based on identical quantizers with the performances of other binary data fusion schemes commonly used in the literature for CR cooperative sensing networks. We further investigate the performance gain that could be obtained by using identical multi- bit quantization at the sensing devices.

Adaptive modulation and antenna diversity are two important enabling techniques for future wireless network to meet demand for high data rate transmission. We study a Markov decision process based cross-layer design of optimal adaptation policy over selection-combining Nakagami-m fading channel for Markov modulated Poisson process (MMPP) traffic. Unlike most of the channel-dependent adaptation policy in the literature, proposed policy chooses modulation constellation dynamically depending on the traffic and buffer states in addition to channel state. Proposed cross-layer dynamic adaptation policy minimizes transmission power, maximizes throughput, and also guarantees target bit error rate, delay and packet overflow rate requirements for the application being considered.

Our contribution, in this paper, is two-fold. First, we analyze performance of a hierarchical modulation-assisted two-best user opportunistic scheduling (TBS) scheme, which was proposed by the authors in [1], in a fading environment where different users have different average link gains. Specifically, we present expression for the spectral efficiency (SE) of the users and using this expression, we compare degrees of fairness (DOF) of the TBS with that of classical single user opportunistic scheduling schemes. Second contribution is that we propose a new hybrid two-user opportunistic scheduling (HTS) scheme based on the TBS scheme. This HTS selects the first user based on the largest absolute carrier-to-noise (CNR) value among all the users while the second user is selected according to the ratios of the absolute CNRs to the corresponding average CNRs of the remaining users. Numerical results are presented for a fading environment where different users experience independent but non-identical (i.n.d) channel fading. These selected numerical results show that the proposed HTS scheme can considerably increase the system's fairness without any degradation of the link SE compared to the classical single best user scheduling. These results also show that the proposed HTS has a lower fairness in comparison to the proportional fair scheduling (PFS) which suffers from a considerable degradation in link SE.

In our earlier works, we proposed rate adaptive modulation assisted two-user opportunistic scheduling schemes. The proposed schemes are innovative in the sense that they include second user in a transmission opportunistically using rate adaptive hierarchical modulations. As such the frequency of information access of the users increases without any degradation of the system link spectral efficiency (SE) compared to the classical opportunistic scheduling. In this paper, we analyze delay performance of our earlier proposed schemes. Specifically, using a queuing analytic model we derive queuing delay as well as buffer distributions of the packets that wait at the base station (BS) buffer for downlink (DL) transmission. Using this model, we compare performance of the two-user opportunistic scheduling schemes with that of the classical single user opportunistic schemes. These single user opportunistic scheduling schemes are the absolute carrier-to-noise ratio (CNR) based scheduling and normalized CNR based scheduling which is equivalent to the proportional fair scheduling (PFS). For an interdependent and identically distributed (i.i.d.) fading environment, our proposed scheme can improve delay performance significantly. Selected numerical results in an independent but non-identically distributed (i.n.d.) fading environment, our proposed scheme achieves overall good delay performance.

The most important task for a cognitive radio (CR) system is to identify the primary licensed users over a wide range of spectrum. Cooperation among spectrum sensing devices has been shown to offer various benefits including decrease in sensitivity requirements of the individual sensing devices. However, it has been shown in the literature that the performance of cooperative sensing schemes can be severely degraded due to presence of malicious users sending false sensing data. In this paper, we present techniques to identify such malicious users and mitigate their harmful effect on the performance of the cooperative sensing system.

The common belief is that localized broadcast algorithms are not able to guarantee both full delivery and a good bound on the number of transmissions. In this paper, we propose the first localized broadcast algorithm that guarantees full delivery and a constant approximation ratio to the minimum number of required transmissions in the worst case. The proposed broadcast algorithm is a self-pruning algorithm based on one round of information exchange. Using the proposed algorithm, each node determines its forwarding status in O(D logD), where D is the maximum node degree of the network. By extending the proposed algorithm, we show that localized broadcast algorithms can achieve both full delivery and a constant approximation ratio to the optimum solution with message complexity O(N), where N is the total number of nodes in the network and each message contains a constant number of bits. We also show how to save bandwidth by reducing the size of piggybacked information. Finally, we relax several system-model assumptions, or replace them with practical ones, in order to improve the practicality of the proposed broadcast algorithm.

Incremental-redundancy hybrid automatic repeat- request (IR-HARQ) schemes are proposed in several wireless standards for increased throughput-efficiency and greater reliability. We investigate transmit power and modulation order adaptation strategies for the IR-HARQ schemes over correlated Rayleigh fading channels using semi-Markov decision process-based model. In order to jointly analyze physical layer and link layer, transmitter model incorporates a finite-size buffer that receives randomly varying traffic from a higher layer application. It is assumed that channel variations can be modeled with a first-order Markov chain. We show that the optimal transmission power and rate adaptation laws under buffering delay and packet overflow constraints can be obtained using the framework of semi-Markov decision process. We discuss three different adaptation models for the IR-HARQ schemes and compare their performances with the non-adaptive scheme. It is shown that unique optimal policy exists for each case and it can be computed using linear programming approach. This optimal policy is then applied for realistic channel fading and incoming traffic samples to evaluate its performance for both hard-decision and soft-decision decoding. Simulation results in general point out that substantial power savings can be achieved using adaptation and also if the transmission-delay requirements are relaxed.

We consider the problem of finding the number of subsequences when deleting symbols from a string. We present a framework to find closed-form expressions for the number of subsequences, and use it to prove the first explicit formulas for and the first formulas for nonbinary alphabets. We also present the first efficient algorithm to compute the number of subsequences for any string, number of deletions, and alphabet size.

In this paper, we investigate an optimal power loading algorithm for an OFDM-based cognitive radio (CR) system. The downlink transmission capacity of the CR user is thereby maximized, while the interference introduced to the primary user (PU) remains within a tolerable range. We also propose two suboptimal loading algorithms that are less complex. We also study the effect of a subcarrier nulling mechanism on the performance of the different algorithms under consideration. The performance of the optimal and suboptimal schemes is compared with the performance of the classical power loading algorithms, e.g., water-filling and uniform power but variable rate loading schemes that are used for conventional OFDMbased systems. Presented numerical results show that for a given interference threshold, the proposed optimal scheme allows CR base station (BS) to transmit more power in order to achieve a higher transmission rate than the classical loading algorithms. These results also show that although the proposed suboptimal schemes have certain degradation in performance compared to the optimal scheme, they outperform the classical loading algorithms. We also present numerical results for nulling mechanism. Finally, we investigate the effect of imperfect channel gain information at the transmitter.

The 25 papers in this special issue focus on cooperative communications.

One of the major challenges in direct sequence-ultra wideband (DS-UWB) receiver design is intersymbol interference (ISI). Several equalization schemes to eliminate ISI in DS-UWB systems have been proposed in the literature. It was shown that frequency-domain (FD) equalization techniques can offer better trade off between performance and complexity compared to time- domain equalization schemes for DS-UWB systems on highly dispersive channels. In this paper, we derive low-complexity FD minimum mean square error turbo equalization schemes for single-user binary phase shift keying (BPSK) and quaternary bi-orthogonal keying (4BOK) DS-UWB systems. For multiuser DS-UWB systems, we combine FD turbo equalization schemes with soft interference cancelation to obtain multiuser FD turbo detectors. The bit error rate performance gain due to turbo detection is shown to be significant, particularly for multiuser DS-UWB systems.

The IEEE 802.11e standard developed by IEEE 802.11TGe intends to provide the quality of service (QoS) support in IEEE 802.11-based wireless local area networks (WLANs) through the introduction of hybrid coordination function (HCF). The HCF controlled channel access (HCCA) designed as a part of HCF is the medium access mechanism for parameterized QoS and is suitable for multimedia applications requiring hard QoS guarantees. The standard also defines a reference scheduler to complement HCCA in meeting these guarantees. In this paper, we investigate the performance of the reference scheduler described in the standard by using a novel queueing analytic framework. The analysis reveals the performance deficiencies of the reference scheduler. Afterwards, to overcome these deficiencies, we propose a new scheduling scheme, namely, the prediction and optimization-based HCCA (PRO-HCCA), based on the insights gained from the queueing analysis. Simulation experiments show that the proposed scheme overcomes the problems of the reference scheduler and successfully enables the HCCA to fulfill the QoS guarantees for multimedia applications.

Reducing the number of redundant transmissions is one of the main objectives of efficient broadcast algorithms for wireless ad hoc networks. There are many localized broadcast algorithms proposed to reduce the number of transmissions. However, they do not guarantee a reasonable bound on the number of transmissions in the worst case. In fact, the common belief is that localized broadcast algorithms are not able to guarantee both full delivery and a good bound on the number of transmissions. In this paper, we propose the first localized broadcast algorithm that guarantees full delivery and a constant approximation ratio to the minimum number of required transmissions in the worst case. The proposed broadcast algorithm is a self-pruning algorithm based on 1-hop neighbor information. Our experimental results confirm the analytical analysis of the algorithm and show a significant reduction in the number of transmissions and end-to-end latency compared to one of the best broadcast algorithms based on 1-hop neighbor information.

Cognitive radio (CR) technology is an innovative radio design philosophy in order to increase the spectrum utilization by exploiting the unused spectrum in dynamically changing environments. Specifically, the CR technology will allow a group of potential users (referred to as secondary users) to access available spectrum resources unused by primary users (PUs) for whom the band has been licensed. The spectrum available for secondary users (SUs) depends on PUs' activity in the licensed spectrum. In this paper, we develop a queuing analytic framework to study important performance measures experienced by SUs in a CR network. We study queuing delay and buffer statistics of SUs' packets by modeling PUs' activity as a two state Markov chain and SUs' channel quality variation as a finite state Markov chain (FSMC). In order to allocate available channels among the SUs, an opportunistic channel allocation scheme is considered. The proposed framework facilitates to design an admission controller for SUs' network in order to maintain a given quality service (QoS) requirement which is specified in the form of statistical delay guarantee.

Cognitive radio (CR) technology is an innovative radio design philosophy which aims to increase spectrum utilization by exploiting unused spectrum in dynamically changing environments. Orthogonal frequency division multiplexing (OFDM) is a potential modulation technique for CR networks' air interface. In this paper, we study and explore optimal power loading algorithm for an OFDM-based CR system and the rate in each subcarrier is adjusted according to the power. As such the downlink capacity of the CR user is maximized while the interference introduced to the primary user remains within a tolerable range. We also propose two suboptimal loading algorithms that have less complexity. The performance of optimal and suboptimal schemes are compared with the performance of classical power loading algorithms that are used for conventional OFDM-based systems e.g., water-filling and uniform power but variable rate loading schemes. Presented numerical results show that for a given interference threshold the proposed optimal scheme allows the CR users to transmit more power in order to achieve higher transmission rate than the classical loading algorithms. These results also show that the proposed suboptimal schemes offer a performance close to the optimal scheme. Finally, we study the effect of subcarrier nulling mechanism on the performance of different algorithms under consideration.

The paper presents a queueing analytical model for radio link level performance analysis in spatial multiplexing multiple-input multiple-output (MIMO) wireless systems using adaptive modulation. In the physical layer, the modulation level is adaptively adjusted according to the channel quality based on quadrature amplitude modulation (QAM). In the medium access control (MAC) layer, the authors consider a time division multiple access (TDMA) scheme with weighted round-robin scheduling. Developed based on a discrete-time Markov chain and vacation queueing model, the analytical model provides various packet-level performance measures. In addition, we present an optimization formulation to obtain users' weights for packet scheduling so that the transmission rate requirements of the users can be satisfied. Afterwards, an admission control scheme is proposed.

A queue-aware power allocation scheme for multiple-output multiple-input (MIMO) system using space time block coding (STBC) is presented. In the the physical layer, along with space-time block coded MIMO, the authors consider adaptive modulation to enhance transmission rate and error performance. To improve data reliability, automatic request (ARQ) is used for retransmission of erroneous packets from the radio link level queue. The proposed power allocation scheme is designed to minimize the cost which is defined as a function of transmit power and packet dropping probability at the radio link level queue. The genetic algorithm is used to obtain the solutions for the optimal parameters of the queue-aware power allocation scheme to minimize radio resource usage while meeting the quality-of-service (QoS) requirements for data traffic. A queueing analytical model is presented to investigate the link level performances (e.g., average queue length, packet dropping probability, throughput, and average delay) under different physical layer parameter setting.

The IEEE 802.11e standard developed by IEEE 802.11TGe intends to provide the quality of service (QoS) support for the popular 802.11 based wireless local area networks (WLAN) through the introduction of hybrid coordination function (HCF). The HCF controlled channel access (HCCA) designed as a part of HCF is the medium access mechanism for parameterized QoS and is suitable for multimedia applications requiring hard QoS guarantees. The standard also defines scheduling and admission control schemes to complement HCCA in meeting these guarantees. However, the reference scheduler has several limitations which render it incapable of providing QoS guarantees to many multimedia applications. In this paper, we propose a new scheduling scheme which overcomes these limitations to provide critical performance guarantees. Simulation experiments show that the proposed scheme successfully enables the HCCA to fulfill the QoS guarantees for wide variety of multimedia applications.

