Low Earth Orbit (LEO) nano-satellites can provide uplink connectivity for large numbers of distributed Internet of Things (IoT) sensing devices. To achieve a target Quality-of-Service (QoS), devices must send packets multiple times, due to collisions. This paper characterises the achievable set of terminal QoS targets, and determines the optimal uplink packet attempt rates. We show that QoS target feasibility is determined by the solution of a linear program (LP), and that the solution gives the optimal packet attempt rates. We show that the QoS targets can be modified using the shadow prices from the LP, to obtain feasibility. We show that our LP based approach can support greater than 30% more ground sensor terminals, compared to existing schemes.

This paper considers multiuser millimeter wave (mmWave) MIMO communication systems where both the base station (BS) and the user equipments (UEs) use analog beamforming (BF). We propose a beam acquisition approach to find the best directions for the narrow beams, required to achieve BS-UE links above a minimum signal-to-noise ratio (SNR) threshold. The multiple UEs first select their beams simultaneously, based on signals transmitted from the BS on wide training beams. The BS then switches to a beam acquisition mode in order to select the best beam direction for each UE, based on training signals the UEs send on the uplink. We propose a novel parallel beam acquisition scheme for this uplink phase. We also propose a user rejection policy, in which weak UEs that do not satisfy a target SNR threshold, equivalent to a certain bit error rate, are rejected. To do so, we derive the posterior probability that a BS beam has a resultant SNR below the target SNR threshold. We also propose a generalized likelihood ratio test (GLRT) to reduce the computational burden. We derive closed-form error probability expressions for the proposed GLRT approach, and examine the trade-off between the beam acquisition time and accuracy in selecting the beams. We show that the beam acquisition time of our proposed approach is as low as 3% of existing approaches.

This paper analyses the data message success rate for Internet of Things (IoT) sensing devices communicating over Low Earth Orbit (LEO) satellite links. We present an analytical framework for optimizing multi-objective multi-packet reception on the uplink. We present an analytical result for the probability of message success for a given ground terminal, and present an analytical result for the overall probability of message success, averaged across all terminals.

This paper considers millimeter-wave (mmWave) networks with hybrid beamforming communications, where base stations have a limited number of radio frequency (RF) chains. The base stations have overlapping coverage to overcome blockage issues in both downlink and uplink transmission. We propose a user association (UA) scheme that minimizes the time required for clearing data traffic of users in the coverage area. We formulate the UA problem as a time allocation problem, allocating time to user-base station links. We provide an innovative two-stage approach to solve this problem. Stage one optimizes a time fraction allocation for user-base station links. Then these time fractions are distributed across the RF chains at each base station using a fully distributed algorithm. Stage two then schedules the user-base station links, provably solving the UA minimum clearing time problem. We then characterize the achievability of any set of target user rates. Numerical results show that our proposed UA scheme achieves significantly reduced clearing times in comparison to baseline schemes.

This paper presents an efficient practical Zak-OTFS modulation implementation using time and frequency windowing methods. We present two general classes of delay-Doppler (DD) twisted convolution (TC) filters (Type-1 and Type-2), and show that they can be realized by time and frequency windowing functions. We then propose practical methods to generate time domain Zak-OTFS signals, for actual transmission, using the windowing functions. For Type-1, the signals are generated using an interpolation filter. For Type-2, they are generated using a form of precoded OFDM. We show that this allows a wide variety of pulse shapes to be implemented in practice for Zak-OTFS modulation. This was not previously possible. We also show that the Type-2 signals are more spectrally efficient than their Type-1 counterparts. Finally, we compare the channel predictability of the two implementations.

This paper designs energy-efficient trajectories for unmanned aerial vehicles (UAVs) harvesting data sequentially from distributed ground nodes. We propose a novel optimization framework for path planning, based on dynamic programming. We develop an optimum backward-forward algorithm that jointly optimizes the hovering locations for each ground node, and the visiting order to those locations. Our algorithm minimizes the total energy consumption of the UAV over its trajectory. Our framework is compatible with various probabilistic wireless communication channel models, and can also be applied to different cost functions, including minimising the total flying time, and allowing for bi-directional communications. We also develop a lower complexity algorithm that approximates the optimum UAV trajectory by decomposing the original problem into two sub-problems, and iterating back and forth between the two. This alternating algorithm has polynomial time complexity, and we show that it produces a near-optimum UAV trajectory, with as little deviation as 5% to 15% from the average energy consumption of the optimum algorithm.

This paper provides capacity results for multi-user mm-wave hybrid-beamforming, and presents optimal joint beam allocation and user scheduling algorithms. We characterize the downlink capacity of a practical system with quantized analog beamforming code-books under the constraint that users cannot be scheduled at the same time if they are closer together than a beam width in angle. We show that the capacity region is determined by a small number of linear inequality constraints. We also present capacity-achieving scheduling algorithms that provide beam allocations guaranteeing that user rate requirements are met within each resource block. In particular, we propose “sand-filling” algorithms that are provably optimal and which have linear complexity. Intuitively, our schemes can be viewed in terms of filling containers with coloured sand, in such a way that the colours at any given height do not conflict with the colours in the other containers at the same height, where the containers represent the RF chains (i.e. the beamforming resources), and the coloured sand represents the users (and their rate requirements). We show a numerical example where the capacity of our scheme is 82% higher than a traditional resource partitioning scheme.

This paper develops a beam direction optimization framework for next-generation GEO satellite networks. The objective is to meet traffic demands at user locations. Given beam-pointing directions, the downlink of the GEO satellite is a vector broadcast channel that consists of a single transmitter and multiple distributed ground users. We characterize the downlink channel matrix for the multibeam satellite network by using an array factor formula for uniform planar arrays. We obtain a necessary and sufficient condition dependent on the downlink channel matrix to provision traffic demands by meeting given SINR targets at user locations. Utilizing the necessary and sufficient conditions, we formulate a joint beam direction and power optimization problem to attain target SINRs which uses minimum total power. Our results demonstrate that analog beamforming with optimized beam shifts can achieve an SINR gain of 8 dB when compared to analog beamforming without beam direction optimization. It also offers a spatial multiplexing advantage of 90 km by enabling simultaneous provisioning of user locations in close proximity within the same frequency band. When compared to hybrid beamforming, our scheme can achieve an SINR gain of 2 dB.

This paper proposes an efficient 3D deployment approach for multiple UAV base stations, to maximize the probability of connections for users spread over a wide area. We consider covering a circular region, such as might apply in a disaster scenario affecting a city centre where terrestrial base stations have become inoperable. We compare two approaches to deploying UAVs. One is a regular triangular arrangement of UAVs and the other is an optimized circle packing arrangement. We start by considering a flying height optimized for a single UAV. We then show that both approaches can be improved by varying the height and flying locations of the UAVs, to expand the overall desired coverage area and overlap the individual UAV coverage areas. We show that the simple regular triangular arrangement can obtain superior connectivity compared to the circle packing approach, with significantly lower complexity.

In this paper, we consider a millimeter wave network deployed to cover an urban street. Each base station (BS) employs hybrid beamforming with a limited number of radio frequency (RF) chains. Its link to any user equipment (UE) is prone to being blocked by vehicles and pedestrians moving along the street. We propose a Round Robin (RR) access protocol with proactive cell switching in which each UE switches its connection to the least loaded line of sight BS at the end of its RR transmission frame or any time when its link is blocked. We compare the UE connectivity performance of the proposed protocol to the conventional cellular network association protocols and the RR protocols which switch only when the link is blocked. Our results reveal the impacts of different system parameters (i.e. the number of BSs, the number of RF chains, the length of RR transmission frame) on the performance of the protocol, and the importance of cell switching in dealing with load balancing as well as blockage

This paper considers the implementation of compressive sensing (CS) approaches for beam alignment (BA) in multiuser millimeter wave (mmWave) MIMO systems. We particularly consider wideband time-varying channels in the practical low SNR regime. We examine two different time scales for beam-switching in the BA training phase at both the base station (BS) and the user equipment (UE). We also compare different time scales for running the CS algorithm at the UE, with their corresponding overhead and complexity. We propose an overarching trial-based protocol that re- initializes the BA process at particular times. We also propose a new approach to designing the CS sensing matrix (SM), based on a deterministic construction. Rows of our proposed SM are Kronecker product decomposable, making it ideal for the BA problem. We show that when block-based beam switching is employed in combination with running the CS algorithm Every Epoch (CS-EE), our proposed SM gives superior performance compared to the other approaches. Moreover, our proposed overarching trial-based protocol enhances the performance even further. We also show that running the CS algorithm Every Block (CS-EB) outperforms CS-EE at the cost of higher complexity and overhead.

This paper jointly optimizes the flying location and wireless communication transmit power for an unmanned aerial vehicle (UAV) conducting covert operations. This is motivated by application scenarios such as military ground surveillance from airborne platforms, where it is vital for a UAV’s signal transmission to be undetectable by those within the surveillance region. Specifically, we maximize the communication quality to a legitimate receiver, who is also a ground-user but outside the surveillance region, under specific constraints on communication covertness, maximum transmit power, and the UAV’s physical location related to the required surveillance quality. We provide an explicit solution to the optimization problem for one of the most practical constraint combinations. For other constraint combinations, we determine feasible regions for flight, that can then be searched to establish the UAV’s optimal location. In many cases, the 2-dimensional optimal location is achieved by a 1-dimensional search. We discuss two heuristic approaches to UAV placement, and show that in some cases they are able to achieve close to optimal, but that in other cases significant gains can be achieved by employing our developed solutions.

Millimetre wave (mmWave) beam tracking is a challenging task because tracking algorithms are required to provide consistent high accuracy with low probability of loss of track and minimal overhead. To meet these requirements, we propose in this article a new cost-effective analog beam tracking framework namely Adaptive Tracking with Stochastic Control (ATSC). Under this framework, beam direction updates are made using a novel mechanism based on measurements taken from only two beam directions perturbed from the current data beam. To achieve high tracking accuracy and reliability, we provide a systematic approach to jointly optimise the algorithm parameters. The complete framework includes a method for adapting the tracking rate together with a criterion for realignment (perceived loss of track). ATSC adapts the amount of tracking overhead that matches well to the mobility level, without incurring frequent loss of track, as verified by an extensive set of experiments under both representative statistical channel models as well as realistic urban scenarios simulated by ray-tracing software. In particular, numerical results show that ATSC can track dominant channel directions with high accuracy for vehicles moving at 72 km/hour in complicated urban scenarios, with an overhead of less than 1%.

In this paper, we propose an adaptive beam search algorithm for the initial alignment of millimetre-Wave beams. The proposed algorithm works by gradually deactivating beams that are unlikely the best beam from a pre-synthesised codebook to save overhead, based on a Bayesian probability criterion with a uniform improper prior. The beam deactivations can be implemented with low-complexity operations that require computing a low-degree polynomial or a search through a look-up table. The proposed algorithm does not require prior knowledge of channel statistics or signal to noise ratios (SNRs) to optimise the amount of searching time, and uses a suitable amount of time to achieve satisfactory beam search accuracy in different SNRs and fading scenarios. Numerical results confirm that the proposed algorithm can adapt to a wide range of channels with a fixed algorithm parameter, and can achieve better balance between beam search overhead and accuracy than non-adaptive approaches with fixed overhead.