This paper presents two main results relating to elliptic curve cryptography. First, a double point compression scheme is proposed which allows a compact representation of elliptic curve points without the computational cost associated with ordinary single point compression. A triple point compression scheme is also proposed which can result in more savings in memory and/or bandwidth. Second, a new approach to speeding up random point multiplication is given for the case where the base point is variable but available in a certificate. In this approach, some redundant information (a few multiples of the base point) is added to the certificate. It is shown that a significant speed up can be obtained by optimizing the Moller's algorithm for the case where only a portion of the lookup table is available. It is also shown how to use redundant information to compute random point multiplication using parallel processors. The proposed point compression schemes can be employed to reduce the required bandwidth when single point compression is computationally expensive

In this letter, we study an application of hierarchical constellations (known also as embedded, multi-resolution, or asymmetrical constellations) for multi-user opportunistic scheduling. The key idea is to rely on hierarchical constellations to transmit information to two or more best users simultaneously in each transmission. The transmit power as well as the constellation parameter is changed according to the link qualities of the selected users in a way that a given target bit error rate (BER) is satisfied. The expressions for the average transmit power, and the outage probability with truncated channel inversion power control are presented. We also analyze and compare buffer distribution, average buffer occupancy, and packet loss probability of different; schemes via queuing analysis. We finally compare the hierarchical scheme for multi-user scheduling with a uniform constellation-based time-slotted scheme

We propose and study a two-best user opportunistic scheduling scheme using fixed power discrete rate adaptive hierarchical constellations (known also as embedded, multi- resolution, or asymmetrical constellations). According to the classical opportunistic scheduling, the scheduler transmits information to the selected first best user in each transmission slot in order to maximize the spectral efficiency. Our newly proposed scheme transmits information not only to the first best user but also to the second best user if the channel qualities of the selected two users support. As such the frequency of channel access of the users is increased without any degradation of overall spectral efficiency compared to the classical single best user scheduling. The key idea is to rely on hierarchical constellations to transmit information to two best users simultaneously. Specifically, according to the channel quality of the first best user, the alphabet size of the square quadrature amplitude modulation (QAM) is selected in order to maximize the spectral efficiency. However, if the first best user's channel quality is good enough to decode the information transmitted in the second hierarchy of the selected size hierarchical QAM constellation while the second best user's channel quality is capable of decoding the information transmitted in the first hierarchy, information is transmitted to both the selected first and second best users using the hierarchical QAM constellation. Otherwise, information is transmitted only to the first best user using the selected size uniform QAM constellation. We present expressions for the information transmission probability and the overall average spectral efficiency [bits/sec/Hz] defined as the overall average transmitted data rate per unit bandwidth for a specified number of users, a specified average carrier-to-noise ratio (CNR), and bit error rate (BER). Numerical results for a fading environment where the channel variation among the users is identically and independently distributed (i.i.d.) are presented. These results show that, in such i.i.d. fading environment, our newly proposed fixed power discrete rate adaptive hierarchical modulation- assisted two-best user scheduling provides more frequent access to the information (almost double) without any average spectral efficiency degradation compared to the classical single best user opportunistic scheduling.

We investigate the packet-level and the connection-level performances in a power-constrained (e.g., solar-powered) wireless mesh router with packet scheduling and admission control. The system model under consideration is compatible with the IEEE 802.16a standard with orthogonal frequency division multiple access (OFDMA) air interface. In the medium access control (MAC) layer, transmission frames are grouped into super-frames and the allocation of subchannel and number of frames to each connection (i.e., scheduling) is performed to satisfy the traffic requirement of each connection and also the power supply constraint at a mesh router/802.16a base station (BS). A queueing analytical model based on discrete-time Markov chain (DTMC) is used to analyze the packet-level performances. Based on this scheduling, router capacity in terms of the maximum number of ongoing connections is obtained. Subsequently, a threshold-based admission control method is proposed for both relay and local connections in a router so that connection-level performances are satisfied. To this end, we optimize the admission control over multiple time periods in which the amount of supplied power and the traffic load at a mesh router are time-dependent.

In their earlier work, the authors proposed a multiple best user opportunistic scheduling using power controlled hierarchical constellations and showed that the proposed scheme offers more frequent information access (almost double) to the users at the expense of certain increase in the average transmit power. As follow-up of our earlier work, in this paper, we analyze higher layer performances of the proposed two best user scheduling scheme via queuing analysis. More specifically, we analyze the buffer distribution, the average buffer occupancy, the delay distribution, and the packet loss probability of the hierarchical constellation-based multiple best user scheduling which has been proposed earlier by the authors. We then compare these higher layer performances of the hierarchical two best user scheduling with the classical single best user scheduling. Selected numerical results show that the hierarchical two best user scheduling scheme outperforms the classical single best user scheduling in terms of buffer distribution, average buffer occupancy (i.e., average buffering delay), delay distribution, and packet loss probability of the packets at the transmission buffer at the expenses of an increase in the average transmit power.

Non-linear frequency domain equalization schemes which give better performance than linear frequency domain equalization schemes, have recently been proposed in the literature for single carrier (SC) systems. In this paper, we study performance of non-linear frequency domain equalization schemes, viz. decision feedback equalization (DFE) and iterative DFE, for DS-UWB systems. We compare bit error rate (BER) performance of various time domain and frequency domain equalization techniques and evaluate their computational complexity. We show that the frequency domain equalization techniques can offer better trade off between complexity and performance compared to the time domain equalization techniques for DS-UWB systems.

We study coding and modulation rate adaptation problem for HARQ systems with partially observable state from cross-layer viewpoint. The rate of convolutionally coded M-QAM is adapted jointly with buffer state and channel state. We assume that perfect channel state information is not known at the transmitter, but it can be estimated from previous actions and observations. POMDP-based approach is utilized to formulate the problem, where average throughput is maximized, and average delay, packet error rate and overflows are minimized. To solve the cross-layer adaptation problem approximately, we discuss two heuristic-based methods and compare their applicability with completely observable channel state case by simulation results.

The wormhole attack is one of the most severe security attacks in wireless ad hoc networks. In this paper, we analyze the effect of the wormhole attack in shortest path routing protocols. Using analytical and simulation results, we show that a strategic placement of the wormhole can disrupt on average 32% of all communications across the network. We also analyze a more severe attack in which several attackers make wormholes between each other and give an upper bound on the average number of communications that can be disrupted. Finally, we propose a new robust and secure on-demand distance vector routing protocol which is able to route packets as long as there is a non-faulty path between the source and the destination.

Enhanced Data Rates for Global Evolution (EDGE) based systems are expected to facilitate the same services as third generation WCDMA systems. This goal is achieved through physical layer enhancements to increase the data rate and spectral efficiency. Thus, it has become important to incorporate the recent advances in the physical layer. Recently, space-time block coding (STBC) has evolved as an effective transmit diversity technique. Convolutional channel coding is employed in EDGE systems. The combination of channel coding and STBC can be used to achieve high throughput over hostile wireless channels. On the other hand, turbo equalization can be employed in channel coded broadband wireless systems to further enhance the radio link performance. EDGE-based systems employ 8PSK high- level modulation. Hence, maximum a posteriori (MAP)-based soft equalization is not suitable due to high complexity. Therefore, in this paper, we propose a low-complexity MMSE-based turbo equalization scheme for Alamouti space-time (ST) block coded multiple-input multiple-output (MIMO) systems. In the proposed iterative receiver, widely linear (WL) processing is used to exploit the rotational variance of the ST block coded transmit signal. Equalization and ST block decoding are jointly carried out at each iteration using the a priori information delivered by the convolutional channel decoder from the previous iteration. The simulation results demonstrate that high performance improvement can be obtained using the proposed iterative scheme in comparison to the non-iterative equalization. Due to the low-complexity, the proposed scheme is highly attractive for future EDGE-based systems with Alamouti STBC.

We study a cross-layer optimization problem of a rate-adaptive MQAM system that maximizes throughput, and minimizes packet error rate, delay and overflow using the framework of Markov decision process. We consider finite size buffer and random incoming traffic arrivals. The fading channel is assumed to be Nakagami-m and modeled with a finite state Markov channel, and transmit diversity is achieved with orthogonal space-time block code. To schedule packets, the transmitter depends on both buffer state and channel state information, and selective-repeat ARQ is used at the data link layer for error detection. Simulation results show that the throughput maximization depends not only on the received SNR but also on the number of actions and incoming traffic statistics.

We investigate transmit power adaptation strategy for IR-HARQ scheme over correlated fading channels. In order to jointly analyze physical and link layers, the transmitter model incorporates a finite-size buffer that receives randomly varying traffic from a higher layer application. It is assumed that channel variations can be modeled with first order Markov chain. We show that the optimal power adaptation law under buffer delay and packet overflow constraints can be obtained using the framework of semi-Markov decision processes. The optimal policy is computed using the linear programming approach. Simulation results show that substantial power savings can be achieved if the transmission delay requirements are relaxed.

The IEEE 802.11e draft standard currently being developed by IEEE 802.11TGe proposes to enable the much needed Quality of Service (QoS) support for the popular 802.11 based wireless local area networks (WLAN) through the introduction of Hybrid Coordination Function (HCF). The HCF Controlled Channel Access (HCCA) designed as a part of HCF is the medium access mechanism for parameterized QoS and is suitable for multimedia applications requiring hard QoS guarantees. The draft standard also defines scheduling and admission control schemes to complement HCCA in meeting these guarantees. However, most of the popular multimedia applications generate Variable Bit Rate (VBR) traffic that brings challenge to the HCCA and its scheduler and admission controller design. This paper introduces a novel queueing analytic framework that will be useful to analyze the performance of HCCA in provisioning required QoS for VBR traffic applications. The analysis also provides important insights that could be useful to improve the HCCA scheduler and admission controller designs.

Recently, space-time block coding (STBC) has received a remarkable interest as an effective transmit diversity technique to combat channel fading, but STBC provides little or no coding gain. However, as channel coding is usually employed in wireless systems, the combination of channel coding and STBC can be used to achieve high throughput gains over wireless channels. On the other hand, turbo (iterative) equalization can be employed in channel coded broadband wireless systems to further enhance the performance. Hence, in this paper, we propose a minimum mean square error (MMSE)-based turbo equalization scheme for Alamouti space-time (ST) block coded multiple-input multiple-output (MIMO) systems. In the proposed iterative receiver, widely linear (WL) processing is used to exploit the rotational variance of the ST block coded transmit signal. Equalization and ST block decoding are jointly carried out at each iteration using the a priori information delivered by the convolutional channel decoder from the previous iteration. The extrinsic information generated by the combined soft equalization-ST block decoding stage is passed to the channel decoder as the a priori information. The simulation results demonstrate that high performance improvement can be obtained using the proposed iterative scheme in comparison with thenon-iterative equalization. Due to the low-complexity, the proposed iterative scheme may be highly attractive to be implemented in future Alamouti ST block coded wireless systems.

In this paper, we introduce a new multi-mode Beyond 3rdGeneration (B3G) access system concept based on heterogeneous physical layer modes or configurations, with a common (or anchor) layer 2 and 3 protocols stack. Such a system can support a wide variety of physical layer access techniques, e.g. Code Division Multiple Access (CDMA), Orthogonal Frequency Division Multiple Access (OFDMA), Multi-Carrier CDMA (MC-CDMA) etc, with different configurations which are optimized for different deployment scenarios and performance targets, while anchored by a common layer 2 and 3 protocols. Seamless inter-system handoff is enabled by the common layer 2/3 protocols, while dynamic radio resource/load/spectrum management can be performed across the different physical layer modes to achieve optimum spectrum efficiency and Quality of Service (QoS) support. The overall system concept of the multimode access system is first presented, followed by a detailed account of the anchor layer 2/3 protocol design.

We study in this paper an integrated packet scheduling and unequal error protection strategy for the transmission of packetized multi-resolution (layered) image/video data over time varying wireless channels. Different transmission priorities are given to different layers of video/image data not only by using hierarchical constellation (known also as nonuniform, asymmetric, multi-resolution constellation) at the physical layer but also by a buffer adaptive packet scheduling protocol at the medium access control (MAC) layer. Basically, according to the current buffer occupancy and channel state, the scheme dynamically selects packets from different resolution levels to transmit for the current transmission. The bits from the selected packets are assigned to different hierarchies of a hierarchical 4/16-quadrature amplitude modulation (QAM). In our proposed transmission framework, the transmit power level and the constellation priority parameter are also selected dynamically according to the quality of the wireless channel and scheduling state. In order to minimize the distortion in the received image/video with a given power budget, a joint optimization of the packet scheduling protocol, the transmit power level, and the constellation priority parameter is proposed. The power-distortion trade-offs curve is plotted for a given fading rate. We also compare the proposed scheme with a scheme employing uniform signal constellation. The comparison shows that in order to achieve a given quality of the received image/video, the scheme employing hierarchical QAM constellation always requires less power than the scheme employing uniform constellation.

This letter addresses training-signal-based combined timing and frequency synchronization and channel estimation for orthogonal frequency-division multiplexing systems. The proposed scheme consists of two stages. At the first stage, coarse timing and frequency-offset estimates are obtained. Based on these estimates, a (coarse) channel response estimate is obtained. The timing and frequency-offset estimates at the second stage are obtained by maximum-likelihood (ML) realization based on a sliding observation vector. Then ML channel estimation is performed. A means of complexity reduction by an adaptive scheme is also presented. The simulation results show that the proposed combined approach performs quite well, and circumvents the problem of mismatch among individual synchronization tasks.

This paper addresses an optimal periodic training signal design for frequency offset estimation in frequency-selective multipath Rayleigh fading channels. For a fixed transmitted training signal energy within a fixed-length block, the optimal periodic training signal structure (the optimal locations of identical training subblocks) and the optimal training subblock signal are presented. The optimality is based on the minimum Cramer-Rao bound (CRB) criterion. Based on the CRB for joint estimation of frequency offset and channel, the optimal periodic training structure (optimality only in frequency offset estimation, not necessarily in joint frequency offset and channel estimation) is derived. The optimal training subblock signal is obtained by using the average CRB (averaged over the channel fading) and the received training signal statistics. A robust training structure design is also presented in order to reduce the occurrence of outliers at low signal-to-noise ratio values. The proposed training structures and subblock signals achieve substantial performance improvement.