Millimeter wave (mmWave) multiple-input multiple-output (MIMO) communication systems with a large number of antennas are power hungry when using conventional high-resolution analog-to-digital/digital-to-analog converters (A/Ds). To reduce the power consumption of mmWave MIMO systems, existing studies have considered hybrid structures with a reduced number of high-resolution or low-resolution A/Ds at either the transmitter or the receiver side. In this paper, we propose and investigate a multi-user hybrid architecture with low-resolution A/Ds equipped at both the transmitter and the receivers. To mitigate the impact of utilizing low-resolution A/Ds at the transceivers, we propose a novel data transmission scheme, which exploits a weighted phased-array to synthesize the beamforming matrix in the analog domain so as to mitigate inter-user interference. Under the scheme proposed, we derive the achievable rate and the energy efficiency to establish guidelines on the optimal resolution choice of A/Ds for hybrid mmWave systems. For a typical total transmit power at the BS, e.g., 30 dBm, the proposed scheme with 5~6-bit A/Ds can significantly improve the energy efficiency by as much as 100% over that of the conventional hybrid MIMO architecture with high-resolution A/Ds (10-bit A/Ds), without significant degradation in data rate performance.

Pseudonyms have been adopted to preserve identity privacy of nodes in distributed networks. Frequent and unlinkable changes of pseudonyms need to be enabled by having at least k nodes change together to confuse potential eavesdroppers. Existing approaches either depend on the coordination from central controllers, or involve interactive signaling between the nodes. This can potentially compromise privacy. This paper proposes a fully uncoordinated approach to change pseudonyms in distributed networks, where each node uses a pseudonym until its expiration and then changes after a random delay. We develop a new model to analyse the time-varying population of changing pseudonyms. Critical conditions are analytically established, under which individual nodes can independently change their pseudonyms while their identity privacy is preserved. The conditions are validated by illustrative examples. Corroborated by simulations, the accuracy of the analytical model improves, as the number of nodes increases. The analysis confirms that, the k-anonymity can be achieved at a negligible throughput loss in the case of large networks.

Millimeter Wave (mmWave) communications rely on highly directional beams to combat severe propagation loss. In this paper, an adaptive beam search algorithm based on spatial scanning, called Iterative Deactivation and Beam Shifting (IDBS), is proposed for mmWave beam alignment. IDBS does not require advance information such as the Signal-to-Noise Ratio (SNR) and channel statistics, and matches the training overhead to the unknown SNR to achieve satisfactory performance. The algorithm works by gradually deactivating beams using a Bayesian probability criterion based on a uniform improper prior, where beam deactivation can be implemented with low-complexity operations that require computing a low-degree polynomial or a search through a look-up table. Numerical results confirm that IDBS adapts to different propagation scenarios such as line-of-sight and non-line-of-sight and to different SNRs. It can achieve better tradeoffs between training overhead and beam alignment accuracy than existing non-adaptive algorithms that have fixed training overheads.

Swift and accurate alignment of transmitter (Tx) and receiver (Rx) beams is one of the fundamental design challenges to support directional transmission in millimeter-wave cellular communications. In this paper, we propose a new Optimized Two-Stage Search (OTSS) algorithm for Tx-Rx beam alignment via beam training. In contrast to one-shot exhaustive search, OTSS judiciously divides the training energy budget into two stages. In the first stage, OTSS explores and trains all candidate Tx-Rx beam pairs and then discards a set of less favorable pairs learned from the measured received signal. In the second stage, OTSS takes an extra measurement for each of the remaining pairs and combines with the previous measurement to determine the best one. For OTSS, we derive fundamental bounds on its misalignment probability under a single-path channel model with ideal codebooks and establish a guideline on its optimized parameter choices. Numerical results have confirmed the advantage of OTSS over the state-of-the-art baselines.

We address the critical problem of hiding unmanned aerial vehicles (UAV) for wireless transmissions by the emerging covert communication technology, since in military surveillance scenarios the disclosure of a UAV's location information may lead to an attack. Specifically, we jointly optimize the UAV's transmit power and height in order to maximize the communication quality to a legitimate receiver subject to a covertness constraint, a maximum transmit power constraint, and a lower bound and an upper bound on the UAV's height. To this end, we first derive the UAV's optimal height for maximizing the legitimate communication quality without any constraint and then we address this problem under constraints in particular the covertness constraint. Our solution explicitly shows the impact of these constraints and reveals the tradeoff among the legitimate communication quality, covertness requirement, and surveillance cost. For example, our examination demonstrates that the legitimate communication quality increases with the surveillance cost represented by the quality of the camera used for conducting surveillance.

This paper proposes a new fully decentralized approach to online placement and optimization of virtual machines (VMs) for network functions virtualization (NFV). The approach is of practical value, as network services comprising a chain of virtual network functions (VNFs) are proposed to be queued on the basis of leading unexecuted VNFs at every server, rather than on the typical basis of services, reducing queues per server and facilitating queue management and signaling. It is also non-trivial because the VNFs of network services must be executed correctly in order at different VMs, coupling the optimal decisions of VMs on processing or offloading. Exploiting Lyapunov optimization techniques, we decouple the optimal decisions by deriving and minimizing the instantaneous upper bound of the NFV cost in a distributed fashion, and achieve the asymptotically minimum time-average cost. We also reduce the queue length by allowing individual VMs to (un)install VNFs based on local knowledge, achieving stable redeployment of VNFs, adapting to the network topology and the temporal and spatial variations of services. Simulations show that the proposed approach is able to reduce the time-average cost of NFV by 71% and reduce the queue length (or delay) by 74%, as compared with existing approaches.

Network Function Virtualization (NFV) can cost-efficiently provide network services by running different virtual network functions (VNFs) at different virtual machines (VMs) in a correct order. This can result in strong couplings between the decisions of the VMs on the placement and operations of VNFs. This paper presents a new fully decentralized online approach for optimal placement and operations of VNFs. Building on a new stochastic dual gradient method, our approach decouples the real-time decisions of VMs, asymptotically minimizes the time-average cost of NFV, and stabilizes the backlogs of network services with a cost-backlog tradeoff of [ε, 1/ε], for any ε > 0. Our approach can be relaxed into multiple timescales to have VNFs (re)placed at a larger timescale and hence alleviate service interruptions. While proved to preserve the asymptotic optimality, the larger timescale can slow down the optimal placement of VNFs. A learn-and-adapt strategy is further designed to speed the placement up with an improved tradeoff [ε, log2(ε)/ε]. Numerical results show that the proposed method is able to reduce the time-average cost of NFV by 23 percent and reduce the queue length (or delay) by 74 percent, as compared to existing benchmarks.

Swift and accurate alignment of transmitter (Tx) and receiver (Rx) beams is a fundamental design challenge to enable the reliable outdoor millimeter-wave communications. In this paper, we propose a new optimized two-stage search (OTSS) algorithm for Tx–Rx beam alignment via spatial scanning. In contrast to one-shot exhaustive search, the OTSS judiciously divides the training energy budget into two stages. In the first stage, OTSS explores and trains all candidate beam pairs and, then, eliminates a set of less favorable pairs learned from the received signal profile. In the second stage, OTSS takes an extra measurement for the each of the survived pairs and combines with the previous measurement to determine the best one. For the OTSS, we derive an upper bound on its misalignment probability, under a single-path channel model with training codebooks having an ideal beam pattern. We also characterize the decay rate function of the upper bound with respect to the training budget and further derive the optimal design parameters of OTSS that maximize the decay rate. OTSS is proved to asymptotically outperform the state-of-the-art beam alignment algorithms and is numerically shown to achieve better performance with limited training budget and practically synthesized beams.

In vehicular ad hoc networks (VANETs), safety messages must be protected for location privacy. Pseudonym schemes have provided a promising solution. However, attacks could still be carried out from the medium access control (MAC) layer. In this paper, we present a new MAC semantic linking attack that links the new and old pseudonyms by analyzing the vehicles' transmission patterns in the MAC layer, even if they change pseudonyms simultaneously. To deal with the attack, a MAC layer aware pseudonym (MAP) scheme is proposed. The MAP scheme is compatible with the standard and coordinates each vehicle to access the wireless medium in a time- slotted manner. In MAP scheme, vehicles change pseudonyms and slot utilization pattern consistently. The interactive influence between the pseudonym changing and safety message transmission is evaluated. Taking the pseudonym age, anonymity set size, time-toconfusion and packet delivery ratio as the performance metrics, extensive simulation results have verified that the MAP scheme can improve the location privacy and enhance transmission efficiency in VANETs.

This paper proposes a new fully decentralized approach for online placement and optimization of virtual machines (VMs) for network functions virtualization (NFV). The approach is non-trivial as the virtual network functions (VNFs) constituting network services must be executed correctly in order at different VMs, coupling the optimal decisions of VMs on processing or forwarding. Leveraging Lyapunov optimization techniques, we decouple the optimal decisions by minimizing the instantaneous NFV cost in a distributed fashion, and achieve the asymptotically minimum time-average cost. We also reduce the queue length by allowing individual VMs to (un)install VNFs based on local knowledge, adapting to the network topology and the temporal and spatial variations of services. Simulations show that the proposed approach is able to reduce the time-average cost of NFV by 71% and reduce the queue length (or delay) by 74%, as compared to existing approaches.

Future fifth-generation (5G) cellular networks, equipped with energy harvesting devices, are uniquely positioned to closely interoperate with smart grid. New interoperable functionalities are discussed in stochastic two-way energy trading and online planning to improve efficiency and productivity. Challenges lie in the unavailability of a-priori knowledge on future wireless channels, energy pricing and harvesting. Lyapunov optimization techniques are utilized to address the challenges and stochastically optimize energy trading and planning. Particularly, it is able to decouple the optimization of energy trading and planning during individual time slots, hence eliminating the need for joint optimization across a large number of slots.

Decoupling network services from underlying hardware, network function virtualization (NFV) is expected to significantly improve agility and reduce network cost. However, network services, sequences of network functions, need to be processed in specific orders at specific types of virtual machines (VMs), which couples decisions of VMs on processing or routing network services. Built on a new stochastic dual gradient method, our approach suppresses the couplings, minimizes the time-average cost of NFV, stabilizes queues at VMs, and reduces the backlogs of unprocessed services through online learning and adaptation. Asymptotically optimal decisions are instantly generated at individual VMs, with a cost-delay tradeoff [ε,log2(ε)/√ε]. Numerical results show that the proposed method is able to reduce the time-average cost of NFV by 30% and reduce the queue length (or delay) by 83%, as compared to existing non-stochastic approaches.

In millimeter wave cellular communication, fast and reliable beam alignment via beam training is crucial to harvest sufficient beamforming gain for the subsequent data transmission. In this paper, we establish fundamental limits in beam-alignment performance under both the exhaustive search and the hierarchical search that adopts multi-resolution beamforming codebooks, accounting for time-domain training overhead. Specifically, we derive lower and upper bounds on the probability of misalignment for an arbitrary level in the hierarchical search, based on a single-path channel model. Using the method of large deviations, we characterize the decay rate functions of both bounds and show that the bounds coincide as the training sequence length goes large. We go on to characterize the asymptotic misalignment probability of both the hierarchical and exhaustive search, and show that the latter asymptotically outperforms the former, subject to the same training overhead and codebook resolution. We show via numerical results that this relative performance behavior holds in the non-asymptotic regime. Moreover, the exhaustive search is shown to achieve significantly higher worst case spectrum efficiency than the hierarchical search, when the pre-beamforming signal-to-noise ratio (SNR) is relatively low. This paper hence implies that the exhaustive search is more effective for users situated further from base stations, as they tend to have low SNR.

In this paper, we develop an analytical framework for the initial access (also known as base station (BS) discovery) in a millimeter-wave communication system and propose an effective strategy for transmitting the reference signals (RSs) used for BS discovery. Specifically, by formulating the problem of BS discovery at user equipments (UEs) as hypothesis tests, we derive a detector based on the generalized likelihood ratio test and characterize the statistical behavior of the detector. The theoretical results obtained allow analysis of the impact of key system parameters on the performance of BS discovery, and show that RS transmission with narrow beams may not be helpful in improving the overall BS discovery performance due to the cost of spatial scanning. Using the method of large deviations, we identify the desirable beam pattern that minimizes the average miss-discovery probability of UEs within a targeted detectable region. We then propose to transmit the RS with sequential scanning, using a pre-designed codebook with narrow and/or wide beams to approximate the desirable patterns. The proposed design allows flexible choices of the codebook sizes and the associated beam widths to better approximate the desirable patterns. Numerical results demonstrate the effectiveness of the proposed method.

Coordinated scheduling/beamforming (CS/CB) is a cost-effective coordinated multipoint (CoMP) transmission paradigm that has been incorporated in the recent long-term evolution cellular standard. In this paper, we study CS/CB with the aim of developing low-complexity multicell coordinated user scheduling policies. We focus on a class of multicell interfering broadcast networks in which base stations have only local data and local channel state information, but each has sufficient antennas to serve multiple users using zero-forcing beamforming. The coordination problem is formulated as finding scheduling decisions across the cells such that the network sum rate is maximized. Starting from the two-cell model, we uncover the structure for a good scheduling decision, which in turn leads to the definition of two distributed scheduling policies of differing complexity and intercell coordination. Asymptotic theoretical bounds on the average sum rate are derived to predict the performance of the policies proposed. We extend to some example networks containing more than two cells and develop network-wide coordination policies. Numerical results confirm the effectiveness of the proposed policies and shed light on practical coordinated system design.

With the rise of cheap small-cells in wireless cellular networks, there are new opportunities for third party providers to service local regions via sharing arrangements with traditional operators. These arrangements are highly desirable for large facilities-such as stadiums, universities, and mines-as they already need to cover property costs, and often have fiber backhaul and efficient power infrastructure. In this paper, we propose a new network sharing arrangement between large facilities and traditional operators, called a facility micronetwork. Our facility micronetwork concept consists of two aspects: leasing of core network access from traditional operators; and service agreements with users. Importantly, our incorporation of a user service agreement into the arrangement means that resource allocation must account for financial as well as physical resource constraints. We evaluate the facility micronetwork concept by analyzing the moments of the stochastic revenue process from serviced users. Using our analysis, we demonstrate the impact on the profitability of facility micronetworks based on physical layer-modeled via stochastic geometry-and financial parameters.

This work introduces a novel cooperation framework that allows mobile service providers (MSPs) to offload traffic onto each other so that temporarily unused spectrum/resources of cellular bands can be opportunistically harvested. Specifically, through traffic offloading, MSPs aim to maximize their profit while maintaining their QoS commitment. For that purpose, we model the strategic cooperation between MSPs as a stochastic Markov game in which the dynamics of MSPs' resources and user behaviors are captured by an underlying Markov decision process. We prove that the game is irreducible and admits a Nash Equilibrium at which all MSPs benefit from traffic offloading. A practical algorithm that uses only local information to govern traffic offloading at MSPs is then developed. Numerical simulations show that by designing appropriate profit sharing contracts, this algorithm can achieve almost the same performance as that of a socially optimal solution.

Generalized spatial modulation (GSM) is a variant of spatial modulation (SM) which offers enhanced spectral efficiency with a moderate increase in signal processing complexity. This paper proposes a novel compressive sensing (CS) aided detection algorithm which offers better performance than traditional CS based detection algorithms. In contrast to widely considered frequency-flat channel models, we have adopted frequency-selective wireless channel models to account for high data-rate applications. Our proposed algorithm offers superior performance over traditional CS based algorithms even in the presence of channel estimation errors. Numerical experiments are conducted to investigate the mathematical analysis under different suppositions on channel state information. Normalized mean-square error (NMSE) and bit-error rate (BER) versus signal-to-noise (SNR) curves are studied to investigate the performance under different detection algorithms.

Cooperative localization can improve both the availability and accuracy of positioning systems, and distributed belief propagation is a promising enabling technology. Difficulties with belief propagation lie in achieving high accuracy without causing high communication overhead and computational complexity. This limits its application in practical systems with mobile nodes that have limited battery size and processing capabilities. In this paper, we propose an efficient cooperative localization algorithm that can be applied to a real indoor localization system with a non-Gaussian ranging error distribution. We first propose an asymmetric double exponential ranging error model based on empirical ranging data. An efficient cooperative localization algorithm based on distributed belief propagation is then proposed. The communication and computational cost is reduced by passing approximate beliefs represented by Gaussian distributions between neighbours and by using an analytical approximation to compute peer-to-peer messages. An extension of the proposed algorithm is also proposed for tracking dynamic nodes. The proposed algorithms are validated on an indoor localization system deployed with 28 nodes covering $8000 \mbox{m}^{2} $ , and are shown to outperform existing algorithms. In particular, the fraction of nodes located to one-meter accuracy is doubled using the proposed ranging error model and localization algorithm.

In Vehicular Ad Hoc Networks (VANETs), vehicles driving along highways can be grouped into clusters to facilitate communication. The design of the clusters, e.g., size and geographical span, has significant impacts on communication quality. Such design is affected by the Media Access Control (MAC) operations at the Data Link layer, the wireless channel conditions at the Physical layer, and the mobility of the vehicles. Previous works investigated these effects separately. In this paper, we present a comprehensive analysis that integrates the three important factors into one model. In particular, we model an unsaturated VANET cluster with a Markov chain by introducing an idle state. The wireless channel fading and vehicle mobility are integrated by explicitly deriving the joint distribution of inter-vehicle distances. Closed-form expressions of network performance measures, such as packet loss probability and system throughput, are derived. Our model, validated by extensive simulations, is able to accurately characterize VANET performance. Our analysis reveals intrinsic dependencies between cluster size, vehicle speed, traffic demand, and window size, as well as their impacts on the overall throughput and packet loss of the cluster. Performance evaluation results demonstrate the practical value of the proposed model in providing guidelines for VANET design and management.

To maximize power transfer for inductively charging electric vehicles (EVs), charger and battery coils must be aligned. Wireless sensors can be installed to estimate misalignments; however, existing ranging techniques cannot satisfy the precision requirements of the misalignment estimation. We propose a high-precision wireless ranging and misalignment estimation scheme, where high precision is achieved by iteratively measuring, estimating, and aligning the coils. Another key aspect is to convert the nonconvex misalignment estimation to a more tractable problem with a convex objective. We develop a conditional gradient descent method to solve the problem, which performs gradient descent (or conditional gradient descent on the boundary of the search space) and projects out-of-boundary points back into the space. Employing experimentally validated models, we show that our scheme can achieve 92% of the efficiency of perfectly aligned coils in 90% of operations, and tolerate correlated distance measurement errors. In contrast, the prior art is susceptible to correlation, undergoing a significant efficiency degradation of 18.5%.

In this paper, we study physical layer security for the downlink of cellular networks. In a cellular network, the confidential messages transmitted to each mobile user can be eavesdropped by the other users in the same cell and also by the users in the other cells. We model the locations of base stations and mobile users as two independent two-dimensional Poisson point processes. By combining tools from stochastic geometry and random matrix theory, we analyze the secrecy rates achievable with regularized channel inversion (RCI) precoding under Rayleigh fading. Our analysis shows that unlike isolated cells, the secrecy rate in a cellular network does not grow monotonically with the transmit power. Moreover, we find that the network tends to be in secrecy outage if the transmit power grows unbounded. Furthermore, we show that there exists an optimal value for the base station deployment density that maximizes the secrecy rate.

In this paper, we consider the broadcast channel with confidential messages and eavesdroppers (BCCE), where a multi-antenna base station simultaneously communicates to multiple potentially malicious users, in the presence of external eavesdroppers randomly located according to a Poisson point process (PPP). By using techniques from stochastic geometry and random matrix theory, we obtain explicit expressions for the secrecy outage probability and mean secrecy rate achievable with regularized channel inversion precoding. We show that both these metrics scale as -4fe, where N is the number of transmit antennas and Aeis the density of external eavesdroppers.

We investigate a coordinated scheduling problem in a two-cell network where in each cell, two users are scheduled for simultaneous communication. Zero-forcing (ZF) beamforming is employed at each base station to suppress both intra- and inter-cell interference. The coordinated scheduling/beamforming problem is formulated as finding proper scheduling decisions and hence beamformers across the network such that a weighted sum-throughput is maximized. We propose three distributed scheduling policies that only require local data and local channel state information at each cell, and consume much less computation and communication overhead than the global optimization approach via exhaustive search. The proposed policies illustrate the complexity-performance tradeoff for the coordinated system. Nevertheless, numerical results show that at all levels of complexity, the proposed policies perform close to the global optimization approach with ZF beamforming and outperform the scheme with matched filtering beamforming even with global coordination.

In Vehicular Ad Hoc Networks (VANETs), vehicles along highways can be grouped into clusters. The design of VANET clusters (i.e., size and geographical span) depends on the packet collision in MAC layer, the wireless channel conditions in PHY layer, and the mobility of the vehicles. Existing works investigated these effects separately. In this paper, we present a comprehensive analysis that combines these three important factors into one model. In particular, we model an unsaturated VANET cluster with a Markov chain by introducing an idle state. The wireless channel fading and vehicle mobility are integrated by explicitly deriving the joint distribution of inter-vehicle distances. Closed-form expressions of network performance measures, i.e., packet loss probability and system throughput, are derived. The proposed analytic model, validated by simulations, is able to accurately characterize VANET performance. Our model can be applied to the design of VANET clusters, and reveals a number of insights that provide guidelines for VANETs design and management.

With high data rate and mobility support wireless networks are becoming an integral part of the ubiquitous broadband access. Appropriate dimensioning of the wireless access networks is essential to satisfy users' Quality of Service (QoS) requirements. Once the network is dimensioned, dynamic variations in traffic or population distribution can affect the capability of the network to deliver the agreed QoS of connections. Consequently, re-dimension the network may be necessary. Current researches do not discuss the effects of QoS schemes on the capacity of the network. In this paper, we investigate the impact of QoS schemes on the capacity of the network. The objective is to determine the capability of the network to deal with the variations in the demography of the covered area and the user's traffic profile with the proposed QoS schemes including Congestion Control (CC) and Radio Admission Control (RAC). Different scenarios are presented to evaluate the effects of QoS schemes on the capacity of the network. This investigation will assist network operators to determine the point after which the network needs to be re-dimensioned.

We consider a coordinated multiuser scheduling problem for a multicell mutually interfering broadcast network. In particular, we focus on a two-cell cluster, where both base stations have only local data and local channel state information, but each has sufficient number of antennas to serve multiple homogeneous users under a full zero-forcing beamforming transmission. The scheduling problem is formulated as finding proper scheduled users and hence beamformers across the cells such that the sum rate is maximized. We uncover the structure for a good scheduling decision, which in turn motivates three distributed coordinated scheduling policies of different levels of complexity. For the simplest policy, we derive a lower bound on the expected achievable sum rate. It is shown in the large user population limit, the simplest policy suffices to preserve the best possible multiplexing gain and multiuser diversity gain for the model studied, but it does induce a pairing loss on the sum rate due to the limited coordination between cells.

This paper addresses adaptive modulation and power allocation for maximizing the practicable sum capacity (sum of the uncoded throughputs of the users) of a multiuser multiple-input single-output MU-MISO) system. Since the optimal solution, dirty paper encoding (DPC), is complicated to implement, we use the simpler linear precoding based on signal- to-leakage-plus-noise ratio (SLNR). For different choices of constellation sizes, the maximum practicable sum capacities and their corresponding optimal power allocations are obtained via individual non-convex optimization. The best constellation sizes for each user are then identified through a search for the highest maximized practicable sum capacity. Simulations demonstrate the significant performance improvement from this approach compared to existing power allocation schemes. Finally, a selection procedure between different constellation sets is presented to obtain the highest practicable sum capacity while maintaining the instantaneous BER of each user below a target value. This approach allows management of the trade-off between the capacity and error performances.