We propose a new technique for multi-resolution video/image data transmission over block fading channels. The proposed scheme uses an adaptive scheduling protocol employing a retransmission strategy in conjunction with a hierarchical signal constellation (known also as nonuniform, asymmetric, multi-resolution constellation) to give different transmission priorities to different resolution levels. Transmission priorities are given in terms of average packet loss rate as well as average throughput. Basically, according to the transmission scheduling and channel state (acknowledgment signal) of the previous transmission, it dynamically selects packets from different resolution levels to transmit for the current transmission. The bits from the selected packets are assigned to different hierarchies of a hierarchical 4/16-quadrature amplitude modulation to transmit them with different error protections. The selection of packets for transmission and the assignment of these selected packets to different hierarchies of the hierarchical constellation are referred to as the scheduling protocol in our proposed scheme. We model this protocol by a finite state first order Markov chain and obtain the packet loss rate and the packet transmission rate over Nakagami-m block fading channel in closed-form. Some selected numerical results show that the proposed scheme can control the relative packet loss rate and the packet transmission rate of different resolution levels by varying the priority parameter (or equivalently, the asymmetry) of the hierarchical constellation and the maximum number of allowed retransmissions.

We address the issue of optimal packet scheduling over correlated fading channels which trades off between minimization of three goals: average transmission power, average delay and average packet dropping probability. We show that the problem forms a weakly communicating Markov decision process and formulate the problem as both unconstrained and constrained problem. Relative value iteration (RVI) algorithm is used to find optimal deterministic policy for unconstrained problem, while optimal randomized policy for constrained problem is obtained using linear programming (LP) technique. Whereas with RVI only a finite number of scheduling policies can be obtained over the feasible delay region, LP can produce policies for all feasible delays with a fixed dropping probability and is computationally faster than the RVI. We show the structure of optimal deterministic policy in terms of the channel and buffer state and form a simple log functional suboptimal scheduler that approximately follows the optimal structure. Performance results are given for both constant and bursty Poisson arrivals, and the proposed suboptimal scheduler is compared with the optimal and channel threshold scheduler. Our suboptimal scheduler performs close to the optimal scheduler for every feasible delay and is robust to different channel parameters, number of actions and incoming traffic distributions.

We address the issue of optimal coding rate scheduling for adaptive type-I hybrid automatic repeat request wireless systems. In this scheme, the coding rate is varied depending on channel, buffer and incoming traffic conditions. In general, we consider the hidden Markov model for both time-varying flat fading channel and bursty correlated incoming traffic. It is shown that the appropriate framework for computing the optimal coding rate allocation policies is partially observable Markov decision process (POMDP). In this framework, the optimal coding rate allocation policy maximizes the reward function, which is a weighted sum of throughput and buffer occupancy with appropriate sign. Since polynomial amount of space is needed to calculate the optimal policy even for a simple POMDP problem, we investigate maximum-likelihood, voting and Q-MDP policy heuristic approaches for the purpose of efficient and real-time solution. Our results show that three heuristics perform close to completely observable system state case if the fading and/or traffic state mixing rate is slow. On the other hand, when the channel fading is fast, Q-MDP heuristic is the most throughput-efficient among considered heuristics. Also, its performance is close to the optimal coding rate allocation policy of fully observable system state case. We also explore the performances of the proposed heuristics in the bursty correlated traffic case and show that maximum-likelihood and voting heuristics consistently outperform the non-adaptive case

We propose and study a two best user opportunistic scheduling algorithm using discrete rate adaptive hierarchical constellations (known also as embedded, multi-resolution, or asymmetrical constellations). The key idea is to rely on hierarchical constellations to transmit information to the two best users opportunistically. The newly proposed scheme transmits information to single or two best users jointly considering the channel qualities of these users. We present expressions for the information transmission probability and the overall average spectral efficiency [Bits/Sec/Hz] defined as the overall average transmitted data rate per unit bandwidth for a specified number of users, average carrier-to-noise ratio (CNR), and bit error rate (BER). Numerical results for an identical and independent (i.i.d.) fading environment, where the channel variation among the users is i.i.d., are presented. The results show that in such i.i.d. fading environment, our newly proposed discrete rate adaptive hierarchical modulation assisted two best user scheduling provides more frequent access to the information (almost double) without any average spectral efficiency degradation compared to the classical single best user opportunistic scheduling.

This paper explores optimal and suboptimal power and bit loading algorithms for a multicarrier system. Specifically, we study the trade-offs between the total transmit power of an orthogonal frequency division multiplexing (OFDM) system and the buffering delay of the packets in a transmission buffer. The loading framework is formulated as a Markov decision process (MDP) and an optimal loading policy which minimizes the transmit power while meeting a target delay constraint is obtained via equivalent linear programming (LP) methodology. The complexity of finding the optimal loading policy and its' implementation issues are described. Since finding the optimal policies becomes complex and practically un-realizable for large number of carriers in the system, we offer a sub-optimal power and bit loading algorithm using the results of the single carrier system's power and rate adaptation policy and a greedy approach. Selected numerical examples show that the sub-optimal algorithm, which has reduced complexity, has performance close to the optimal one.

We study two cross-layer optimization problems for M-QAM systems that adapt transmission rate with channel state and buffer occupancy. We formulate both problems as constrained Markov decision process problem and give linear programming technique based solutions. In first problem, our objective is to minimize average transmission power under constraint on average delay and packet dropping probability. We minimize average bit error rate (BER) with average delay and packet dropping probability constraints in second problem. The Nakagami-m fading channel with diversity-combining is described as finite state Markov channel. Simulation results show that the system performances can be improved by adapting rate with buffer state and hence delaying packet in the buffer in addition to employing diversity-combining at the receiver.

Space-time (ST) block coding based transmit diversity is included in the 3G mobile telecommunication specification for CDMA downlink transmission. On the other hand, turbo (iterative) equalization can be used in channel coded broadband wireless systems to enhance the performance. Hence, in this paper, we develop a linear MMSE-based turbo equalization scheme for downlink ST block coded CDMA to achieve high capacity gains over multipath fading channels. The proposed unified CDMA system model considers both conventional and block spreading. However, block spreading is more desirable as confirmed by the simulation results. Both ST encoding and ST decoding are performed at the chip-block level. Turbo equalization is performed after ST decoding. Furthermore, we also consider computationally-efficient implementations of the proposed turbo equalization scheme. Simulation results demonstrate that high performance can be achieved using the proposed iterative equalizer

We present a cross-layer optimization problem where the coding rate of hybrid ARQ systems is adapted with channel, buffer, and input traffic state to minimize packet errors as well as buffer delay. Representing both the incoming traffic and the time-varying wireless channel as a finite state Markov chain, it is shown that the problem forms a partially observable Markov decision process (POMDP) problem. Since finding optimal policy is PSPACE complete, we investigate two policy-heuristic approaches for the purpose of efficient and real time solving of our formulated POMDP problem. Numerical results reveal that the performances of these two heuristic are almost same as the case when channel states are fully observable.

An opportunistic power control algorithm was proposed in (C. W. Sund and K. K Leung, June 2004). While it provides significant throughput improvement, fairness has been a major challenge. In this paper, we propose an opportunistic power control algorithm with fairness consideration. Alongside the throughput enhancement of the power control algorithm, we prove the uniqueness, convergence and continuity properties of its fixed point

This paper considers the phase control problem in multiple-input single-output antenna system (MISO) with finite number of control bits. We propose an optimal algorithm which requires only O(nTlog nT) of computations, where nTis the number of transmit (input) antennas

This paper introduces a novel differential modulation scheme for a two-user cooperative diversity system which does not require channel state information at either the users or the destination. The performance of fixed decode-and-forward and selection relaying protocols is evaluated in both symmetric and asymmetric interuser-channel cases. The lower bound on the performance of the decode-and-forward protocol is given, while the exact bit-error probability of the selection relaying protocol is thoroughly derived. The decode-and-forward relaying protocol achieves a performance gain when the signal-to-noise ratios in the interuser channels are symmetric and sufficiently high. The selection relaying protocol shows a larger performance gain and does not exhibit an error floor like in the case of the decode-and-forward protocol. In addition, it is robust to the asymmetric interuser channels.

This paper introduces a new radix-2 representation with the same average weight as the width-w nonadjacent form (w-NAF). In both w-NAF and the proposed representations, each nonzero digit is an odd integer with absolute value less than M. However, for w-NAF, M is of the form 2/sup w-1/, while, for the proposed representation, it can be any positive integer. Therefore, using the proposed integer representation, we can use the available memory efficiently, which is attractive for devices with limited memory. Another advantage of the proposed representation over-w-NAF is that it can be obtained by scanning the bits from left-to-right. This property is also useful for memory-constrained devices because it can reduce both the time and space complexity of fast point multiplication techniques.

Signal fading is a ubiquitous problem in mobile and wireless communications. In digital systems, fading results in bit errors, and evaluating the average error rate under fairly general fading models and multichannel reception is often required. Predominantly to date, most researchers perform the averaging using the probability density function method or the moment generating function (MGF) method. This paper presents a third method, called the characteristic function (CHF) method, for calculating the average error rates and outage performance of a broad class of coherent, differentially coherent, and noncoherent communication systems, with or without diversity reception, in a myriad of fading environments. Unlike the MGF technique, the proposed CHF method (based on Parseval's theorem) enables us to unify the average error-rate analysis of different modulation formats and all commonly used predetection diversity techniques (i.e., maximal-ratio combining, equal-gain combining, selection diversity, and switched diversity) within a single common framework. The CHF method also lends itself to the averaging of the conditional error probability involving the complementary incomplete Gamma function and the confluent hypergeometric function over fading amplitudes, which heretofore resisted to a simple form. As an aside, we show some previous results as special cases of our unified framework.

This paper addresses the problem of dynamic rate and power adaptation for forward link data transmission using high-order modulation and multicode formats in cellular wideband code division multiple access (WCDMA) networks. A novel framework for dynamic joint adaptation of modulation order, number of code channels (hence transmission rate), and transmission power is proposed for downlink data transmission in a cellular WCDMA system where different users have similar frame error rate (FER) requirements. Based on a general downlink signal-to-interference ratio (SIR) model, the problem of optimal dynamic rate and power adaptation is formulated, for which the rate and power allocation can be found by an exhaustive search. Two heuristic-based dynamic rate and power allocation schemes are proposed. Performance of dynamic joint rate and power adaptation under the proposed framework is evaluated for a random micromobility model using computer simulations. Also, an analytical approach to evaluate the throughput performance of dynamic rate and power adaptation using high-order modulation and multicode formats is presented.

Semiblind multiuser detection for the reverse link of a multicell code-division multiple-access (CDMA) system is considered. In such a system, although active users are present in the home cell and neighboring cells, the base station receiver only knows the signature information of the users in its own cell. Three new semiblind linear multiuser detectors are proposed based on parallel interference cancellation approach. Compared with some known semiblind detectors, the proposed detectors share a rather simple implementation structure and involve reduced latency for processing, which are of particular importance in a time-varying CDMA system. Numerical results are presented to compare the detection performance of the proposed detectors with that of some existing semiblind multiuser detectors.

The problem of adopting space-time block coding (STBC) in the uplink of direct sequence code division multiple access (DS-CDMA) systems is addressed. A novel system architecture is proposed for space-time (ST)-coded uplink transmissions over multipath fading channels with multiple user interference (MUI)-free reception. This proposed system is a combination of single-carrier time-reversal zero-padding (SC-TR-ZP)-based STBC with chip-interleaved block-spread (CIBS)-CDMA. Simulation results show that a substantial performance improvement can be achieved by adopting ST coding compared to the original CIBS-CDMA scheme without ST coding. Optimal maximum likelihood sequence estimation (MLSE) may be computationally prohibitive for long channels and/or with high-level modulation. Hence, the performance of different decision feedback sequence estimation (DFSE) schemes is investigated for the proposed ST-coded uplink system. In the case of whitened DFSE (WDFSE), a linear prediction (LP)-based approach is adapted for designing a whitening prefilter. Furthermore, a new scheme, which is a combination of linear equalization (LE) and modified unwhitened DFSE (MUDFSE) is proposed. The proposed combined LE-MUDFSE (Comb. LE-MUDFSE) scheme is very attractive as error-floor behavior appearing in other unwhitened DFSE schemes is eliminated. The simulation results indicate that a substantial performance improvement over the minimum mean-square error (MMSE) equalizer can be achieved by using either Comb. LE-MUDFSE scheme or WDFSE scheme.

This letter models and analyzes an adaptive radio link level error control protocol using Reed–Solomon codes for wireless networks. Results show that the proposed dynamic rate adaptive strategy provides a much improved throughput relative to a conventional type-I and type-II hybrid-automatic repeat request (ARQ) protocols.

We present a general Markov decision process based framework for the identification of optimal delay-constrained rate adaptation for MQAM systems and power adaptation for type-I hybrid ARQ systems. This framework can be applied to adaptive resource allocation over correlated fading channels. It is shown that the optimal rate and power control can be obtained by solving the appropriately formulated Markov decision processes using linear programming techniques. In the case of adaptive MQAM systems, the optimal rate allocation policy is dependent on the current buffer occupancy and the channel state. For hybrid ARQ systems the power control law can be formulated as being dependent on the current buffer occupancy and the history record of channel and action observations. The results of this paper are of importance for the development of modern wireless standards that support delay sensitive multimedia traffic.

Semi-blind multiuser detection for the reverse link of a multi-cell code-division multiple-access (CDMA) system is considered. In such a system, although active users are present in the home cell and neighbouring cells, the base station receiver only knows the signal information of the users in its own cell. Three new adaptive semi-blind linear multiuser detectors are proposed, based on a parallel interference cancellation approach. Compared with some known semi-blind detectors, the proposed detectors share a rather simple implementation structure and involve reduced latency for processing, which are of particular importance in a time-varying CDMA system. Numerical results are presented to show that the detection performance of the proposed detectors is superior to that of some existing semi-blind multiuser detectors.

Cooperative transmission is an alternative approach to achieve diversity in wireless systems. So far the research has focused on the situation where perfect channel state information is available and coherent detection is employed at at the destination receiver. This paper proposes a differential modulation scheme for a two-user cooperative diversity system which does not require channel state information at either users or destination. The relaying protocols such as fixed decode-and-forward, selection relaying, and incremental relaying protocols are compared. The proposed scheme achieves spatial diversity gains when the signal-to-noise ratios between cooperative users are sufficiently high.