With recent advances in energy harvesting technology, practical wireless nano-sensor networks (WNSNs) are coming within reach. An important aspect of these WNSNs is that the charge time is significantly longer than each sensor mote can reliably transmit its data-leading to sparse transmission requests in the time-domain. In this paper, we propose a compressed sensing-based approach for efficient request handling. We show that our scheme can achieve near contention free transmission while ensuring that each sensor mote's queue is stable. This sharply contrasts with the unstable sensor mote queues obtained using the standard round- robin approach. To guide design, we also derive closed-form expressions for the average energy consumption, which show that the average energy state of the battery increases exponentially with the transmit power.

In the cooperative multiple-input/multiple-output (MIMO), multiple access point (AP)-user links form a cluster to increase achievable throughput by cooperatively mitigating inter-user interference within the cluster. In this paper, we propose a clustered cooperative MIMO endowing a constraint on the cluster size such that the clustered MIMO can be implemented as a distributed version of downlink multiuser MIMO in existing standards with minimal modifications. New greedy algorithm and coalition formation algorithm are proposed using matching theory for establishing clusters and allocating frequencies. Simulation results shows that the proposed algorithms achieve almost 20% higher throughput than the fixed cell planning scheme, with very low searching complexity.

Virtual Multiple-Input Multiple-Output (MIMO) is a promising uplink technology that can meet the throughput demand of Long-Term Evolution-Advanced (LTE-A) systems. However, the complexity of scheduling virtual MIMO is a challenge; existing virtual MIMO is therefore limited to best effort applications. We investigate the resource allocation and scheduling problem in a heterogeneous virtual MIMO system where delay sensitive applications are present. The goal is to maximize the system throughput while maintaining delay bound for delay sensitive traffic. To tackle the complexity challenge, we propose two low-complexity suboptimal algorithms, where the key idea is to reduce the search space and iteratively minimize the rate loss respectively. Simulation results show that the rate loss minimization based heuristic algorithm converges to within 99% of the optimal throughput on average and maintains delay bound for delay sensitive users. It also achieves almost the same fairness performance as the optimal solution.

Radio Admission Control (RAC) is a key function of the Radio Resource Management (RRM) at layer 3 of an eNodeB; however, the 3GPP standard does not specify the RAC and is left as an eNodeB vendor specific. Most admission control schemes proposed to date do not ensure differentiation among the users at different priority levels. Also, they do not provide fairness among the users with the same priority. This paper proposes a novel RAC scheme for Long Term Evolution (LTE-Advanced) networks based on the combined idea of complete sharing and virtual partitioning. It introduces a step wise degradation scheme, to prioritize the high priority traffic in state of resource limitations. A detailed and comprehensive simulation is performed in Opnet to show the efficiency of the proposed RAC scheme. The simulation results demonstrate that the proposed RAC scheme minimizes the call blocking probability and adheres extremely well to the bandwidth constraints of different traffic types.

In this paper, we study physical layer security for the downlink of cellular networks, where the confidential messages transmitted to each mobile user can be eavesdropped by both (i) the other users in the same cell and (ii) the users in the other cells. The locations of base stations and mobile users are modeled as two independent two-dimensional Poisson point processes. Using the proposed model, we analyze the secrecy rates achievable by regularized channel inversion (RCI) precoding by performing a large-system analysis that combines tools from stochastic geometry and random matrix theory. We obtain approximations for the probability of secrecy outage and the mean secrecy rate, and characterize regimes where RCI precoding achieves a nonzero secrecy rate. We find that unlike isolated cells, the secrecy rate in a cellular network does not grow monotonically with the transmit power, and the network tends to be in secrecy outage if the transmit power grows unbounded. Furthermore, we show that there is an optimal value for the base station deployment density that maximizes the secrecy rate, and this value is a decreasing function of the signal-to-noise ratio.

In this paper, we propose clustered quantization techniques for multiuser multi-input/multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) using constellation based codebooks. Constellation based codebooks provide scalability and efficient codeword search capability, which are key features for practical multiuser MIMO-OFDM systems with a large number of antennas. The proposed clustered quantization scheme quantizes consecutive subcarriers into a single codeword that minimizes aggregated quantization errors. We base our new clustering techniques on two constellation based quantization methods, namely equal-magnitude angular quantization (EMAQ) and squared-lattice angular quantization. New efficient codebook search algorithms are proposed for the clustered quantization. In addition, we propose new constellations to guarantee different users quantize channels into distinct codewords. One is a rotated M-PSK constellation suitable for randomly-distributed user scenarios, and the other is a random phase equal-magnitude (RPEM) constellation suitable for ill-conditioned user scenarios. Thus, full spatial multiplexing gain can be achievable even with small number of users. Finally, a near-sphere codeword search algorithm is proposed for the RPEM. In simulations, the proposed clustered quantization shows up to 50% higher throughput compared to conventional fixed-pilot channel quantization. Also, we show our new constellations for EMAQ improve throughput almost 35% compared to the standard EMAQ.

Relays enabled with multiuser MIMO techniques have great potential to mining vehicle safety applications. However, they are yet to be practical due to high scheduling overhead in mobile, radio-unfriendly, mining environments. A new decentralized relay-assisted multiuser MIMO approach is proposed, which cuts the overhead by 80% and enables relay-assisted multiuser MIMO to be implemented in practice. This approach is a new distributed participatory downlink transmission method, where both the relays and destinations participate in the scheduling decisions. A new recursive algorithm is also developed to optimally quantize the channel conditions of the vehicles, thereby minimizing the feedback requirement. Analytical results, confirmed by simulations, show that the proposed approach is able to achieve 97.6% of the sum-rate upper bound of the network, using only three bits to characterize the channel condition of each vehicle. In terms of throughput, the proposed decentralized scheme can perform 45.2% better than the existing centralized scheme. The proposed approach is compatible with industrial communication standards and can be implemented with commercial industrial communication systems.

In this paper, we consider the broadcast channel with confidential messages and external eavesdroppers (BCCE), where a multi-antenna base station simultaneously communicates to multiple potentially malicious users, in the presence of randomly located external eavesdroppers. Using the proposed model, we study the secrecy rates achievable with regularized channel inversion (RCI) precoding by performing a large-system analysis that combines results from stochastic geometry and random matrix theory, where the number of users K and the number of transmit antennas N both grow to infinity in a fixed ratio. We obtain explicit expressions for the probability of secrecy outage and an upper bound on the rate loss due to the presence of external eavesdroppers. We show that both these quantities scale as \fraclambda_esqrt{N} as the density of external eavesdroppers λ_e grows, irrespective of their collusion strategy. Furthermore, we derive a practical rule for the choice of the regularization parameter, which is agnostic of channel state information and location of eavesdroppers, and yet provides close to optimal performance.

Large scale deployment of machine-to-machine (M2M) communication networks hinges on the cost and energy efficient design of the embedded devices. Standard WLAN power save mechanisms, which are designed for human communications, experience performance degradation and unbalanced energy consumptions in M2M communication networks. We develop a novel analytical model that takes into account the fundamentally different network architecture and traffic patterns of M2M communications. Our model accurately characterizes the high contention and long packet delay found in M2M communication networks, while previous models underestimate such measures. To combat such performance decline, we propose a new algorithm that enhances existing power save mechanisms to extend the lifetime of a M2M communication network. We call this the Offset ListenInterval (OLi) Algorithm. The OLi algorithm spreads the M2M traffic evenly with calculated offsets to alleviate network contention and reduce packet delay. Our analytical model is then used to evaluate the energy efficiency of our OLi algorithm and compare with the standard power save mechanisms. Our results show that the proposed OLi algorithm extends the lifetime by up to 40%, and scales up to thousands of nodes in a M2M communication network.

Bandwidth-demanding mobile video applications are becoming increasingly popular in wireless networks, leading to a relentless growth in the demand for wireless throughput and quality of service (QoS). Multiuser Multiple-Input Multiple-Output (MIMO) has great potential to meet the growth of wireless throughput. However, this advancement in physical-layer technologies does not necessarily translate into better QoS for the applications, unless the design principles and operating protocols at the higher layers of the networking stack are adapted accordingly to fully capture this potential. We propose a new scheduling algorithm, which selects mobile users to form multiuser MIMO based on the priorities we carefully design to leverage the demands of wireless throughput and video quality. We also develop a new computationally efficient parallel technique to calculate the priorities precisely, which allows the users to be selected in a computationally effective way. Analyses and simulations show that the proposed scheme allows video applications to achieve close to the throughput upper bound of multiuser MIMO. Our scheme also improves the video quality by reducing the loss of video enhancement packets by an order of magnitude and by reducing the delay by 35%, compared to the state of the art.

The design of a reliable physical-layer network coding (PNC) scheme for practical fading two-way relay channels is a challenging task. This is because the signals transmitted by two users arrive at the relay with varied amplitudes and a relative carrier-phase offset, which will impair the performance of PNC. This paper studies a linear PNC scheme for fading two-way relay channels where the transmitters lack the channel state information. In this scheme, the relay computes and broadcast some finite-set integer combinations of two users' messages. The coefficients for the integer combinations used at the relay are carefully designed to minimize the error probability. This scheme can be viewed as a practical embodiment of the compute-and-forward concept. We develop a new LPNC design criterion called minimum set-distance maximization. Using this criterion, we derive an explicit expression for the optimized integer coefficients that minimizes the error probability of LPNC. The optimized integer coefficients turn out to resemble the fading channel coefficients. We further derive a closed-form expression on the average error probability performance over a complex-valued Rayleigh fading two-way relay channel, which shows that our designed LPNC scheme approaches the optimal error performance at a high SNR. Numerical results show that our designed LPNC outperforms existing schemes by more than 5 dB at a medium-to-high SNR regime.

In this paper, we study the performance of regularized channel inversion precoding in MISO broadcast channels with confidential messages under imperfect channel state information at the transmitter (CSIT). We obtain an approximation for the achievable secrecy sum-rate which is almost surely exact as the number of transmit antennas and the number of users grow to infinity in a fixed ratio. Simulations prove this anaylsis accurate even for finite-size systems. For FDD systems, we determine how the CSIT error must scale with the SNR, and we derive the number of feedback bits required to ensure a constant high-SNR rate gap to the case with perfect CSIT. For TDD systems, we study the optimum amount of channel training that maximizes the high-SNR secrecy sum-rate.

Communication is an enabling technology for the efficient control and management of next-generation Smart Grids. Energy conservation of the communication devices is essential for future large scale deployment of Smart Grid communication networks. However, existing power save protocols experience high contention in Smart Grid communication networks that have a large number of nodes and periodic traffic. We design a new energy conservation protocol, Power Save with Offset Listen Interval (PS-OLi), to address such contention problems. PS-OLi avoids message collisions by controlling the station wake up time with a calculated offset. A new analytical model is developed to characterize the power save performance of networks with periodic traffic. Simulation results show that our analytical model accurately predicts the collision probability and packet delay. We use our model to evaluate the energy efficiency of PS-OLi and standard power save protocols. Our results show that PS-OLi extends the lifetime of a Smart Grid communication network by more than 10%.

We develop a novel approach for estimation and inference of spatial field defined over a two-dimensional space under quantized and imperfect channels communication constraints in wireless sensor networks. The objective is to derive an efficient solution for spatial intensity and exceedance estimation. The algorithm developed is based on a series expansion approach in which the first order is the familiar Laplace approximation utilising a Gaussian basis. We illustrate the efficiency of our approach through extensive simulations.

We investigate a linear physical-layer network coding (LPNC) scheme for fading two-way relay channels, where the transmitters cannot track the channel. In this scheme, the relay computes and forwards integer combinations of the two users' messages. We develop a design criterion for adaptively choosing the integer coefficients at the relay, which minimizes the high-SNR error probability of the LPNC scheme. We derive an explicit expression for the optimized integer coefficients, and show that the crucial factor is the ratio between the two users' fading channel coefficients. We also extend the LPNC scheme to the complex-valued model and derive the optimized integer coefficient vectors. Numerical results show that our designed LPNC scheme outperforms existing schemes by more than 5 dB.

Existing mobile video applications are continuously driving up the demand for throughput and better quality of service (QoS) for future Long Term Evolution-Advanced (LTE-A) networks. Multi-User Multiple-Input Multiple-Output (MU-MIMO) is one of the most promising technologies that would meet the throughput demand. Unfortunately, existing MU-MIMO schemes do not consider metrics such as delay, and therefore, cannot meet the QoS requirement of delay sensitive applications, such as mobile video. We propose a new cross-layer MU-MIMO scheduling algorithm, which is referred to as joint channel and delay aware user scheduling (CDAUS), satisfies both the throughput and delay requirements. The key idea of the CDAUS algorithm is to select users to form MU-MIMO based on the delay requirements of individual users, as well as their channel correlations. The priority of the users is carefully designed to leverage their delay and throughput. Simulation results show that the proposed CDAUS algorithm is able to reduce the average delay by up to 30% with a marginal 2% sacrifice of throughput, compared to previous work. It also reduces delay variations and improves fairness among the users.

Coordinated multipoint (CoMP) is an interference mitigation technique in LTE release 10, which exploits base station (BS) cooperation to improve throughput for cell-edge users. An important new feature present in CoMP is that variable numbers of BSs can service a given user. This poses a new problem for beamforming that is not present in single-cell operation: the quantization codebook must support a variable dimension codebooks, with the dimension corresponding to the number of BSs employed. This is a problem that has not appeared in previous releases of LTE. In this paper, we propose a low complexity structured codebook that has linear complexity in both the codebook size and dimension. As such, the variable dimension codebooks are readily accommodated and the codebook can be constructed online as the number of transmitting BSs varies. We also propose a new method to store optimal structured codebooks-in the sense of the Grassmannian criterion-of variable dimension by exploiting properties of the combinatorial designs known as cyclic difference sets. Although the size of the optimal codebooks is limited, our method reduces storage requirements as subsets of the same parameters are used to construct the codebook for each dimension. We show via simulations that our low complexity codebook construction performs comparably with the standard Fourier codebook obtained using an exhaustive search, with only linear complexity in both size and dimension.

We propose a base station (BS) cooperation scheme for heterogeneous wireless cellular networks, with multiple small-cells overlaid on top of a macrocell network. Our scheme can guarantee that each BS's queue is stable, while satisfying minimum signal-to-interference and noise ratio (SINR) targets. We achieve queue stability by employing a stochastic scheduling technique, where the realizations of tuned random variables determine whether each BS transmits, in addition to the minimum SINR target. We develop a new algorithm to tune the random variables in our proposed scheme, which approximately maximizes the probability that each BS transmits-to reduce queue lengths-subject to the constraint that each BS's queue is stable. In particular, we approximate the non-convex signomial optimization problem arising from the queue stability constraints as a convex optimization problem. We demonstrate that our scheme can achieve queue stability at each BS, even when BS queues are unstable for the standard fractional frequency reuse scheme.

We develop a novel approach to source localization in mobile wireless sensor networks. Standard approaches make explicit assumptions relating to the statistical characteristics of the physical process and propagation environments which result from distributional model assumptions in a likelihood-based inference method. In contrast, we adopt an approach known in statistics as a non-parametric modeling framework which allows one to relax the number of required statistical assumptions, specifically with regard to the distributional properties of the received signal and the physical process. This is achieved via a re-formulation of the problem as a flexible non-parametric regression model via the framework of Gaussian Processes. Coupling this modeling perspective with a Bayesian optimization mechanism, we frame the global optimization objective as a sequential decision problem. We then develop an efficient algorithm to sequentially select the optimal location at which the mobile sensor should obtain observations under communication and mobility constraints. Simulation results demonstrate the efficiency of the algorithm at achieving accurate localization in a wireless sensor network.

Coordinated Multi-Point (CoMP) for Long Term Evolution Advanced (LTE-A) systems refers to a range of techniques to increase the capacity averaged over the cell, and also at the cell edge where the path loss is usually highest. In this paper, the problem of power allocation is first addressed for maximizing the sum capacity at each point of the coverage area in a CoMP multi-user downlink. Then, based on targeting the minimum value of the maximized sum capacity, a design approach is presented for obtaining an optimal size of the cells in a wireless network. The approach guarantees that the sum capacity at each point of the coverage area is above the target value. The path loss model is pivotal for the outcome of this type of performance analysis and the ensuing system design. Here, a simplistic, standard path loss model is used, but the approach can use other models.

Coordinated multipoint (CoMP) is a base station (BS) cooperation technique to boost the signal-to-noise ratio (SNR) of cell-edge users in future generation wireless networks. We propose a fixed weight CoMP downlink scheduler to reduce the packet loss probability (PLP) due to buffer overflow in BSs with finite queues. The CoMP scheduler selects a single BS to serve the associated cell-edge user with the largest weighted SNR. To meet PLP targets, we develop a simple strategy to design the packet transmission time and the scheduling weights of each BS. The network design capitalizes on our new closed-form expression for the PLP that relates three key network parameters: packet arrival rate, packet transmission time, and probability that each BS is scheduled. We compare the proposed fixed weight scheduler with an adaptive weight scheduler that requires instantaneous packet delay information. We show via analysis and simulation that the fixed weight scheduler can achieve a comparable PLP to the adaptive weight scheduler, while reducing communication overheads for the BSs.

In this paper, we study the performance of regularized channel inversion (RCI) precoding in large MISO broadcast channels with confidential messages (BCC). We obtain a deterministic approximation for the achievable secrecy sum-rate which is almost surely exact as the number of transmit antennas M and the number of users K grow to infinity in a fixed ratio β=K/M. We derive the optimal regularization parameter ξ and the optimal network load β that maximize the per-antenna secrecy sum-rate. We then propose a linear precoder based on RCI and power reduction (RCI-PR) that significantly increases the high-SNR secrecy sum-rate for 1<;β<;2. Our proposed precoder achieves a per-user secrecy rate which has the same high-SNR scaling factor as both the following upper bounds: (i) the rate of the optimum RCI precoder without secrecy requirements, and (ii) the secrecy capacity of a single-user system without interference. Furthermore, we obtain a deterministic approximation for the secrecy sum-rate achievable by RCI precoding in the presence of channel state information (CSI) error. We also analyze the performance of our proposed RCI-PR precoder with CSI error, and we determine how the error must scale with the SNR in order to maintain a given rate gap to the case with perfect CSI.

Small cells are an emerging approach to improving hotspots throughput in cellular networks. Unfortunately, they cannot be deployed in a large scale under current cellular architectures, because of a severe interference problem and inefficient use of spectrum. We propose a new small-cell architecture which reconfigures topologies and frequency bands, adapting to changing traffic demands and interference-mitigating requirements. The new architecture consists of distributed small-cell nodes (SCN) and co-located baseband units (BBU), and adaptively switches the connections between the SCNs and BBUs. The BBUs can even be shared among multiple SCNs that use different frequency bands. Our architecture requires fewer BBUs, and the spectrum and energy utilization is significantly more efficient compared with current architectures. Simulations show that the new architecture is able to increase the spectrum utilization by 23.5%, and improve the network satisfaction regarding traffic demands by 144.2% for small cells covering 0.5 km2. Our architecture can also reduce the investment and energy consumption of the BBUs by up to 40%.

In practical radio transmissions, bit error and channel capture are two dominating factors that affect wireless network performance. Previous models have omitted the interaction between bit error and channel capture. We present a homogeneous-network performance-prediction model for a Rayleigh fading channel that incorporates both the capture effect and transmission error into a 3-D Markov Chain. We accurately characterise the interaction between packet error and capture by incorporating them both into the model of the receiver operations. We show how the model can be solved efficiently. The model provides quality of service measures, including packet delay and loss, which are difficult to achieve with other models. Simulation results confirm that our 3-D model accurately predicts the performance for practical SNRs and receiver sensitivities. We demonstrate that our model can be directly applied to call admission control of Voice over IP service with a QoS guarantee in a WiFi network. The model is then extended to heterogeneous networks, where different stations have different packet arrival rates and packet sizes.

We propose and analyze transmit antenna selection (TAS) to enhance physical layer security in a wiretap channel with NAantennas at the transmitter, NBantennas at the receiver, and NEantennas at the eavesdropper. We focus on the practical scenario where the transmitter does not have any channel state information (CSI) of the eavesdropper's channel. The transmitter selects a single antenna that maximizes the instantaneous signal-to-noise ratio (SNR) at the receiver. The receiver and the eavesdropper employ either maximal-ratio combining (MRC) or selection combining (SC) to combine the received signals. For the proposed protocols, we derive new closed-form expressions for the probability of non-zero secrecy capacity. We consider Nakagami-m fading with non-identical fading parameters of the main channel, mB, and of the eavesdropper's channel, mE. Next, we derive new closed-form expressions for the exact secrecy outage probability, based on which the ε-outage secrecy capacity is characterized. Based on the exact expressions, we derive the asymptotic secrecy outage probability which accurately reveals the secrecy diversity order and the secrecy array gain. We confirm that the proposed protocols achieve identical secrecy diversity orders of NANBmB. An interesting conclusion is reached that this diversity order is independent of NEand mE. Furthermore, we prove that under the proposed protocols, the secrecy outage probability and the ε-outage secrecy capacity improve with increasing NA.

We investigate efficient communication over multiple-input multiple-output (MIMO) two-way relay channels (TWRCs), where two multi-antenna users exchange information via a multi-antenna relay. We propose a new MIMO physical-layer network coding (PNC) scheme that includes novel eigen-direction alignment (EDA) precoding. The proposed EDA precoding efficiently aligns the two-user's eigen-modes into the same set of orthogonal directions, and multiple independent PNC streams are implemented over the aligned eigen-modes. We derive an achievable rate-pair of the proposed scheme, for given EDA precoding parameters, over a MIMO TWRC. To maximize the achievable rate-region, we formulate a design criterion for the EDA precoding parameters, and present solutions to the formulation. Closed-form bounds on the sum-rates of the designed EDA-PNC schemes are derived. Numerical results show that there is only a small gap between the achievable rate of the proposed scheme and the capacity upper bound of the MIMO TWRC. It is shown that the proposed scheme can significantly outperforms existing schemes in the literature.

We analyze the impact of antenna correlation on secrecy performance of multiple-input multiple-output wiretap channels where transmitter employs transmit antenna selection while receiver and eavesdropper perform maximal-ratio combining with arbitrary correlation. New closed-form expressions are derived for the exact and asymptotic (high signal-to-noise ratio in transmitter-receiver channel) secrecy outage probability.

We propose a novel space-division-based network-coding scheme for multiple-input multiple-output (MIMO) two-way relay channels (TWRCs), in which two multiantenna users exchange information via a multiantenna relay. In the proposed scheme, the overall signal space at the relay is divided into two subspaces. In one subspace, the spatial streams of the two users have nearly orthogonal directions and are completely decoded at the relay. In the other subspace, the signal directions of the two users are nearly parallel, and linear functions of the spatial streams are computed at the relay, following the principle of physical-layer network coding. Based on the recovered messages and message-functions, the relay generates and forwards network-coded messages to the two users. We show that, at high signal-to-noise ratio, the proposed scheme achieves the asymptotic sum-rate capacity of the MIMO TWRC within [ 1/ 2]log(5/4) ≈ 0.161 bits per user-antenna, for any antenna configuration and any channel realization. We perform large-system analysis to derive the average sum-rate of the proposed scheme over Rayleigh-fading MIMO TWRCs. We show that the average asymptotic sum-rate gap to the capacity is at most 0.053 bits per relay-antenna. It is demonstrated that the proposed scheme significantly outperforms the existing schemes.