In this paper, we address the problem of adopting space-time (ST) coding in the uplink of DS-CDMA systems. A novel system architecture, which is the combination of single-carrier time-reversal zero-padded (SC-TR-ZP) based ST block coding with chip-interleaved block-spread (CIBS)-CDMA, is proposed for frequency selective uplink transmissions. Simulation results show that a substantial performance improvement can be achieved by adopting ST coding compared to the original CIBC-CDMA scheme without ST-coding. Optimal maximum likelihood sequence estimation (MLSE) may be computationally prohibitive for long channels and/or with high-level modulation. Hence, the performance of different decision feedback sequence estimation (DFSE) schemes are investigated for the proposed ST block coded uplink system. In the case of whitening DFSE, a linear prediction (LP)-based approach is adapted for designing a whitening prefilter. The proposed combined linear equalization-modified unwhitened DFSE (Comb. LE-MUDFSE) scheme seems to be very attractive as error floor behavior appearing in other unwhitened DFSE schemes is eliminated. The simulation results indicate that a substantial performance improvement over the MMSE equalizer can be achieved either by using Comb. LE-MUDFSE or whitened DFSE (WDFSE) scheme.

This paper explores optimal and suboptimal packet schedulers for time-varying flat fading channels that trade-off between minimization of the average delay and the average transmitted power. Both uncorrelated and correlated block fading channels are investigated. Extending a previous work, we formulate the trade-off as a unconstrained Markov decision processes and find the stationary deterministic optimal policy using both relative value iteration and policy iteration algorithm. As well, we present constrained Markov decision processes formulation of the problem and linear programming algorithm to solve it and show that optimal schedulers are randomized in this case. In order to alleviate the computational complexity needed, to determine the optimal scheduling policy we propose a suboptimal log-scheduling policy that has performance close to that of the optimal scheduler. The proposed policy is also robust to different channel models. It is demonstrated that log-policy is favorable to the water-filling policy for very slow fading channels.

We propose a new technique for multi-resolution video/image data transmission over block fading channels. The proposed scheme uses an adaptive scheduling protocol employing a retransmission strategy in conjunction with a hierarchical signal constellation (known also as nonuniform, asymmetric, multi-resolution constellation) to give different transmission priorities to different resolution levels. Transmission priorities are given in terms of packet loss rate as well as average throughput i.e., transmission rate. Basically, according to the transmission scheduling and channel state (acknowledgment signal) of the previous transmission, it dynamically selects packets from different resolution levels to transmit for the current transmission. The bits from the selected packets are assigned to different hierarchies of a hierarchical 4/16- quadrature amplitude modulation to transmit them with different error protections. The selection of packets for transmission and the assignment of these selected packets to different hierarchies of the hierarchical constellation are referred to as the scheduling protocol in our proposed scheme. We model this protocol by a finite state first order Markov chain and obtain the packet loss rate and the packet transmission rate over Nakagami-m block fading channel in closed-form. Some selected numerical results show that the proposed scheme can control the relative packet loss rate and the packet transmission rate of different resolution levels by varying the priority parameter (or equivalently the asymmetry) of the hierarchical constellation and the maximum number of allowed retransmissions.

The idea of combined timing and frequency synchronization and channel estimation is quite desirable since the synchronization and channel estimation tasks can affect each other. This paper addresses training signal based combined timing and frequency synchronization and channel estimation for OFDM systems. The proposed scheme consists of two stages. At the first stage, coarse timing and frequency offset estimates are obtained. Based on these estimates, a (coarse) channel response estimate is obtained. The timing and frequency offset estimates at the second stage are obtained by a maximum likelihood (ML) realization based on sliding observation vector. Then a ML channel estimation is performed. The simulation results show that the proposed combined approach performs quite well and circumvents the problem of mismatch among individual synchronization tasks.

This paper presents a training signal based improved timing offset estimation method in frequency selective fading channels. A coarse timing offset estimate is first obtained by maximizing a normalized correlation metric. A coarse frequency offset estimate is similarly obtained by a correlation metric. Then a sliding observation vector based maximum likelihood approach (SOV-ML) for joint timing and frequency offset estimation is applied. This SOV-ML requires the knowledge of channel impulse response (CIR). The CIR estimate is usually affected by the coarse timing and frequency offset estimates. The key requirement for SOV-ML is to obtain a CIR estimate which is not affected (or minimally affected) by the coarse timing and frequency offsets. This paper addresses how to obtain this CIR estimate and presents how this channel estimation assists in improving the timing offset estimation. A way of complexity reduction by an adaptive scheme is also presented.

This paper addresses optimal periodic training signal design for frequency offset estimation in frequency selective multipath Rayleigh fading channels. For a fixed transmitted training signal energy and within a fixed length block, the optimal periodic training signal structure (the optimal location of identical training subblocks) and the optimal training subblock signal are presented. The optimality is based on the minimum Cramer-Rao bound (CRB) criterion. Based on the snap-shot CRB, the optimal periodic training structure is derived. The optimal training subblock signal is obtained by utilizing the average CRB and the received training signal statistics. The optimal training structure with optimal training signals achieves substantial performance improvement over nonoptimal training structure with nonoptimal training signals.

This work presents a feasibility study for a possible extension to the IS-856 (HDR, 1xEV-DO) standard in terms of allowing two user transmission in the system downlink. Since the 1.25 MHz bandwidth of this system is not perfectly frequency flat, the one user at a time scheme is no longer optimal in theory. Furthermore, the two user transmission allows for more granular data rate selection by the base station. The extension requires minimum changes to the physical layer of the IS-856 standard and is compatible with the existing physical layer specifications with no additional overhead required in the downlink. A packet scheduling algorithm that is able to take advantage of the two user transmission is presented. The performance of the proposal is studied with physical layer and system simulations. The simulation results indicate that the proposed extension modestly increases the average system data rate that may not justify the required complexity.

Dynamic radio link adaptation is a key component in WCDMA/3G wireless networks to improve the spectral efficiency while meeting the radio link level QoS (quality of service) requirements, such as the BER (bit error rate) requirements, for the different wireless services. Again, performance of an end-to-end protocol, such as TCP (Transmission Control Protocol), depends on the performance of the underlying radio link adaptation technique. A multilayer modeling of the WCDMA/3G radio interface is therefore necessary to understand better the interlayer protocol interactions and identify suitable transport and radio link layer mechanisms to improve TCP performance in a wide-area cellular WCDMA/3G network. We present such a multilayer system model to analyze TCP performance under joint rate and power adaptation with constrained BER requirements for downlink data transmission in a cellular VSF (variable spreading factor) WCDMA/3G network. To this end, we present the outline of a more general model which can completely describe the interaction between TCP and the radio link adaptation and error control protocol.

This letter considers a multiple-access fading channel with opportunistic transmission of the users, i.e., only the user with the highest received power is allowed to transmit at a certain time slot. The transmit power randomization, independent of the channel estimates, is used in order to increase the fading rate, decrease the latency, and shape the distribution of the received powers. We derive the optimal distribution of the received powers that maximizes the throughput of the system, and measure possible gains compared with the long-term average throughput of the opportunistic transmission in a Rayleigh fading channel. The issue of unequal fading distributions of different users is also addressed.

For original paper see A. A. Alsugair and R. S. Cheng, ibid., vol. 41, p. 1072-1082 (July, 1995). We show that the signature sequences set that maximizes the lower bound on symmetric capacity derived in the above paper also maximizes the sum capacity of the Gaussian synchronous code-division multiple-access (CDMA) channel. This is done by relying on the equivalence of the eigenvalues of energy-weighted correlation matrices. This result establishes the missing link between the above paper and the sum capacity maximization result by Viswanath et al. (1999).

A set of centralized burst-level cell scheduling schemes, namely, First Come First Served with Frame Reservation (FCFS-FR), FCFR-FR+, Earliest Deadline First with Frame Reservation (EDF-FR), EDF-FR+, and Multitraffic Dynamic Reservation (MTDR), are investigated for transmission of multiservice traffic over time division multiple access (TDMA)/time division duplex (TDD) channels in wireless ATM (WATM) networks. In these schemes, the number of time slots allocated to a virtual circuit (VC) during a frame-time is changed dynamically depending on the traffic type, system traffic load, the time of arrival (TOA)/time of expiry (TOE) value of the data burst and data burst length. The performances of these schemes are evaluated by computer simulation for realistic voice, video and data traffic models and their quality-of-service (QoS) requirements in a wireless mobile multimedia network. Both the error-free and the correlated fading channel conditions are considered. Simulation results show that the EDF-FR+ and MTDR schemes outperform the other schemes and can provide high channel utilization with predictive QoS guarantee in a multiservice traffic environment even in the presence of bursty channel errors. The EDF-FR+ scheme is found to provide better cell multiplexing performance than the MTDR scheme, Such a scheme would be easy to implement and would also result in a power conservative TDMA/TDD medium access control (MAC) protocol for broadband wireless access. Burst-level cell scheduling schemes such as EDF-FR+ can be easily adapted as MAC protocols in the emerging differentiated services (DS) enhanced wireless Internet protocol (IP) networks.

The usage of multichannel receivers that are followed by diversity combining can significantly improve the performance of wireless communications links. In this paper, we investigate in some detail three popular techniques for diversity combining, namely maximal ratio combining (MRC), equal gain combining, and selection combining. The main goal is to investigate under which circumstances it can be guaranteed that a certain technique does indeed decrease the probability of error of a multichannel receiver. The analyzed fading model is quite general with the only assumption that fading gains are scaled exchangeable random variables. The crucial mathematical tool used to produce the results of this paper is the powerful theory of stochastic majorization. Among other results, it was shown that the average bit-error probability of the MRC receiver with equally distributed average powers always decreases with the addition of a new diversity branch if the total power is fixed.

To improve the spectral efficiency while meeting the radio link level quality of service requirements such as the bit-error-rate (BER) requirements for the different wireless services, transmission rate and power corresponding to the different mobile users can be dynamically varied in a cellular wideband code-division multiple-access (WCDMA) network depending on the variations in channel interference and fading conditions. This paper models and analyzes the performance of transmission control protocol (TCP) under joint rate and power adaptation with constrained BER requirements for downlink data transmission in a cellular variable spreading factor (VSF) WCDMA network. The aim of this multilayer modeling of the WCDMA radio interface is to better understand the interlayer protocol interactions and identify suitable transport and radio link layer mechanisms to improve TCP performance in a wide-area cellular WCDMA network.

Optimal dynamic rate allocation among mobile stations for variable rate packet data transmission in a cellular wireless network is an NP-complete problem; therefore, suboptimal solutions to this problem are sought for. In this paper, three novel suboptimal dynamic rate adaptation schemes, namely, peak-interference-based rate allocation, sum-interference-based rate allocation, and mean-sense approximation-based rate allocation, are proposed for uplink packet data transmission in cellular variable spreading factor wide-band code division multiple access (WCDMA) networks. The performances of these schemes are compared to the performance of the optimal dynamic link adaptation for which the rate allocation is found by an exhaustive search. The optimality criterion is the maximization of the average number of radio link level frames transmitted per frame time under constrained signal-to-interference-plus-noise ratio (SINR) at the base station receiver. Two different error control alternatives for variable rate packet transmission environment are presented. We demonstrate that the dynamic rate adaptation problem under constrained SINR can be mapped into the radio link level throughput maximization problem with integrated rate and error control. Performance evaluation is carried out under random and directional micromobility models with uncorrelated and correlated long-term fading, respectively, in a cellular WCDMA environment for both the homogeneous (or uniform) and the nonhomogeneous (or nonuniform) traffic load scenarios.

This paper addresses the problem of dynamic link adaptation under multiple quality-of-service (QoS) constraints in cellular wideband code-division multiple-access (WCDMA) systems. A novel dynamic joint rate and power adaptation framework is proposed for downlink data transmission in a multicell variable spreading factor (VSF) WCDMA system where the different classes of users have different signal-to-interference ratio (SIR) requirements. Based on a general downlink SIR model, the problem of optimal dynamic rate and power adaptation under multiple SIR constraints is also formulated, for which the rate and power allocation can be found by an exhaustive search. Two schemes, namely, near-optimal and suboptimal schemes, are proposed for implementation-friendly dynamic rate and power adaptation. Performance of dynamic joint rate and power adaptation under the proposed framework is evaluated under random micro-mobility model with uncorrelated long-term fading and a directional micro-mobility model with correlated long-term fading in a cellular WCDMA environment.

Single-cell and multiple-cell direct-sequence code-division multiple-access (DS-CDMA) systems supporting heterogeneous traffic are investigated when decorrelating detector is used at receiver. Theoretical analyses and numerical examples are presented to study the effect of imperfect power control on the system performance of the reverse link. As to the forward link, the system performance is analyzed and the power allocation problem at base stations is formulated as a constrained optimization problem. Two algorithms, namely, the optimal algorithm and the unit transmission power allocation (UTXPA) algorithm, are proposed to solve this optimization problem. Computer simulations are presented to compare the performance of the proposed algorithms.

In this letter, concatenation of trellis-coded modulation (TCM) with differential space-time block codes (DSTBC) is considered under frequency-flat Rayleigh-fading channels with and without perfect interleaver. It is shown that the design criteria of TCM concatenated with DSTBC are exactly the same as that of TCM concatenated with space-time block codes (STBC) in perfectly known channels. They are effective code length over span two symbol intervals and minimum product-sum distance over span two symbol intervals. Based on the design criteria, several new rate-2/3 systematic Ungerboeck's TCM schemes have been found by computer search. They outperform existing optimal TCM schemes designed for additive white Gaussian noise or flat fading channels.

The usage of multichannel receivers that are followed by diversity combining can significantly improve the performance of wireless communications links. In this paper we investigate in some detail two popular techniques for diversity combining, namely maximal ratio combining (MRC) and equal gain combining (EGC). The main goal is to investigate under which circumstances it can be guaranteed that a certain technique does indeed decrease the probability of error of a multichannel receiver. The analyzed fading model is quite general with the only assumption that fading gains are scaled exchangeable random variables. The crucial mathematical tool used to produce the results of this paper is the powerful theory of stochastic majorization. Among other results, it was shown that the average bit error probability of the MRC receiver with equally distributed average powers always decreases with the addition of a new diversity branch if the total power is fixed.