A key component of multiuser MIMO using zero-forcing precoding is the feedback of quantized channel state information to the base station. A problem arises when each user has a common codebook as the quantized channels can form a singular matrix that results in a reduced sum-rate. In this paper, we propose two new structured constructions to generate different codebooks at each user via transformations of a base codebook. The first construction is based on the Householder transform, which is used to construct a different codebook at each user for most types of base codebooks, with no storage in addition to the base codebook. A feature of our first construction is that the transformed codebook using the Fourier base codebook has a search complexity reduction of up to 50% compared to the standard approach, although only one additional unique codebook can be constructed with this type of base codebook. To construct multiple different codebooks using the Fourier base codebook, we propose a second construction that is based on the representation theory of groups. We show that both our constructions significantly reduce storage requirements compared with the intuitive but impractical random construction, while obtaining the same sum-rate performance. In particular, we only require elements generated directly from the base codebook or from finite fields, instead of random complex numbers.

We propose a new scheduler for wireless multimedia relay networks (WMRNs). Our scheduler is designed to account for delay, symbol error probability (SEP), and packet loss probability (PLP) due to buffer overflow. We develop a cross-layer scheduling approach for the downlink to balance these system metrics. Our scheduler is based on a new metric which is referred to as the delay in packet scheduling (DPS). The user with the largest weighted signal-to-noise ratio is scheduled, where the weight is a function of the DPS. We then derive analytical expressions for the probability mass function (PMF) of the DPS, and the SEP of the scheduled user in Rayleigh fading. We derive an analytical approximation for the PMF of the buffer state. An analytical expression is then derived for the PLP due to buffer overflow. Our analysis is verified via simulations. We show the probability that a target DPS is met is 30% higher for our new scheme compared to the standard opportunistic equal weight scheduler, with negligible degradation in the SEP of the scheduled user. This can lead to a 85% improvement in the PLP.

The authors of the above titled paper (ibid., vol. 9, no. 8, pp. 2664-2675, Aug. 2010), have become aware that several of the equations in that paper were presented with errors. In this brief, we provide correct equations. The implementation of the model in the original paper was in accordance with the correct equations, so the implementation results presented in Section V. Performance Analysis are still valid.

Small cells with wireless backhaul are promising, whereas challenges of severe overlapping coverage and strong interference are yet to be addressed. Coordinating small cells could resolve the challenges; however, existing multicell coordinated beamforming techniques involve high cost of communication overhead, synchronization and backhaul. Such problems may deteriorate in practical cellular applications, where there could be many users, each generating high channel feedback overhead to compete for an opportunity of being scheduled, and the downlink data signals of the coordinated cells need to be precisely synchronized at each of the users. We propose a new scheme, which cuts the overhead by 80% and enables the coordination to be practically implemented in a decentralized manner. Our scheme is a user-centric downlink scheduling approach, where mobile terminals trigger and participate in the scheduling decisions of small cells. We also develop a new recursive algorithm to optimize the quantization levels of mobile terminals' feedback, minimizing the feedback requirement. Analysis, confirmed by simulations, shows that our scheme is able to achieve 94.4% of the sum-rate upper-bound which can only be approached by idealized centralized coordination. In terms of throughput, given the 80% reduced overhead, our scheme is 139.5% better than the idealized centralized coordination approach.

We propose and analyze transmit antenna selection (TAS) to enhance physical layer security in a wiretap channel with multiple antennas at the transmitter, the receiver, and the eavesdropper. We consider the practical scenario of passive eavesdropping, where the transmitter does not have any channel state information (CSI) of the eavesdropper's channel. In the main channel between the transmitter and the receiver, we select a single antenna at the transmitter that maximizes the instantaneous signal-to-noise ratio (SNR) at the receiver. At the receiver and the eavesdropper, we consider two combining techniques: 1) maximal-ratio combining (MRC) and 2) selection combining (SC). For non-identical Rayleigh fading between the main channel and the eavesdropper's channel, we first derive new closed-form expressions for the exact and asymptotic secrecy outage probabilities. The asymptotic results accurately reveal the secrecy diversity order and the secrecy array gain. Next, we derive new closed-form expressions for the probability of positive secrecy and characterize the ε-outage secrecy capacity. We show that, under TAS/MRC and TAS/SC protocols, the secrecy outage probability approaches zero and the ε-outage secrecy capacity increases with increasing number of transmitter antennas.

Metro cells are an emerging solution to improving hotspots throughput in cellular networks. Unfortunately, they cannot be deployed in a large scale under current cellular networks because of a severe interference problem. We propose a new metro-cell base station control switch (BSCS) which reconfigures topologies and frequency bands adapting to changing traffic demands. The new BSCS connects distributed metro-cell nodes (MCN) and collocated baseband units (BBU), and is able to adaptively switches the connections. As a result, fewer BBUs are required, and frequency utilization is significantly more efficient compared with current networks. Simulations show that our BSCS is able to improve network satisfaction regarding traffic demands by 144.2% and reduce BBU cost by 40% in a metro-cell network covering 0.5 km2.

Cooperative multiplexing has the potential to double the achievable throughput by allowing the base station (BS) and the relay station (RS) to transmit to different users at the same time in the second time slot of the half time division duplexed (TDD) relay transmission. This throughput improvement comes at a cost of performance degradation due to inter-user interference between the BS and the RS. To overcome this degradation, we propose cooperative multiplexing optimum combining (CMOC) for the relay-link users. The proposed CMOC receiver combines the signals in the first and second time slot of the half TDD transmission such that the output signal-to-interference-plus-noise ratio (SINR) is maximized. New insights are drawn from our exact closed-form expressions of SINR distributions. Based on these, we present new analytical expressions for the outage probability, symbol error rate, and achievable throughput. Our results show a 3.5 times improvement in the achievable throughput relative to the standard single-channel receiver in the high interference regime.

Multi-user multiple-input multiple-output (MU-MIMO) has a potential to realize cost effective high data rate internet access to the homes in rural areas. We propose the novel Ngara Access system where the central access point (AP) is equipped with a uniform circular array (UCA) installed on a high tower while each UT is equipped with a directional antenna free of clutter, providing predominantly line-of-sight (LoS) channel environment. Using a three dimensional geometric optics based channel model, we provide bit error probability simulation results which show that the spectral efficiency of the proposed system can be improved linearly as a function of the number of antenna elements at AP, without increasing the total transmitting power, provided a half wavelength antenna spacing is maintained and user groups of four or more are used to avoid ill-conditioned channel. Hardware demonstrators based on the proposed system have achieved the system spectral efficiency of 20 bits/s/Hz in an actual rural environment and of 67 bits/s/Hz in a laboratory environment at a lower UHF band.

We propose a new reduced-dimension (RD) eigen-direction alignment (EDA) precoder for MIMO two-way relay channels (TWRCs) with nR>; nT, where nRdenotes the number of antennas at the relay, and nTis that at each of the two users. The RD-EDA precoder can efficiently create aligned eigen-modes for the two users, enabling independent streams of physical-layer network coding. We investigate the design of the RD-EDA and develop a simple suboptimal solution. It is shown that the proposed RD-EDA scheme performs close to the sum-capacity upper bound of the MIMO TWRC. Moreover, it is shown that the proposed scheme can significantly outperform other existing schemes in the literature.

In this paper, we consider a channel quantization problem that selects the best codeword representing a group of consecutive subcarriers (cluster) in multiuser MIMO-OFDM systems. The clustering is required to reduce the amount of feedback information in practical OFDM systems. Based on M-PSK based codebooks, we propose a new codeword search algorithm for the clustered MIMO-OFDM with complexity of O(2NT) compared to the complexity of O(MNT) for conventional exhaustive search, where NTdenotes the number of transmit antennas. Through simulations, the proposed clustered codeword selection scheme for the multiuser MIMO-OFDM shows up to 54% performance improvement in throughput compared with the conventional MIMO-OFDM system that performs the channel quantization only on predetermined pilot subcarriers.

We propose and analyze two MIMO protocols with analog network coding (ANC) in two-way amplify-and-forward (AF) relaying where multi-antenna nodes communicate via a single antenna relay. Specifically, we present a new framework for the comparative analysis of beamforming and antenna selection in two-way relaying with non-identical Rayleigh fading between the hops. To facilitate the comparison, we derive new closed-form expressions for the exact and asymptotic sum symbol error rate (SSER). We show that beamforming and antenna selection offer the same diversity order of min{NA, NB}, where NA and NB are the number of antennas at the two nodes. We proceed to characterize the fundamental difference between the two protocols in terms of their array gains. A pivotal conclusion is reached that when either of the two nodes is equipped with a single antenna, antenna selection provides identical performance to beamforming at medium and high signal-to-noise ratios without the added hardware and signaling overhead.

In this paper, we study the performance of the Regularized Channel Inversion (RCI) precoder in a multi-user MIMO system with malicious users. We consider the general case when the number of users per transmit antenna β can take any value. We derive the optimal regularization parameter that maximizes the achievable secrecy sum-rate via large-system analysis, which we show to be accurate via simulations. We find that the secrecy requirements limit the number of users per transmit antenna that can be served with non-zero sum-rate. We show that for large signal-to-noise ratio, RCI can achieve secrecy without reducing the sum-rate if β; 1, then the secrecy requirements result in a poor sum-rate.

We present a flexible class of stochastic models that are developed for cooperative wireless relay networks systems, in which the relay processing functionality is not known at the destination. The challenge is then to perform system identification in this wireless relay network. We first construct a statistical model based on a representation of the system using Gaussian Processes. We then develop a computationally efficient algorithm which is based on the Iterated Conditioning on the Modes estimation to undertake system identification for each relay in the presence of partial Channel State Information (CSI). We evaluate the identification performance for different non-linear relay functionalities.

In this paper, we propose a linear precoder for the downlink of a multi-user MIMO system with multiple users that potentially act as eavesdroppers. The proposed precoder is based on regularized channel inversion (RCI) with a regularization parameter α and power allocation vector chosen in such a way that the achievable secrecy sum-rate is maximized. We consider the worst-case scenario for the multi-user MIMO system, where the transmitter assumes users cooperate to eavesdrop on other users. We derive the achievable secrecy sum-rate and obtain the closed-form expression for the optimal regularization parameter αLSof the precoder using large-system analysis. We show that the RCI precoder with αLSoutperforms several other linear precoding schemes, and it achieves a secrecy sum-rate that has same scaling factor as the sum-rate achieved by the optimum RCI precoder without secrecy requirements. We propose a power allocation algorithm to maximize the secrecy sum-rate for fixed α. We then extend our algorithm to maximize the secrecy sum-rate by jointly optimizing α and the power allocation vector. The jointly optimized precoder outperforms RCI with αLSand equal power allocation by up to 20 percent at practical values of the signal-to-noise ratio and for 4 users and 4 transmit antennas.

We develop a general framework for the analysis of a broad class of point-to-point linear multiple-input multiple-output (MIMO) transmission schemes in decentralized wireless ad hoc networks. New general closed-form expressions are derived for the outage probability, throughput and transmission capacity. For the throughput, we investigate the optimal number of data streams in various asymptotic regimes, which is shown to be dependent on different network parameters. For the transmission capacity, we prove that it scales linearly with the number of antennas, provided that the number of data streams also scales linearly with the number of antennas, in addition to meeting some mild technical conditions. We also characterize the optimal number of data streams for maximizing the transmission capacity. To make our discussion concrete, we apply our general framework to investigate three popular MIMO schemes, each requiring different levels of feedback. In particular, we consider eigenmode selection with MIMO singular value decomposition, multiple transmit antenna selection, and open-loop spatial multiplexing. Our analysis of these schemes reveals that significant performance gains are achieved by utilizing feedback under a range of network conditions.

We investigate efficient communications over MIMO two-way relay channels (TWRCs) of nTR, where nTdenotes the number of antennas at each user and nRdenotes that at the relay. We propose a new reduced-dimension (RD) cooperative precoding scheme. In the proposed scheme, the two users cooperatively create nTaligned eigen-modes, supporting nTstreams of physical-layer network coding. We investigate the design of the RD cooperative precoder and derive an asymptotically optimal solution. We analytically show that, in the worst case, the proposed scheme is within ½ bit per transmit antenna of the asymptotic sum-capacity of the MIMO TWRC. For fading MIMO TWRCs with i.i.d. Gaussian coefficients, we derive a closed-form expression of the average sum-rate of the proposed scheme using large system analysis. Our analytical result shows that, for a large system with nT/nR= ½, the proposed scheme is less than 0.16 bit per transmit antenna away from the capacity. Furthermore, this gap reduces as nT/nRincreases, and vanishes as nT/nRtends to 1. It is demonstrated that the proposed scheme can significantly outperform other existing schemes in the literature.

We propose cascaded transmit antenna selection with maximal-ratio combining (TAS/MRC) for use in multiuser relay networks (MRN) with NS, NR, and NDantennas at the source, the relay, and each of the K destinations, respectively. We consider opportunistic scheduling where the destination with the highest instantaneous end-to-end signal-to-noise ratio (SNR) is scheduled for transmission. In cascaded TAS/MRC, a single transmit antenna that maximizes the instantaneous received SNR in each hop is selected, and all the receive antennas are MRC combined. We derive new exact closed-form statistics of the end-to-end SNR, from which we derive the exact and the approximate symbol error rate (SER) for M-ary quadrature amplitude modulation (M-QAM) and M-ary phase-shift keying (M-PSK). New concise expressions are derived to characterize the diversity order and the array gain. We highlight that our proposed scheme attains the maximum diversity order of NR× min{NS, NDK}. Furthermore, we determine the optimal power assignment at the source and the relay that minimizes the SER.

We present a novel codebook design criterion for the limited feedback MIMO broadcast channel with zero-forcing precoding. To reduce system implementation complexity, each user has the same codebook. We derive a new sum-rate bound, show the bound maximization problem is invex and explicitly solve it using the Karush-Kuhn-Tucker (KKT) conditions. We show that the solution has the same structure as Grassmannian frames. We also derive a new lower bound on the outage probability. We show via simulations that our codebooks designed using Grassmannian frames outperform random vector quantization with different codebooks at each user for codebook sizes greater than 9 bits.

We propose transmit antenna selection with maximal-ratio combining (TAS/MRC) for use in multiple-input-multiple-output (MIMO) multiuser relay networks (MRN). The network under consideration is equipped with NS, NR, and NDantennas at the source, the relay, and each of the K destinations, respectively. For this network, the destination with the highest instantaneous end-to-end signal-to-noise ratio (SNR) is scheduled for transmission. In each hop, a single transmit antenna that maximizes the post-processing SNR is selected, while all the receive antennas are MRC combined. We first derive new closed-form expressions for the outage probability and the symbol error rate (SER) for amplify-and-forward (AaF) relaying. Next, we present compact and easy-to-compute expressions for the diversity order and the array gain to provide practical insights into the network behavior. We highlight the fact that our proposed scheme attains the maximum diversity order of NR× min{NS,NDK}.

In this paper, we present a novel user selection scheme for the broadcast channel (BC) using zero-forcing (ZF) precoding with optimal power control. Our scheme is based on a threshold that sets a minimum acceptable sum-rate. In order to design the threshold, we develop a new approximation of the sum-rate and derive simple design rules for the threshold with complexity constraints. We also extend the scheme so that users with differing quality of service (QoS) demands can be accommodated. Simulations show our scheme performs close to the exhaustive search algorithm, but with significantly reduced complexity. Moreover, it significantly reduces the outages compared to non-threshold based low complexity scheduling schemes.

We consider the impacts of channel fading on the quality of service (QoS) performance of the IEEE 802.11 system. Traditional 2-D Markov chain models, while suitable for throughput analysis, are unable to capture the QoS performance due to the lack of a proper queueing model. We present a 3-D Markov chain queueing model that incorporates channel fading effects and solve the Markov chain efficiently with our Collapsed Transition onto Basis approach. In doing so, we are able to investigate important QoS measures, packet delay and loss, as well as throughput, for a 802.11 system under practical channel fading conditions. The analytical results are validated by extensive simulations. Our 3-D model offers new insights in channel fading effects on system capacity and QoS performance. We demonstrate that our 3-D model can also be used to provides guidelines for traffic control.

The performance of spatial multiplexing systems with linear minimum-mean-squared-error receivers is investigated in ad hoc networks. We present new exact closed-form expressions for the outage probability and transmission capacity. These expressions reveal that from a transmission capacity perspective, single-stream transmission is preferable over multi-stream transmission.

This paper proposes multiple-input multiple-output (MIMO) transmission in fixed gain amplify-and-forward relaying to allow for high data rate coverage in wireless distributed networks. We consider a hierarchical network architecture in which the relay is a multiple antenna static node assisting single antenna mobile nodes. We derive new exact closed-form expressions for the outage probability and the symbol error rate (SER) valid for arbitrary N antennas at the relay under independent but not necessarily identically distributed (i.n.d.) Rayleigh fading. Our solutions apply to general operating scenarios with distinct average received signal-to-noise ratios (SNRs) throughout the network. Based on these, we derive new concise asymptotic expressions which accurately characterizes the outage probability and the SER in the high SNR regime. In our asymptotic solutions, we present an exact expression for the array gain in terms of the average received SNRs and the number of antennas N. We further show that the maximum achievable diversity order is N+1.

We propose a new joint channel coding and physical layer network coding (CPNC) scheme for multiple-input multiple-output (MIMO) two-way relay channels (TWRCs). At the heart of the scheme lies a key technique referred to as eigen-direction alignment (EDA) precoding. This technique efficiently creates multiple aligned parallel channels which facilitates the deployment of multi-stream CPNC. Our analysis shows that the achievable rate of the scheme can approach the capacity upper bound in the median to high signal-to-noise (SNR) region when nT> nR, where nTand nRdenote the number of antennas of each user and that of relay, respectively. The gap to the capacity upper bound diminishes as nT/nRincreases. Numerical results demonstrate that the proposed scheme significantly outperform other well-known schemes in the literature.

We present new statistical properties of the end-to-end signal-to-noise ratio (SNR) in multiple-input multiple-output (MIMO) relaying with distributed transmit antenna selection and receiver maximal-ratio combining (TAS/MRC). In particular, we derive new expressions for the exact and the first order expansions of the cumulative distribution function (cdf). Based on these, new closed-form expressions are derived for the exact and the first order expansions of the moment generating function (mgf). We then present a new concise expression for the symbol error rate (SER) with M-ary phase-shift keying in the high SNR regime. Our asymptotic SER expression explicitly reveals the diversity order and the array gain of the MIMO relay network.

We consider the downlink transmit power allocation problems in multi-user MIMO wireless networks using zeroforcing beamforming. Traditionally such problems are solved by water-filling algorithm under the assumption of perfect channel knowledge. However when channel information is not known a priori or time varying the water-filling solution is shown to be unstable. We use the sliding mode control theory to synthesize the transmit powers so that the target SINR requirements of all users are met. We synthesize the sliding mode controller for the case of zero-forcing beamforming. The synthesis problem is solved under time varying Rayleigh fading channel conditions. Our solutions and simulation results show that our sliding mode controller is stable and delivers better quality of service under practical channel conditions.

Distributed transmit antenna selection with maximal-ratio combining (TAS/MRC) is proposed for use in multiple-input multiple-output (MIMO) multiuser relay networks (MRN), where NS, NR, and NDantennas are equipped at the source, the relay, and each of the K destinations, respectively. For such networks, the destination with the highest instantaneous end-to-end signal-to-noise ratio (SNR) is scheduled for transmission. In each hop, a single transmit antenna that maximizes the post-processing SNR is selected, while all the receive antennas are MRC combined. New exact closed-form expressions are derived for the cumulative distribution function (CDF), the probability density function (PDF), and the moment generating function (MGF) of the highest instantaneous end-to-end SNR. Based on these, we determine the symbol error rate with M-ary phase-shift keying. Our derived results apply to general operating scenarios with arbitrary number of antennas, arbitrary number of destinations, and distinct average SNRs.

In multi-hop cognitive radio networks (CRNs), there can be dramatic increase in end-to-end delay when a traffic flow switches between a number of channels along its path. We propose a new Maximum Flow-Segment (MFS) based scheme to channel assignment in CRN by minimizing the number of times the channel is switched along a flow. Our MFS based scheme has been efficiently integrated into the AODV on-demand routing protocol. We demonstrate that our MFS based scheme reduces the number of channel switches for the traffic flows and reduces the end-to-end delay by 50%. Our scheme also minimizes the routing overhead, and achieves a higher and more stable throughput than the link based approach.

This paper presents a comparison and analysis of selection relaying with transmit beamforming as an effective approach to combat channel impairments in relay-assisted cellular networks. We consider the downlink scenario where the base station equipped with N antennas transmits to the mobile station either directly, or indirectly via a relay station, according to the link with the strongest received signal-to-noise ratio (SNR). We compare two amplify-and-forward protocols: i) fixed gain relaying which requires partial channel state information (CSI), and ii) variable gain relaying which requires full CSI. We present new exact closed-form expressions for the generalized moments of the end-to-end SNR to characterize the higher-order statistical properties of the SNR. We derive new exact closed-form expressions for the symbol error rate (SER), which are valid for a wide variety of modulations. Furthermore, we explicitly characterize the asymptotic behavior of the SER to obtain two key performance parameters: the array gain and the diversity order. Based on these, we reveal that the SNR advantage of variable over fixed gain relaying vanishes in the large N limit.

We develop a unified framework for the symbol error rate (SER) of distributed transmit antenna selection with receiver maximal-ratio combining (TAS/MRC) in multiple-input multiple-output (MIMO) relay networks. We focus on nonregenerative relaying with NS, NR, and NDantennas at the source, relay, and destination, respectively. We consider the general fading scenario of Nakagami-m fading with distinct m fading parameters in the source-to-relay and the relay-to-destination links. We present new analytical expressions for the statistics of the end-to-end signal-to-noise ratio (SNR). Specifically, we derive exact expressions and first order expansions for the cumulative distribution function and moment generating function of the end-to-end SNR. Based on these, we derive new closed-form expressions for the asymptotic SER under M-ary phase-shift keying (M-PSK) and M-ary quadrature amplitude modulation (M-QAM). Our asymptotic solutions accurately identify the diversity order and the array gain as two key design components of the network.

In wireless mesh networks, it is desirable to utilize overlapping coverage of multiple parallel relays to assist the source-destination transmission. In this letter, we consider selection diversity (SD) to select the strongest link amongst the direct and N amplify-and-forward (AF) relay links. We derive new closed-form expressions for the symbol error rate (SER) in independent but not necessarily identically distributed (i.n.d.) Rayleigh fading relay channels. Our results are given as both lower bound and asymptotic expressions based on an accurate upper bound on the signal-to-noise ratio (SNR) of the relay links. Our asymptotic results provide key performance parameters such as the array gain and diversity order, which prove that a full N+1 diversity order is achieved. We show that SD can offer an array gain advantage over maximal-ratio combining which entails all the relays to transmit. Numerical results are shown to validate the analysis.

This paper investigates the performance of open-loop multi-antenna point-to-point links in ad hoc networks with slotted ALOHA medium access control (MAC). We consider spatial multiplexing transmission with linear maximum ratio combining and zero forcing receivers, as well as orthogonal space time block coded transmission. New closed-form expressions are derived for the outage probability, throughput and transmission capacity. Our results demonstrate that both the best performing scheme and the optimum number of transmit antennas depend on different network parameters, such as the node intensity and the signal-to-interference-and-noise ratio operating value. We then compare the performance to a network consisting of single-antenna devices and an idealized fully centrally coordinated MAC. These results show that multi-antenna schemes with a simple decentralized slotted ALOHA MAC can outperform even idealized single-antenna networks in various practical scenarios.