This paper models and analyzes the performance of opportunistic scheduling under constrained frame error rate (FER) requirement for downlink data transmission in cellular CDMA networks using high-order modulation and multicode formats. The effects of multipath-induced interference and imperfect self-interference cancellation on single-transmission are specifically modeled. Based on the proposed framework the performances of the several opportunistic schedulers are evaluated using Monte Carlo simulation considering both bursty and nonbursty downlink data traffic flows.

This paper addresses the problem of dynamic rate and power adaptation for forward link data transmission using high-order modulation and multicode formats in cellular wideband code division multiple access (WCDMA) networks. A novel framework for dynamic joint adaptation of modulation order, number of code channels (hence transmission rate) and transmission power is proposed for downlink data transmission in a cellular WCDMA system where the different users have similar frame error rate (FER) requirements. Based on a general downlink signal-to-interference ratio (SIR) model, the problem of optimal dynamic rate and power adaptation is formulated, for which the rate and power allocation can be found by an exhaustive search. Two heuristic-based dynamic rate and power allocation schemes are proposed. Performance of dynamic joint rate and power adaptation under the proposed frame-work is evaluated under random micro-mobility model using computer simulations.

A novel dynamic joint rate and power adaptation framework is proposed for downlink data transmission in a multicell variable spreading factor (VSF) WCDMA system where the different classes of users have different signal-to-interference ratio (SIR) requirements. Based on a general downlink SIR model, the problem of optimal dynamic rate and power adaptation under multiple SIR constraints is also formulated, for which the rate and power allocation can be found by an exhaustive search. Performance of the dynamic joint rate and power adaptation under the proposed framework is evaluated under random micro-mobility model with uncorrelated long-term fading and a directional micro-mobility model with correlated long-term fading in a cellular WCDMA environment for both homogeneous (or uniform) and the non-homogeneous (or non-uniform) traffic load scenarios.

Tarokh's differential space-time block codes (DSTBC) can provide a full spatial diversity and be decoded without channel state information. The bit error rate performance of a conventional differential detection has 3-dB degradation compared to a coherent detection in a quasi-static fading channel. Differential detection experiences more degradation in a fast fading channel and error floor appears at high SNR. In [E. Chiavaccini and G.M. Vitetta, May 2002], an approximate maximum likelihood receiver was derived and it reduced the error floor significantly. In this paper, we modify the receiver in [E. Chiavaccini and G.M. Vitetta, May 2002] and apply the concept of multistage decision-directed estimator with intrablock-interference cancellation to obtain further improvement. The proposed receiver works efficiently at moderate to high SNR and at the fading rate between f/sub d/T = 0.02 and f/sub d/T = 0.07.

Dynamic rate adaptation for uplink data transmission in a cellular multidimensional multicode (MDMC) direct-sequence code-division multiple-access packet data network is modeled and analyzed. An analytical framework is developed to evaluate the performances of radio link level dynamic rate adaptation schemes under multipath fading and log-normal shadowing. The radio link level throughput under optimal dynamic rate adaptation (having exponential computational complexity) and different heuristic-based suboptimal rate adaptation schemes can be assessed under the presented analytical framework. The performance of MDMC signaling is compared with that of the single-code variable spreading factor (VSF) signaling. To this end, based on an equilibrium point analysis of the system in steady-state, a base station-assisted and mobile-controlled dynamic rate adaptation scheme is presented.

Using a circular contour integral representation for the generalized Marcum-Q function, Q/sub m/(a,b), we derive a new closed-form formula for the moment generating function (MGF) of the output signal power of a dual-diversity selection combiner (SC) in bivariate (correlated) Nakagami-m fading with positive integer fading severity index. This result involves only elementary functions and holds for any value of the ratio a/b in Q/sub m/(a,b). As an aside, we show that previous integral representations for Q/sub m/(a,b) can be obtained from a contour integral and also derive a new, single finite-range integral representation for Q/sub m/(a,b). A new infinite series expression for the MGF with arbitrary m is also derived. These MGFs can be readily used to unify the evaluation of average error performance of the dual-branch SC for coherent, differentially coherent, and noncoherent communications systems.

The sum capacity of optimally allocated spreading sequences with and without power control is studied for synchronous code-division multiple-access channels subject to frequency flat fading. Continuing upon the recently derived characterization of sum capacity for asymmetric received powers with no power control at the transmitter, we present an asymptotic analysis of the sum capacity in the wideband limit of a large number of users and evaluate possible gains compared with the random spread sequences. Next, we discuss group orthogonal optimal sequence allocation and analyze its potential to decrease the complexity of the receiver while achieving the sum capacity of optimally allocated equal-energy sequences. For the power controlled case, we give a general characterization of sum capacity and identify the optimal power-control law and sequence allocation that achieves this capacity. These results are also analyzed in the asymptotic limit of a large number of users.

Spectral efficiency presents the ultimate limit on data rate per unit bandwidth of a certain communication system. For direct-sequence code-division multiple access systems, the spectral efficiency has been derived in case of synchronous reception for optimal and linear multiuser receivers, flat-fading and nonfading environments, as well as single and multicell cellular networks. The most pervasive model employed in all these analyses is the large system random signature model. For the decision feedback receivers, previous research handled only the nonfading case while the case of fading channels remained unknown. This paper analyzes the spectral efficiency of the popular conventional decision feedback receiver (CDFR) in flat- and frequency-selective fading channels with and without power ordering. Results show that in the case of power ordering before cancellation and very large system loads, the spectral efficiency of this receiver in fading channels can be even larger than in the case of channels with no fading. We also discuss and identify optimal power control laws for the CDFR with and without power ordering. The power control law which equalizes single-user capacities in the case of power ordering is also discussed.

This paper proposes a novel dynamic joint rate and power control procedure for downlink data transmission in a multicell variable spreading factor wideband code-division multiple-access (WCDMA) system where the different users have similar quality-of-service requirements in terms of the signal-to-interference ratio (SIR). Two variations of the dynamic joint rate and power allocation procedure, namely, Algorithm-1 and Algorithm-2, are presented. The performances of these two schemes are compared to the performance of the optimal dynamic link adaptation for which the rate and power allocation is found by an exhaustive search. The optimality criterion is the maximization of the total radio link level capacity (or sum-rate capacity) in terms of the average number of radio link level frame transmitted per adaptation interval under constrained SIR and power limit in the base station transmitter. The proposed schemes have linear time complexity as compared to the exponential time complexity of the optimal scheme and achieve better radio link level throughput fairness compared to the optimal link adaptation scheme with a moderate loss in total throughput. Performance evaluation is carried out under random and directional micromobility models with uncorrelated and correlated long-term fading, respectively, in a cellular WCDMA environment for both the homogeneous (or uniform) and the nonhomogeneous (or nonuniform) traffic load scenarios.

We propose a measurement-based dynamic random access (RA) code assignment procedure for prioritized packet data transmission in wideband code-division multiple access (WCDMA) networks. This dynamic adaptation process is based on analytical performance results derived for random packet access under Rayleigh fading in WCDMA networks. The performance of the proposed measurement-based RA code assignment procedure with three different adaptation methods is evaluated by using computer simulations. The performance of the proposed scheme is compared with those of a retransmission control-based and static channel allocation-based prioritized packet access scheme. An integrated (physical layer and link layer) delay-throughput performance model is presented for finite population RA WCDMA systems. The proposed dynamic RA code assignment procedure can be used in an adaptive quality of service (QoS) framework for dynamically adjusting the QoS of prioritized RA data traffic in the evolving WCDMA-based differentiated services wireless Internet protocol networks.

A robust symbol-timing and carrier-frequency synchronization scheme applicable to orthogonal frequency-division-multiplexing systems is presented. The proposed method is based on a training symbol specifically designed to have a steep rolloff timing metric. The proposed timing metric also provides a robust sync detection capability. Both time domain training and frequency domain (FD) training are investigated. For FD training, maintaining a low peak-to-average power ratio of the training symbol was taken into consideration. The channel estimation scheme based on the designed training symbol was also incorporated in the system in order to give both fine-timing and frequency-offset estimates. For fine frequency estimation, two approaches are presented. The first one is based on the suppression of the interference introduced in the frequency estimation process by the training symbol pattern in the context of multipath dispersive channels. The second one is based on the maximum likelihood principle and does not suffer from any interference. A new performance measure is introduced for timing estimation, which is based on the plot of signal to timing-error-induced average interference power ratio against the timing estimate shift. A simple approach for finding the optimal setting of the timing estimator is presented. Finally, the sync detection, timing estimation, frequency estimation, and bit-error-rate performance of the proposed method are presented in a multipath Rayleigh fading channel.

The spectral efficiency presents the ultimate limit on the data rate per unit bandwidth of a certain communication system. For the DS-CDMA systems spectral efficiency has been derived for optimal and linear multiuser receivers in the case of synchronous reception, fading and non-fading environment as well as single and multi-cell cellular networks. The most pervasive model employed in all these analyses is the large system random signature model. For the decision feedback receivers the previous research handled only the non-fading case while the case of fading channels remained unknown. This paper analyses the spectral efficiency of the decision feedback receiver in a fading channel with and without power ordering. The results show that in the case of power ordering before cancellation the multiuser diversity effect previously encountered by S. Shamai (Shitz) and Verdu (see IEEE Trans. on Inform. Theory, vol.47, p.1302-27, May 2001) occurs. Multiuser diversity is the effect where the spectral efficiency of a certain multiple-access system improves in fading channels due to the multiplicity of users that share the system and provide the necessary power diversity. Also, analyzed in this paper is the case of imperfectly estimated channel gains in fading environments or the case of imperfect power control. The spectral efficiency loss incurred by this estimation error is analyzed in the case of the conventional decision feedback receiver.

This paper models and analyzes the performance of TCP (transmission control protocol) under joint rate and power adaptation with constrained BER requirements for downlink data transmission in a multi-cell VSF (variable spreading factor) WCDMA system. The performance of TCP in a wide-area Internet environment is evaluated by using computer simulations considering user mobility, short-term fading (i.e., multipath fading) and long-term fading (i.e., shadowing). The motivation is to explore the inter-layer protocol interactions and to identify suitable transport and radio link layer mechanisms to improve wireless TCP performance in a cellular WCDMA environment.

Algorithms are developed to solve the power allocation problem at the base station (BS) under the constraints of BS transmission power and quality of service (QoS) for single-cell and multiple-cell direct-sequence code-division-multiple-access (DS-CDMA) systems supporting heterogeneous traffic, where a decorrelating detector is employed at the receiver. The presented numerical examples show that the unit transmission power allocation (UTXPA) algorithm offers performance close to that of the optimal algorithm with much reduced computational complexity.

Multiple symbol differential detection (MSDD) of space-time block code is considered in this paper. It is known that MSDD of space-time block code has very high complexity due to the block nature of the code. Therefore, two reduced complexity MSDD are proposed. The first scheme employs multiple differential feedback detection (MDFD). The second scheme, denoted as reduced search detection, works on reducing the number of symbols in the joint decision metrics. Simulation results show that MDFD is suitable for BPSK and reduced search detection is suitable for QPSK and 8-PSK. The improvement over differential detection is 1 dB with 11-block observation length with BPSK and 6-block observation length with QPSK and 8-PSK applied with reduced complexity schemes.

Multidimensional signaling is newly designed to provide a diversity gain of order 2 using two transmit antennas in uplink transmission of wide-band CDMA (W-CDMA) while achieving high and multiple data rates at the same time. The rate can be easily changed on the slot basis in a frame transmission by adapting the order of multidimensional signaling to the incoming traffic. The multidimensional signaling of order zero simply reduces to conventional multicode scheme, so there exists a tradeoff between rate and complexity. Also, the use of multidimensional signaling results in far reduced envelope variations at the maximum rate. With the transmit diversity, the uplink signal-to-interference ratio (SIR) will be further stabilized to meet the requirements of multimedia traffic. Statistics of interferences are characterized in terms of their second- and fourth-order moments from which diversity gain is theoretically verified. For realistic multipath fading channels, considering both equal and unequal average path powers, the average probability of symbol error is obtained in compact form, in which the two schemes, multidimensional signaling with and without transmit diversity are compared, and then with nonmulticode scheme in view of the bit error rate (BER). Numerical and simulation results show that the multidimensional signal with transmit diversity provides a significant gain over that with no diversity, and furthermore outperforms nonmulticode scheme subject to the same signal energy per bit and chip rate.

A reduced complexity channel estimation for OFDM systems with transmit diversity is proposed by exploiting the correlation of the adjacent subchannel responses. The sizes of the matrix inverse and the FFTs required in the channel estimation at every OFDM data symbol are reduced by half of the existing method for OFDM systems with nonconstant modulus subcarrier symbols or constant modulus subcarrier symbols with some guard tones. The complexity reduction of half FFTs size and some matrix multiplications is still achieved for constant modulus subcarrier symbols with no guard tones. The price for the complexity reduction is a slight BER degradation and for the channels with small relative delay spreads, the BER performance of the reduced complexity method becomes quite comparable to the existing method. An alternative approach for the number of significant taps required in the channel estimation is described which achieves a comparable performance to the case with the known suitable number of significant taps. A simple modification which reduces the lost leakage of the nonsample-spaced channel paths is also proposed. This modification achieves a substantial performance improvement over the existing method without any added complexity.

This paper analyzes two different low-complexity multiuser detection schemes for the oversaturated synchronous CDMA systems, ie, systems which can accommodate more users than the processing gain of the system. The first scheme is multistage iterative alternative detection of the users of the two groups combined with interference cancellation. The bit-error rate performance analysis of this scheme using Gaussian approximation is also derived and it is shown that this scheme is the realization of the space altering generalized expectation maximization algorithm known in signal processing literature. As an improvement for the shortcomings of the first scheme in near-far situations, a group orthogonal sequence allocation scheme is introduced. It is demonstrated that it can lead to efficient optimal multiuser detection. It is also shown that if all groups of sequences attain the Welch bound for the sum of squared sequence correlation coefficients then the optimal joint multiuser detection maximizes the sum capacity of the channel.

In this paper, a measurement-based dynamic RA (Random Access) code assignment procedure Is proposed for prioritized packet data transmission in WCDMA (Wideband Code Division Multiple Access) networks. This dynamic assignment process is based on analytical performance results derived for random packet access under Rayleigh fading in WCDMA networks. The performance of the proposed measurement-based RA code assignment procedure with three different adaptation methods is evaluated using computer simulation for bursty data packet arrival patterns. The performance of the proposed scheme is compared to those of a retransmission control-based and static channel allocation-based prioritized packet access schemes. The proposed scheme can be used in an adaptive QoS (Quality of Service) framework for dynamically adjusting the QoS of prioritized random access data traffic In the evolving WCDMA-based DS (Differentiated Services) wireless IP (Internet Protocol) networks.

A fast converging blind adaptive multiuser detector is proposed in this paper. In the proposed method, the convergence of the blind adaptive detectors for weak power users is accelerated by successively canceling the interference of the strong power signals from the received signal. The order and channel parameters for the interference cancellation are determined from the steady state of the detectors. Numerical results presented show that satisfactory performance can be achieved in various environments.

Optimal dynamic rate allocation among mobile stations for variable rate packet data transmission in a cellular wireless network is an NP-complete problem; therefore, sub-optimal solutions to this problem are sought. Again, interference calculation is non-trivial in the case of a packet-switched cellular CDMA network with heterogeneous traffic load in different cells. In this paper, a sub-optimal two-step dynamic rate selection procedure is proposed for uplink packet data transmission in cellular WCDMA (wideband code division multiple access) networks. A novel 'mean-sense' approach for inter-cell interference calculation is employed assuming homogeneous traffic load in the different cells. Two different error control alternatives for this variable rate packet transmission environment are presented and their performances are analyzed for three different channel models. The performance of the proposed two-step rate selection procedure is fairly close to that of the optimal rate allocation found through exhaustive search.

A unified time-division multiple access (TDMA) based centralized wireless access scheme is proposed for performing the statistical multiplexing of bursty data sources in a wireless packet data network. This scheme combines dynamic bandwidth allocation with admission control and packet conditioning (at the mobile stations) to provide fair bandwidth distribution among bursty data flows with different profile rates (or subscription levels) in an error-prone environment. The dynamic bandwidth allocation policy is credit-based and both the burst-level and the packet-level bandwidth allocations are considered. The performance of the scheme is evaluated using computer simulations for different total subscription levels, for different compositions of flows with different profile rates, and for different channel quality with different channel-error correlation patterns. The simulation results show that the throughput variability among flows with the same level of subscription is considerably small except for long range dependent flows with very high traffic burstiness. The relative throughput fairness among flows with different profile rates can also be achieved. The post facto loss and delay values (i.e., observed average packet delay and average packet loss values) for the flows depend on the corresponding delay tolerance limits of the data bursts, TDMA frame-length, and the wireless link utilization level. The energy efficiency of the wireless access scheme is evaluated in terms of the average transmitter usage time and the average receiver usage time in the mobile stations for both the burst-level and the packet-level bandwidth allocation. The proposed scheme can be used in an adaptive quality-of-service (QoS) framework for dynamically adjusting the QoS for flows in order to accommodate wireless channel errors and user mobility.

Two unified expressions for computing the refined outage criterion (which considers the receiver noise) in cellular mobile radio systems are derived using the Laplace and Fourier inversion formulas. Since these expressions do not impose any restrictions on the signal statistics while being easy to program, they provide a powerful tool for outage analysis over generalized fading channels. We also assess compatibility and applicability of previously published approaches that treat noise as cochannel interference (noise-limited model) or consider a minimum detectable receiver signal threshold and receiver noise. The outage probability in an interference-limited case can be evaluated directly by setting the minimum power threshold to zero. The analysis of correlated interferers is presented. Results are also developed for a random number of interferers. Several new closed-form expressions for the outage probability are also derived. Some previous studies have suggested approximating Rician desired signal statistics by a Nakagami-m (1960) model (with positive integer fading severity index) to circumvent the difficulty in evaluating the outage in Rician fading. The suitability of this approximation is examined by comparing the outage performance under these two fading conditions. Surprisingly, some basic results for Nakagami-m channel have been overlooked, which has led to misleadingly optimistic results with the Nakagami-m approximation model. However, similar approximation for the interferer signals is valid.

High rate transmission can be realized using multiple orthogonal codes (MOC), as proposed in the third-generation wide-band code-division multiple-access (W-CDMA) standard. However, the linear sum of MOC channels is no longer constant amplitude, and a highly linear, power-inefficient amplifier may be required for transmission. Recently, a nonlinear block coding technique called precoding is introduced to maintain a constant amplitude signal after superposition of MOC channels. This is achieved by adding redundancy. In this paper, we first describe a multidimensional signaling scheme that recovers some information rate loss by precoding. Second, we propose a self-interference (SI) cancellation scheme resulting from a code diversity between the in-phase and quadrature subchannels among MOC channels. In a typical wireless channel with multipath fading, this type of SI can be detrimental especially when the number of parallel MOC channels is large. Third, we show that the error detection capability of precoding can be combined with code diversity, resulting in a diversity gain. In addition, we show that the diversity gain can be achieved using antenna diversity to assure the degree of freedom in code diversity, and even with the large number of MOC channels, the error performance can be maintained reliably while outperforming the variable spreading factor scheme in W-CDMA.

The moment generating function (MGF) of the signal power at the output of dual-branch switch-and-stay selection diversity (SSD) combiners is derived. The first-order derivative of the MGF with respect to the switching threshold is also derived. These expressions are obtained for the general case of correlated fading and nonidentical diversity branches, and hold for any common fading distributions (e.g., Rayleigh, Nakagami-m, Rician, Nakagami-q). The MGF yields the performance (bit or symbol error probability) of a broad class of coherent, differentially coherent and noncoherent digital modulation formats with SSD reception. The optimum switching threshold (in a minimum error rate sense) is obtained by solving a nonlinear equation which is formed by using the first-order derivative of the MGF. This nonlinear equation can be simplified for several special cases. For independent and identically distributed diversity branches, the optimal switching threshold in closed form is derived for three generic forms of the conditional error probability. For correlated Rayleigh or Nakagami-m fading with identical branches, the optimal switching threshold in closed form is derived for the noncoherent binary modulation formats. We show previously published results as special cases of our unified expression. Selected numerical examples are presented and discussed.

The performance implications of retransmission diversity packet combining on the RLC (radio link control)/MAC (medium access control) layer and transport layer protocol performance are investigated for three different heuristic-based RLC/MAC layer access control schemes in a CDMA S-ALOHA network under frequency selective Rayleigh fading. The transport layer protocol implements a two-level error recovery mechanism for reliable data transmission. Two different transport layer timer control mechanisms are considered. Implications of some physical layer parameters on system performance are discussed. It is observed that, for two-level error recovery through a reliable transport protocol, the achieved throughput depends on the transport protocol timer control mechanism and a suitable mechanism can be identified for an underlying RLC/MAC layer access control scheme and a particular physical layer design.

This paper presents a general method for calculating the average error rates and outage performance of a broad class of coherent, differentially coherent and noncoherent communication systems with/without diversity reception in a myriad of fading environments. Unlike the moment generating function (MGF) technique, the proposed characteristic function (CHF) method based on Parseval's theorem enables us to unify the average error rate analysis of different modulation formats and all commonly used predetection diversity techniques (i.e., maximal-ratio combining (MR), equal-gain combining (EG), selection diversity (SD), switched diversity (SW) and hybrid diversity systems) in a single common framework. The CHF method also lends itself to the averaging of the conditional error probability (CEP) involving the complementary incomplete Gamma function and the confluent hypergeometric function over fading amplitudes, which heretofore resisted to a simple form. As an aside, we show previous results as special instances of our unified framework.

Performance analysis of equal-gain combining (EGC) diversity systems is notoriously difficult only more so given that the closed-form probability density function (PDF) of the EGC output is only available for dual-diversity combining in Rayleigh fading. A powerful frequency-domain approach is therefore developed in which the average error-rate integral is transformed into the frequency domain, using Parseval's theorem. Such a transformation eliminates the need for computing (or approximating) the EGC output PDF (which is unknown), but instead requires the knowledge of the corresponding characteristic function (which is readily available). The frequency-domain method also circumvents the need to perform multiple-fold convolution integral operations, usually encountered in the calculation of the PDF of the sum of the received signal amplitudes. We then derive integral expressions for the average symbol-error rate of an arbitrary two-dimensional signaling scheme, with EGC reception in Rayleigh, Rician, Nakagami-m (1960), and Nakagami-q fading channels. For practically important cases of second- and third-order diversity systems in Nakagami fading, both coherent and noncoherent detection methods for binary signaling are analyzed using the Appell hypergeometric function. A number of closed-form solutions are derived in which the results put forward by Zhang (see ibid., vol.45, p.270-73, 1997) are shown to be special cases.

A theoretical framework is developed to analyze the user membership in cellular networks. The main interest is on code-division multiple-access (CDMA) networks, although the validity of the proposed approach is not restricted to these networks. The membership of a user terminal to a certain base station (BS) is established if the local mean attenuation to this BS is the lowest one among all surrounding BSs. The estimate of local mean attenuation on the radio links from a mobile terminal to each of the surrounding BSs is carried out through proper filtering of the sequences of received signal strength measurements taken on broadcast signals at regular time intervals. In CDMA networks, pilot channels can be considered, while broadcast control channels can be generically considered in narrow-band systems. A decision is made each time on whether the terminal is to be assigned to its "current" BS or if it would be better served by a different BS. Two performance measures are considered: the probability that the best BS is not selected and the average number of membership switchings per time unit. A channel model with log-normal shadowing and fast fading superimposed is considered. Analytical expressions for the above-mentioned performance measures are derived in a general system scenario. From numerical results, it is seen that a proper choice of filter parameters is required to achieve the lowest values for both performance measures. Moreover, these values are not negligible when the mobile terminal is close to a boundary cell region. The obtained results are considered to be of interest in handover and power control algorithms.

We address the issue of efficient integration of multi-rate traffic supported by third generation DS-CDMA systems. We have previously proposed the notion of line rate (adjusted data rate before spreading) to incorporate traffic with a wide range of source rates. Each selected line rate will support a group of multi-rate traffic. We evaluate the impact of line rate(s) selection on the forward link capacity of a system with integrated/mixed-rate traffic. We first derive the methodology of evaluating the capacity of mixed-rate traffic in the forward link. Our focus is to investigate the effect of processing gain and activity factor (resulting from a selected line rate) on the capacity of different traffic types. We also address the issue of Walsh-Hadamard codes usage of different length (at each selected line rate) and its impact on line rate selection. Our analysis provides insight into the use of line rate(s) for traffic integration and optimal selection of line rate(s).

An exact analytical expression in a simple form for computing the average symbol error rate (SER) of an arbitrary two-dimension signaling format with equal-gain diversity (EGC) receiver is not available in the literature despite its practical and theoretical importance. The principle difficulty is finding a closed-form expression for the probability density function (PDF) of a sum of L (i.e., diversity order) random fading amplitudes. We develop an alternative, direct technique to evaluate the exact performance of EGC diversity systems (expressed in terms of a single or double finite-range integrals) in Rayleigh, Rician and Nakagami fading channels. Our new approach relies on the use of Parseval's theorem to transform the error integral into the frequency domain. Since the Fourier transform of the PDF is the characteristic function (CHF), which is available in this case, our solution is general and exact. The CHF method also circumvents the need to perform an L-fold convolution integral which is usually encountered in the calculation of the PDF of the sum of the received signal amplitudes. Interestingly, we can also get some new closed-form solutions for binary CPSK and CFSK in the Nakagami fading channel for all L/spl les/3. Closed-form formulas for binary DPSK and NCFSK with EGC may also be obtained for L<3.

This paper outlines a unified approach to performance evaluation of a broad class of coherent, differentially coherent and noncoherent digital communication systems, with dual-branch switched diversity (SWC) reception over generalized fading channels. The moment generating function (MGF) of the signal power at the output of the SWC combiner and the first-order derivative of the MGF with respect to the switching threshold are derived. These expressions are obtained for the general case of correlated fading and nonidentical diversity branches, and hold for any common fading distributions (e.g., Rayleigh, Nakagami-m, Rician, Nakagami-q). The optimum switching threshold (in a minimum error rate sense) is obtained by solving a nonlinear equation which is formed by using the first-order derivative of the MGF. This nonlinear equation can be simplified for several special cases: (a) closed-form expressions for the optimal switching threshold are derived for three generic forms of the conditional error probability by assuming independent and identically distributed diversity branches; and (b) a closed-form formula for the optimal switching threshold is derived for the non-coherent binary modulation formats in correlated Rayleigh or Nakagami-m fading with identical fading statistics.

This article investigates the asymptotic error-rate behavior for the noncoherent on-off keying (OOK) signaling scheme in different fading environments and at both extremes of the signal-to-noise ratio (SNR). A transcendental equation to compute the optimum threshold level of noncoherent OOK operating over a Rician fading channel is derived. The optimum threshold level and its corresponding ratio of the mark and space error probabilities in additive white Gaussian noise (AWGN). Rayleigh, and Rician channels are tabulated as a function of the SNR. Geist (see ibid., vol.42, p.225, 1994) has shown that mark and space errors contribute equally to the average error probability in an AWGN channel when the SNR is large with optimum threshold setting. We show that mark errors predominate when the SNR is small and/or in fading channels.

Exact integral expressions are derived for calculating the symbol-error rate (SER) of multilevel quadrature amplitude modulation (MQAM) in conjunction with L-fold antenna diversity on arbitrary Nakagami fading channel. Both maximal-ratio combining (MRC) (in independent and correlated fading) and equal-gain combining (EGC) predetection (in independent fading) diversity techniques have been considered. Exact closed-form SER expressions for two restricted Nakagami fading cases (MRC reception) are also derived. An exact analysis of EGC for MQAM has not been reported previously, despite its practical interest. Remarkably, the exact SER integrals can also be replaced by a finite-series approximation formula. A useful procedure for computing the confluent hypergeometric series is also presented.

This paper surveys some of the diversity techniques commonly used in cellular radio and satellite communication systems to mitigate the detrimental effects of signal fading. Subsequently, an analytical technique well suited to numerical analysis is presented for computing the average symbol error probability (SER) of a wide class of coherent, differentially coherent and noncoherent communication systems with microdiversity reception under a myriad of fading scenarios. We restrict our analysis to a predetection maximal-ratio combining (MRC) scheme, although this method applies to other diversity combining techniques as well. Our novel derivation relies upon the properties of the moment generating function (MGF) of the fading channels, the use of an alternative exponential form of the complementary error function, and the application of Gauss-Chebychev quadrature (GCQ) rules. The closed-form expressions obtained are sufficiently general to allow for arbitrary fading parameters as well as dissimilar mean signal strengths across the diversity branches. Moreover, this method is computationally stable and approximates the true value of average SER within any degree of accuracy.

This paper outlines an efficient method to concurrently optimize a multiplicity of design variables for continuous selective-repeat (SR) and go-back-N (GBN) automatic repeat request (ARQ) strategies, both in noiseless and noisy feedback channels. For these ARQ protocols, we adapt either the number of identical message blocks sent in each transmission (in the case of GBN scheme) or the number of copies of a block retransmitted to handle a NACKed codeword (for the SR protocol) dynamically to the estimated channel condition. The channel state information is obtained by counting the contiguous acknowledgment (ACK or NACK) messages. Exploiting the asymptotic properties of the steady state probability expressions, we show analytically that the optimum solution indeed lies in the infinite space. Subsequently, a simple expression to estimate the suboptimal design parameters is suggested. Our approach of minimizing the mean-square error function yields to a quantitative study of the appropriateness of the selected parameters. Exact analytical expressions that allows us to compute the throughput crossover probability between any two arbitrary multicopy transmission modes are derived. The results provide fundamental insights into how these key parameters interact and determine the system performance.

This letter presents a simple method to simultaneously optimize a multiplicity of design parameters for the adaptive automatic repeat request strategy previously reported, and subsequently provides a quantitative measurement that reflects the appropriateness of the selected parameters. An exact analytical expression that allows us to compute the throughput crossover probability between the two different protocols is derived. The results provide fundamental insights into how these key parameters interact and determine the system performance.

Maximum-likelihood diversity combining is investigated for an FFH/MFSK spread spectrum system in partial-band noise (PBN). The structure of maximum-likelihood diversity reception in PBN plus white Gaussian noise is derived. It is shown that signal-to-noise ratio and the noise variance at each hop have to be known to implement this optimum diversity combiner. Several suboptimum diversity combining schemes are also considered. The performance of the optimum combining scheme is evaluated. It is shown that adaptive gain control diversity combining actually achieves the optimum performance when interference is not very weak.

We derive a closed-form expression for the power spectral density of amplitude/phase-shift keyed bit sequences randomized through self-synchronizing scrambling when the source sequence is a stationary sequence of statistically independent bits. In addition to the dependence on the symbol pulse shape, duration, and the signal space values with which symbols are represented, we show that the power spectral density is dependent only on the probability of logic ones in the source bit stream, the period of the impulse response of the scrambling shift register, and the number of logic ones in this period. Our results confirm that optimum randomization results with use of primitive scrambling polynomials and poorest randomization occurs with "two-tap" polynomials of the form x/sup D/+1.

This paper outlines a systematic and efficient method to concurrently optimize a multiplicity of design variables for an adaptive go-back-N ARQ strategy both in noiseless and noisy feedback channels. For this continuous ARQ protocol, we adapt the number of identical message blocks sent in each transmission dynamically to the estimated channel condition. The channel state information is obtained by counting the contiguous ACK and NACK messages. Exploiting the asymptotic properties of the steady-state probability expressions, we show analytically that the optimum solution indeed lies in the infinite space. Subsequently, a simple method to estimate the suboptimal design parameters is suggested. Our approach of minimizing the mean square error (MSE) function also yields to a quantitative study of the appropriateness of the selected parameters. The results provide fundamental insights into how these key parameters interact and determine the system performance.

Future multi-media wireless communications systems will require high spectral efficiencies, with reduced receiver complexity. MC-CDMA systems using orthogonal spreading codes systems can increase the spectral efficiency while employing low complexity correlation receivers. A major limitation of multi-carrier systems is the potential for a high crest factor. We examine the requirements for reducing the crest factor in multi-carrier systems, and emphasise the benefits of orthogonal codes for correlation detectors. Our results demonstrate the effectiveness of orthogonal codes in reducing the crest factor while providing low complexity receiver solutions.

An analysis of the user membership in a cellular CDMA network is proposed. It is based on the estimate of the local mean attenuation on the radio links from a mobile terminal to each of the surrounding base stations. The estimate is carried out through proper filtering of the sequences of signal strength measurements performed on the received pilot signals. Two performance measures are considered: the probability that the best base station will not be selected, and the average number of membership switchings per time unit. Assuming a channel model with log-normal shadowing and fast fading superimposed, it is seen that a proper choice of the filter parameters is required to achieve the lowest values for these performance measures. The results obtained are of interest for handover and power control algorithms.

This paper considers the combination of multiple copies of a packet to improve the performance of a slotted direct-sequence spread-spectrum multiple-access (DS/SSMA) ALOHA packet radio system with coherent binary phase-shift keying (BPSK) modulation. Both slotted DS/SSMA ALOHA with and without forward error correction (FEC) are considered. For the case with FEC, maximum-likelihood decoding with code combining is used. Code combining allows for the combination of multiple copies of the same packet (which are typically discarded), to obtain a lower code rate for that specific packet, and therefore an improved probability of successful decoding. In both cases, combining multiple copies of the same packet results in a throughput which is an increasing function over a broad range of offered load, so that the system is more reliable from the point of view of stability. In addition, combining provides a higher throughput and a smaller time delay for packet transmission. This is illustrated by means of analytical and simulation results.

We derive several properties of guided scrambling (GS) encoders and the sequences they generate. We first highlight symmetrical aspects of the GS encoding mechanisms proposed to date, and then show that the existence of discrete components in the power spectrum of the pulse-amplitude-modulated encoded sequence can be predicted from the weight of the scrambling polynomial. We also show that with equiprobable source words, the block or continuous nature of the code has no effect on the statistics of the encoded sequence. We conclude by demonstrating how these properties simplify evaluation of the spectral characteristics of GS coded sequences.

Eighteen new codes are presented which improve the bounds on maximum minimum distance for binary linear codes. They are rate (m-r)/pm, r/spl ges/1, degenerate quasi-cyclic (QC) codes. Based on the known upper bounds, six of these new codes are optimal. In addition, five two-weight QC codes of dimension 8 are given.

This paper deals with the reverse link performance of a slotted direct sequence code division multiple access (DS/CDMA) cellular system with voice and data traffic sharing the same bandwidth. Capacity is studied based on interference analysis. We focus on the mutual interaction between services. The impacts of power level and power control error on the capacity, throughput and delay are analyzed. It is shown that system performance can be improved by selecting appropriate power levels for different services and having a tight power control, especially on voice calls. When the source rate of a data call is twice as high as that of a voice call, two schemes of transmitting data are compared. In scheme 1 and 2, each data packet occupies one and two slots respectively. Under the same capacity condition, better delay performance is achieved by scheme 2.

A frequency-hopped spread-spectrum (FH/SS) packet radio network is considered. Instead of discarding the received packets which were unsuccessfully decoded, the receiver keeps and combines the different received copies of the same packet to improve the throughput and reduce the delay necessary to transmit a packet successfully. It is shown that the throughput is substantially increased over a similar system where the uncorrectable packets are discarded. This system is equivalent to a fast frequency-hopped system where the diversity level is adapted according to the channel conditions. Reed-Solomon (RS) codes are used for error correction and detection.

In this paper, we investigate the application of the concatenated orthogonal/PN spreading scheme for a cellular direct sequence code-division multiple access (DS-CDMA) system with integrated traffic. The performance of the system is evaluated in terms of user capacity. In order to incorporate traffic with a wide range of source rates, line rates (adjusted data rates before spreading) have to be selected for transmission. For traffic with source rates higher than the line rate of concern, we propose the use of concatenated orthogonal/PN spreading sequences to subdivide a high rate stream into parallel line rate streams. Therefore, in this paper, we first analyze the properties of the concatenated orthogonal/PN spreading sequences. The results are used to evaluate their performance for homogenous voice traffic in various cellular mobile environments with multipath fading, lognormal shadowing, and path loss. Our results show that the proposed spreading scheme offers a significant improvement in the forward link capacity as compared to using the conventional nonconcatenated long PN sequence, especially if the multipath fading is Rician (e.g., microcellular and indoor picocellular systems). Incorporating the notion of line rate, we then evaluate the performance of a system with integrated voice and video traffic. Special emphasis is placed on the effect of line rate selection on the overall capacity which leads to the optimal selection of line rates.

This paper proposes chip coding using convolutional codes for fast frequency-hopping spread-spectrum multiple-access (FFH-SSMA) systems. Its performance is evaluated and compared with that of repetition coding which is most commonly used in FFH systems. In our proposal, an information symbol is encoded by a convolutional code of rate 1/n and n chips are transmitted through a frequency hopper. We consider three models when perfect side information (PSI) is available, no side information (NSI) is available, and the ratio threshold test (RTT) is used. The probability density functions (PDFs) of the received signal are derived for asynchronous hopping systems. The performances of convolutional coding with threshold decoding and Viterbi decoding are presented under the constraint of fixed total bandwidth and information bit rate. In comparison with repetition codes, it is found that convolutional codes drastically enhance the system performance. It is identified that Viterbi decoding with RTT offers the most significant performance improvement.

We obtain both the mean and variance of multicell multiuser interference power in a CDMA cellular system with non-ideal handoff and power control. We investigate the effects of handoff operation and choice of line rate (bit transmission rate through the channel) on the Erlang capacity. We consider the call arrival statistics, user membership statistics and finite number of channels available at a base-station in our evaluation of the call dropping rate. The minimum number of channels required at a base-station to ensure a specified quality of service at a given capacity requirement is determined. System capacity is further evaluated considering both the outage probability limited by interference and call dropping rate limited by the finite number of channels.

Guided scrambling (GS) is a line coding technique developed specifically for high bit rate fiber optic transmission systems. This paper continues the development of GS coding by introducing more scrambling polynomials that can be used with this technique. First, a method is presented for constructing polynomials which can be used with balanced encoding. Then it is shown that these polynomials can be used as bases for large families of polynomials, an expansion whose usefulness is demonstrated with the presentation of power spectra for several code configurations. These results indicate that polynomials can be selected from these families to exercise control over average as well as worst-case statistics of the encoded bit stream, a property not available with any other single efficient, balanced line coding technique developed to date. Criteria for polynomial selection are given, and polynomials are recommended for several GS code configurations.>

Multiple error-correcting Reed-Solomon (RS) codes have many practical applications. The complexity of an RS encoder depends on multiplications in the finite field over which the code is defined. We consider a triangular basis for representing the field elements, and present an architecture for a rate-adaptive RS encoder using a triangular basis multiplication algorithm. The architecture supports pipeline and bit-serial operations, and has a low circuit complexity.>

We summarize some efficient techniques and methods which have been developed for high rate multi-media wireless communications. The overall structure of a wireless cellular system which provides integrated services is proposed. Spread spectrum DS-CDMA and modified ATM techniques are chosen to support the system. Efficient signalling and error control coding methods are investigated. The capacity of the DS-CDMA system supporting mixed traffic is evaluated.

Analyzes the multi-cell multi-user interference through a new approach. The statistical effect of hand-off is considered. Differing from the Gaussian approximation, an efficient method for evaluating the performance of a system with small number of users is developed.

This paper considers the application of rate-adaptive coding (RAC) to a spread spectrum multiple access (SSMA) communication system. Specifically, RAC using a variable rate Reed-Solomon (RS) code with a single decoder is applied to frequency-hopped SSMA. We show that this combination can accommodate a larger number of users compared to that with conventional fixed-rate coding. This increase is a result of a reduction in the channel interference from other users. The penalty for this improvement in most cases is a slight increase in the delay (composed of propagation and decoding delay). The throughput and the undetected error probability for a M-ary symmetric channel are analyzed, and performance results are presented.>

An adaptive interference canceller with an adjustable center weight is proposed to improve the performance of the conventional fixed center-weight canceller for applications in data transmission systems such as normal binary phase shift keying (BPSK) and direct sequence spread spectrum BPSK modems. The performance of the new interference canceller is shown to be better than that of the conventional canceller by analysis.>

In this letter, we consider the error correlation in differential phase-shift keying (DPSK) demodulation in terms of its effects on the block and decoded error probabilities. The exact block and decoded error probabilities are derived and computed for additive white Gaussian noise (AWGN). Comparisons are made with the approximate block and decoded error probabilities based on a memoryless model which ignores the error correlation. The effectiveness of interleaving in improving the error performance is addressed under various conditions. Both binary and nonbinary DPSK are studied.>

The performance of M-ary differential phase shift keying (MDPSK) in both tone jamming and Gaussian noise is presented. Previous work has been extended by considering larger signal sets and skewed differential phases with unequal decision regions. The error performance when a frequency offset exists between the jamming tone and MDPSK carrier is also considered.>

A class of rate 2/P quasi-cyclic codes can be characterized in terms of m/spl times/m circulant matrices. In this correspondence, two new codes with parameters (80, 10, 35) and (95, 10, 42) are presented which improve the known lower bound on the maximum possible minimum distance. The former code can be extended with an even parity check bit to an (81, 10, 36) code that establishes that d/sub 2/(81, 10)=36.>

A double error correcting systematic (16,8) quasi-cycle (QC) code that can detect all triple-adjacent errors within each 8-b byte is presented. This code is useful in computer memory applications where adjacent errors are more likely than random errors. As an alternative, a systematic (24,16) QC code is given which corrects single errors, and detects all double errors in addition to all triple-adjacent and quadruple-adjacent errors. A third code, a systematic (32,16) QC code, is presented which corrects all triple errors and detects all quadruple errors. Decoding can be achieved either by syndrome generation and table lookup or by majority logic.>

A Massey-Omura parallel multiplier of finite fields GF(2/sup m/) contains m identical blocks whose inputs are cyclically shifted versions of one another. It is shown that for fields GF(2/sup m/) generated by irreducible all one polynomials, a portion of the block is independent of the input cyclic shift; hence, the multiplier contains redundancy. By removing the redundancy, a modified parallel multiplier is presented which is modular and has a lower circuit complexity.>

An error-correction scheme for an M-ary symmetric channel (MSC) characterized by a large error probability p/sub e/ is considered. The value of p/sub e/ can be near, but smaller than, 1-1/M, for which the channel capacity is zero, such as may occur in a jamming environment. The coding scheme consists of an outer convolutional code and an inner repetition code of length m that is used for each convolutional code symbol. At the receiving end, the m inner code symbols are used to form a soft-decision metric, which is passed to a soft-decision decoder for the convolutional code. The effect of finite quantization and methods to generate binary metrics for M>2 are investigated. Monte Carlo simulation results are presented. For the binary symmetric channel (BSC), it is shown that the overall code rate is larger than 0.6R/sub 0/, where R/sub 0/ is the cutoff rate of the channel. New union bounds on the bit error probability for systems with a binary convolutional code on 4-ary and 8-ary orthogonal channels are presented. For a BSC and a large m, a method is presented for BER approximation based on the central limit theorem.>

Twelve new quasi-cyclic (QC) codes are presented which improve the bounds on the best known binary linear codes. They are rate (m-r)/pm, r>1, codes constructed by deleting r rows from the circulant matrices of rate m/pm QC codes, based on the factors of x/sup m/-1. Heuristic combinatorial optimization was used to find these codes.>

Bit error probability evaluation of trellis-coded modulation (TCM) over fading channels is rather complicated, and the analytical results are limited to loose upper bounds leaving the system designer with the only option of simulation. Cavers and Ho (see IEEE Trans. Commun., vol.40, no.1, p.74-83, 1992) have derived an exact analytical expression for pairwise error-event probability. In this paper, using a different approach, the authors give an alternative method to compute the exact pairwise error event probability of TCM schemes in Rayleigh or Rician fading channels with perfect side information. For example, for a particular TCM scheme, they find the asymptotic difference between the exact and the upper bound of the pairwise error event probability to be 2.68 dB. As it turns out, for Rayleigh fading, the exact pairwise error probability can be calculated in closed-form. For the case of Rician fading, however, a closed-form expression is apparently impossible to obtain. It is observed that an accurate estimate of the bit error probability can be obtained by evaluating a sufficient number of pairwise error-event probabilities. Hence, this approach is a computationally feasible alternative to the simulation.>

A systolic structure for bit-serial division over the field GF(2/sup m/) is developed. Consideration is given to avoid global data communications and dependency of the time step duration on m. This is important for applications where the value of m is large. The divider requires only three basic processors and one simple control signal and its circuit and time complexities are proportional to m/sup 2/ and m, respectively. It does not depend on the irreducible polynomial and can be expanded easily. Moreover, with m additional simple processors, a bit-serial systolic multiplier is developed which uses part of the divider structure. This is advantageous from the implementation point of view, as both the divider and multiplier can be fabricated on a single chip, resulting in a reduction of area.>

Structures for parallel multipliers of a class of fields GF(2/sup m/) based on irreducible all one polynomials (AOP) and equally spaced polynomials (ESP) are presented. The structures are simple and modular, which is important for hardware realization. Relationships between an irreducible AOP and the corresponding irreducible ESPs have been exploited to construct ESP-based multipliers of large fields by a regular expansion of the basic modules of the AOP-based multiplier of a small field. Some features of the structures also enable a fast implementation of squaring and multiplication algorithms and therefore make fast exponentiation and inversion possible. It is shown that, if for a certain degree, an irreducible AOP as well as an irreducible ESP exist, then from the complexity point of view, it is advantageous to use the ESP-based parallel multiplier.>

The class of quasi-cyclic (QC) codes has been proven to contain many good codes. To date the known results are largely codes of the form 1/p and (p-1)/p constructed from circulant matrices. A generalization of these rate 1/p codes to rate (m-1)/pm codes based on the theory of 1-generator QC codes is presented. The results of a search for good codes based on heuristic combinatorial optimization are nine codes which improve the known lower bounds on the minimum distance of binary linear codes.>

The class of quasi-cyclic (QC) codes has been proven to contain many good codes. To date the known QC codes are primarily rate 1/p and (p-1)/p binary codes constructed from circulant matrices. These results are extended to QC codes over GF(3) and GF(4). Codes are constructed using integer linear programming and heuristic combinatorial optimization. Many of these attain the maximum possible minimum distance for any linear code with the same parameters, and several improve the maximum known distances. The link between power residue (PR) codes and QC codes is exploited as a means of constructing new QC codes and to initialize the search algorithm. Previously unknown minimum distances for nonbinary quadratic residue codes are given. The minimum distances for the PR codes and the maximum known distances for the QC codes are tabulated.>

Tables of 1/p and rate (p-1 )/p binary quasi-cyclic (QC) codes that extend previously published results are presented. Many of these codes attain bounds given by T. Verhoeff (1987), who composed a table of bounds on the maximum possible minimum distance of binary linear codes. Many of the codes presented meet or improve these bounds. A best code is considered to be one which has the largest possible minimum distance for the given code dimensions. n and k, and class of error correcting codes. A good code has the maximum known minimum distance for the class of codes. An optimal code is one that achieves the maximum possible minimum distance for a linear code with the same dimensions. Binary power residue codes are found and used to construct QC codes.>

A sequential perceptron-like inference network with novel rule-transfer algorithms is proposed. This network provides an efficient method for building knowledge-based or expert systems. The model is derived from probability and fuzzy set theory. The model has been utilized to organize and maintain the knowledge based. Some critical problems such as the exclusive-OR limitation and the conditional independence assumption have been carefully considered in the modifications

A versatile Reed-Solomon (RS) decoder structure based on the time-domain decoding algorithm (transform decoding without transforms) is developed. The algorithm is restructured, and a method is given to decode any RS code generated by any generator polynomial. The main advantage of the decoder structure is its versatility, that is, it can be programmed to decode any Reed-Solomon code defined in Galois field (GF) 2/sup m/ with a fixed symbol size m. This decoder can correct errors and erasures for any RS code, including shortened and singly extended codes. It is shown that the decoder has a very simple structure and can be used to design high-speed single-chip VLSI decoders. As an example, a gate-array-based programmable RS decoder is implemented on a single chip. This decoder chip can decode any RS code defined in GF (2/sup 5/) with any code word length and any number of information symbols. The decoder chip is fabricated using low-power 1.5- mu , two-layer-metal, HCMOS technology.>

The probability distribution of the received DPSK (differential phase-shift keying) signal under tone jamming is studied. The results should facilitate the analysis of the SFH/DPSK (slow frequency-hopped DPSK) system. The results given are more general than those previously published, in several aspects. First, the differential phase of the transmitted DPSK signal can assume any value. Second, probability distributions are derived instead of a set of probabilities calculated over certain symmetrical regions. This allows analyzing performance for arbitrary selected decision regions as well as determining optimum decision regions for demodulating the DPSK signal. Third, the joint probability distribution of both the magnitude and differential phase of the jammed DPSK signal is given. This can be used in the analysis where both tone jamming and Gaussian noise are considered. These results are used to analyze the error probability performance of a general uncoded SFH/DPSK signal under worst-case tone jamming and Gaussian noise.>

The performance of fast-frequency-hopped M-ary frequency-shift keying with a fixed hop rate is evaluated, utilizing the Chernoff union bound method. The performance criterion used is a throughput measure i.e., an information rate sustained by a system for a given bit error rate, normalized by the hop rate. Both uncoded and coded systems are considered. It is shown using the cutoff rate argument that coding can provide a few dB gain in throughput. This is confirmed by the performance evaluation of various convolutional and block codes. Both partial-band noise jamming and multitone jamming with one tone per M-ary band are considered. Jamming parameters are assumed to be the worst case against the coding channel. Determination of the optimum M is also addressed.>

The development of a 2400-b/s speech digitizer which provides an acceptable level of intelligibility and quality over land mobile satellite channels is described. Performance tests over simulated channels in the UHF band (800 MHz) are presented. The voice digitizer is a linear prediction (LPC) vocoder which uses a channel error correction and concealment procedure tailored to error statistics for a minimum-shift keyed (MSK) downlink to a moving vehicle. The error-handling technique is based on perceptual criteria and utilizes the parametric nature of LPC representation of speech. A single-error-correcting, single-burst-detecting (28, 20) fire code is shown to be the best choice for the application. The intelligibility of the vocoder is measured and compared to the standard LPC-10 algorithm. The major remaining sources of speech quality degradation due to channel errors are determined and ranked.>

The complexity of the algorithm is shown to be asymptotically equal to that of the Viterbi algorithm and is very close for practical noisy channels. The latter is shown by means of computer simulation. The algorithm can be applied directly in an environment where soft-decision decoding is required or preferred. However, depending on the environment, some simplifications may be possible and/or necessary, resulting in suboptimal algorithms. Codes suitable for use with the algorithm should have short total memory length.>

Importance sampling (IS) is a useful technique for reducing the number of Monte Carlo trials in BER estimation. Two important aspects of recent research work in this area are to find more applications of IS BER estimation and to seek a good bias scheme in the implementation of the estimator. This correspondence presents a general and rigorous mathematical description of these aspects of this problem which, we hope, will be useful for further research. We also present a general result on how to choose a good bias scheme which may provide some insight into the problem.

The error-trapping technique, whenever applicable, is easy to implement. Here we investigate the capability of this technique, specially based on the permutation decoding concept. The object is to give exact lower bounds on the code lengthn, for givenk, of the "multiple-error-correcting'' binary(n, k, t)cyclic codes by applying cyclic(T)and squaring(U)(or square rooting) group(T, U)permutations for1)two-step(T, U)permutation decodable codes(todd- and even-valued) and2)three-step(T,U)permutation decodable codes(todd-valued andt = 2). Finally, some general results are presented for the codes that are not permutation decodable for the specific(T, U)group permutations. The derivation of the results involves only the symbol positions of the errors, and consequently, the results are directly applicable to cyclic codes over GF(2^{m}).

We propose a triple error-correcting product code, designed to provide additional error protection for data consisting of 8-bit bytes all having even (or odd) parity (e.g., ASCII characters). A practical decoding algorithm for the code is described.

In this paper we introduce a class of linear codes especially designed to provide additional error protection for data consisting of bytes all having even (or odd) parity (e.g., ASCII characters). The technique consists in adding an overall parity byte computed as a linear function of the information bytes. The linear function is designed such that the resulting codes can correct all single errors and all double errors occurring in distinct information bytes. It is shown that any code which can correct these latter mentioned error patterns has an overall length of at most 37 bytes, and a specific code of length 29 bytes is described. A practical decoding algorithm for the new class of codes is described. Finally, the performance of the codes, when used on the binary symmetric channel, is compared with that of the row-column codes for which the additional parity byte is simply the modulo-2 sum of the information bytes.

A(54,27)code is characterized in terms of a27 \times 27matrix made up of circulant3 \times 3matrices. The minimum distance of this code is found to be11, and its weight distribution is computed. The(54,27)d=11code is extended to a(56,28)d=12external self-dual code. A(54,27)d=10self-dual code is also described in terms of the incidence matrix of a(27,13,6)group difference set defined on GF(3^{3}).

The weight distributions of an(87,29)and a(58,29)circulant code are enumerated. The circulants are based on the quadratic residues and the quadratic nonresidues modulo the prime29. The(87,29)code is known to be cyclic while the(58,29)code is self-dual.

By ordering the elements of GF(pn) lexicographically, rather than sequentially, the recently constructed codes of Rahman and Blake become attractive for ultra high-speed computer applications. The codes are based on supplementary difference sets. The whole procedure is illustrated in detail for the (75,50) double error correcting code.

Without recourse to the normal basis theorem, some(mk, k)cyclic codes are put into quasi-cyclic form, and their weight distributions are obtained. As a special case, some(3p,p)codes of Karlin are examined. It is shown that the dual(3p,2p)codes have minimum distance of at most six.

If a linear binary code of lengthncontains the all-one codeword, than the weights of the code are symmetric. We consider those codes which do not contain the all-one codeword and yet have an equal number of symmetrically placed odd weight words.

Chen et al. [1] give a list of quasi-cyclic (2m,m) codes which have the largest minimum distance of any quasi-cyclic code, for various values ofm. We present the weight distribution of these codes. It will be seen that many of the codes found by Chen et al. [1] are equivalent in the sense of having identical weight distributions.

The weight distribution of some "best"(3m,2m)rate 2/3 binary quasi-cyclic codes of length up to 54 is discussed. The approach taken was to compute the weight distribution of the corresponding(3m,m)rate 1/3 dual code, and then take advantage of the MacWilliams' identities to derive the weight distribution of the(3m,2m)code.

Some optimal rate-\frac{1}{2}quasi-cyclic codes found by Chert et aL [3] are grouped into a small set of equivalence classes with the assistance of a computer. The weight distribution of a selection of these rate-\frac{1}{2}codes is tabulated. In addition, a list of new optimal rate-\frac{2}{3}quasi-cyclic codes of lengths up to 54 is presented.