We propose distributed transmit antenna selection with receiver maximal-ratio combining (TAS/MRC) for use in a two-hop multiple-input multiple-output (MIMO) relay network. The network under consideration is equipped with NS, NR, and NDantennas at the source, relay, and destination, respectively. First, we derive a new closed-form expression for the exact cumulative distribution function (cdf) of the end-to-end SNR. Based on this, we present a new closed-form expression for the exact symbol error rate (SER). Our analytical results are further evaluated in the high SNR regime, leading to practical design insights. Our asymptotic expressions are concise and have the added advantage of explicitly characterizing the diversity order and the array gain of the network. Our exact and asymptotic results are valid for general operating scenarios with distinct average received SNRs in each hop.

Nonregenerative relaying in MIMO multi-relay networks is analyzed under the general operating scenario of independent but not necessarily identically distributed (i.n.d.) Rayleigh fading. Exact closed-form expressions are derived for the moment generating function of the end-to-end signal-to-noise ratio (SNR) with distinct average received SNRs in each link. Our analysis applies to arbitrary L number of relays, each equipped with arbitrary N transmit/receive antennas. Based on the derived results, we determine the symbol error rate with M-ary phase-shift keying. In addition, we carry out a high SNR analysis of the error performance. We explicitly reveal that the diversity order is equal to LN+1.

In wireless dual-hop decode-and-forward (DF) relaying networks, multiple relay stations (RS) and users construct a DF broadcast channel (DFBC). Due to unpredictable decoding failure, scheduling in the DFBC should depend on not only channel qualities but also the availability of error-free data at individual RSs. Based on the reception qualities of RSs and channel quality information (CQI), we propose a new centralized scheduling scheme to maximize the sum rate of the DFBC. An exact closed-form expression for the sum rate is derived to analyze the new scheme. To further facilitate the analysis, the bounds of the sum rate are derived as a computationally effective alternative to the exact expression. Simulations demonstrate that the derived closed-form expression quantifies the proposed scheduling method accurately. It is also revealed that the analytical bounds are able to characterize the performance of the new scheduling method with acceptable accuracy.

In this paper, we investigate the benefits of providing limited-feedback and using transmit antenna selection (TAS) in ad hoc networks. We find that the TAS scheme can provide throughput gains of up to 50% compared to the non-feedback scheme. We also find that the performance gains of the TAS scheme are more significant for low path loss exponents and single-antenna transmission. Our results are obtained by deriving new closed-form expressions for the network throughput and transmission capacity. Moreover, we also propose design guidelines for TAS to determine the optimal number of antennas used for transmission.

Cooperative diversity is a promising solution in wireless distributed networks where integrating multiple antennas onto small mobile devices is practically impossible due to size and cost constraints. As such, we consider a cooperative diversity network where the source and the destination user-pair are equipped with single antennas while the relay is a wireless access point equipped with N antennas. For such networks, we focus on cooperative selection diversity (CSD) to select a single link with the highest instantaneous received signal-to-noise ratio (SNR) between the direct link and the multiple-input multiple-output (MIMO) relay link. We present new closed-form expressions for the exact outage probability and the exact symbol error rate (SER) based on the cumulative distribution function (cdf) of the instantaneous received SNR. Our expressions are valid for arbitrary N antennas and apply to general operating scenarios with distinct average received SNRs in each link. Furthermore, we present a high SNR analysis of the outage probability and SER to explicitly characterize the diversity order and array gain. We show that the diversity order increases with the number of antennas according to N + 1.

Multiple amplify-and-forward (AF) relays with receive diversity is analyzed over unbalanced hops with independent but not necessarily identically distributed Rayleigh fading. Exact closed-form expressions are derived for the moment generating function of the end-to-end signal-to-noise ratio (SNR) at the destination. Our analysis apply to arbitrary numbers of relays and arbitrary numbers of antennas at the destination. Based on the derived results, we determine the symbol error rate with M-ary phase-shift keying. In addition, we carry out an asymptotic analysis in the high SNR regime. Our results provide fundamental insights into the impact of the number of antennas on the performance of multiple AF relaying. We explicitly reveal that the diversity order is equal to the sum of the number of relays and the number of antennas. Theoretical analysis is verified by simulation.

In wireless decode-and-forward (DF) relaying networks, the hybrid ARQ (HARQ) process suffers severe latency, especially when centralized scheduling is employed. We propose a new distributed HARQ based cooperative relaying (DHCR) protocol to reduce the latency. Based on the reception quality of the 1st hop, each relay station (RS) independently processes and forwards the data stream in such a manner that, from the perspective of the destination, three cooperative relaying modes can be effectively formed and one of them is adaptively selected: spatial multiplexing (SM), space-time transmit diversity (STTD) and unicast (UC). The proposed DHCR protocol places priority on SM and it is throughput-oriented. In addition, we develop a new analytical model based on the Markov chain to facilitate the performance analysis of the proposed protocol. Based on the new model, we have derived the exact expressions for spectral efficiency, latency and the distribution of latency. It is revealed that the new DHCR protocol can decrease the latency by around 40% at high signal-to-noise ratio (SNR) without loss of spectral efficiency compared with the centralized approach.

This paper considers multiple-input/multiple-output(MIMO) cooperative communication systems with a decode-and-forward (DF) relay. We propose novel rate maximization schemes which utilizes uniform channel decompositions (UCD)to decompose the MIMO channel between a base station (BS) and a relay station (RS). In the proposed scheme, the MIMO channel is decomposed into multiple independent subchannels with equal gains by the UCD and the power allocation will be performed over the subchannels to maximize achievable throughput. We consider not only a simple individual power constraint but also a sum power constraint as well which is useful for the DF based relay systems. It will be shown through simulations that proposed schemes enhance the achievable throughput significantly by distributing the transmit power of the BS and the RS efficiently.

In this paper, we consider complementary sensing nodes to increase the spectrum sensing efficiency of cognitive radio (CR) systems. As the CR system has no prior knowledge about the operation of the licensed network, it is difficult to employ efficient diversity techniques such as the selection diversity. In this paper, by jointly designed with a medium access layer protocol, we propose a sensor node selection technique on the channel where the primary user is active. Collaborated with the mode of operation defined for CR nodes, the proposed scheme selects the dedicated sensing node for the channel with the best sensing performance. Numerical results show that the performance of the proposed scheme is almost the same as the cooperative spectrum sensing while our proposed scheme requires only one sensing node for the spectrum sensing.

The capture effect can occur in IEEE 802.11 distributed coordination function (DCF) wireless systems when packets arrive with different powers. Packets with high power can effectively swamp low power packets, such that they are received successfully, when otherwise a collision would have occurred. We present a network performance prediction model that accurately incorporates the capture effect into a 3-D Markov Chain. The model is solved efficiently with the Collapsed Transition onto Basis (CTB) approach. The performance of the model is significantly better than existing models in terms of estimating important QoS measures, including packet delay and loss, as well as collision probability and throughput.

This paper analyzes selection diversity as an effective tool to combat channel impairments in relay-assisted cellular systems. We consider the downlink scenario where the base station equipped with N antennas transmits to the mobile station either directly, or indirectly via a relay station, according to the link with the strongest received signal-to-noise ratio (SNR). For this system, we analyze the performance of fixed gain amplify-and-forward relaying that does not require full channel-state-information (CSI) at the relay. We derive new exact closed-form expressions for the outage probability and symbol error rate (SER) based on new statistical properties of the end-to-end SNR. Furthermore, we quantify the asymptotic behavior of the outage probability and SER. We explicitly reveal the impact of multiple antennas with relay selection diversity, on the array gain and the diversity order. Our new asymptotic results prove that the maximum diversity order of N+1 is achieved.

Distributed multi-antenna relaying is analyzed in nonregenerative cooperative networks with unbalanced hops and independent but not necessarily identically distributed Rayleigh fading. Exact closed-form expressions are derived for the moment generating function of the end-to-end signal-to-noise ratio (SNR) at the destination. Our analysis applies to arbitrary N number of antennas at the relay and arbitrary average received SNRs. Based on the derived results, we determine the symbol error rate with M-ary phase-shift keying. In addition, we carry out an asymptotic analysis in the high SNR regime. Our results provide fundamental insights into the impact of the number of antennas on the performance of nonregenerative relaying. We explicitly reveal that the diversity order is equal to N + 1. Theoretical analysis is verified by simulation.

In wireless dual-hop decode-and-forward (DF) relaying networks, multiple relay stations (RS) and users construct a multiple-in-multiple-out (MIMO) broadcast channel (BC). Due to unpredictable decoding failure, scheduling the transmission for the decode-and-forward broadcast channel (DFBC) should depend on not only channel qualities but also the availability of errorless data at individual RSs. Based on the reception qualities of RSs and channel quality information (CQI), we propose a new centralized scheduling scheme to maximize the sum rate of the DFBC. An exact closed-form expression for the sum rate is derived to analyze the new scheme. Simulations demonstrate that the derived closed-form expression is able to quantify the proposed scheduling method accurately. It is also revealed that extra cooperative diversity can be exploited by employing the increased number of RSs, thereby improving sum rate.

This paper proposes and analyzes selection diversity as an effective tool to combat channel impairments in relay-assisted cellular systems. We consider the uplink scenario where the base station equipped with N antennas receives from the mobile station either directly, or indirectly via a relay station, according to the link with the strongest received signal-to-noise ratio (SNR). For this system, we analyze the performance of fixed gain amplify-and-forward relaying that does not require full channel-state-information (CSI) at the relay. We derive new exact closed-form expressions for the outage probability and symbol error rate (SER) based on new statistical properties of the end-to-end SNR. Furthermore, we quantify the asymptotic behavior of the outage probability and SER. We explicitly reveal the impact of multiple antennas with relay selection diversity, on the array gain and the diversity order. Our new asymptotic results prove that the maximum diversity order of N + 1 is achieved.

Multiple fixed gain amplify-and-forward (AF) relays with receive diversity is analyzed for the practical case of unbalanced hops with independent but non-identically distributed (i.n.d.) Rayleigh fading channels. We derive a new exact closed-form expression for the moment generating function (mgf) of the end-to-end signal-to-noise ratio (SNR). Our mgf is valid for the general case of arbitrary numbers of relays and arbitrary numbers of antennas at the destination. Based on this, we determine the exact and approximate symbol error rate (SER) for M-ary phase-shift keying. Our results provide new important insights into the joint impacts of the number of relays and the number of receive antennas on the system performance. Theoretical analysis is verified by simulation.

Wireless decode-and-forward (DF) relay networks suffer from severe latency due to multi-hop propagation. When hybrid ARQ (HARQ) is employed, the latency leads to the throughout degradation of individual HARQ processes because of the decreased number of retransmissions of unsuccessful packets in a given time. We propose two new distributed cooperative HARQ protocols to not only reduce latency but also optimize throughput in both forward and reverse DF links. Additional selection diversity from multiple packets is exploited to compensate for the throughput loss stemming from the less powerful source in the reverse DF link. Based on the 1st hop reception quality, each relay station (RS) independently forwards the packet in such a manner that, from the perspective of the destination, one of the three cooperative relaying modes is effectively formed with the highest instantaneous throughput: spatial multiplexing (SM), space-time transmit diversity (STTD) and unicast (UC). The maximal throughput can be achieved with minimal latency. The superiority of the proposed approaches has been demonstrated in terms of the optimal spectral efficiency and significant reduction in latency. Compared to the centralized approaches, the reduction is up to 40% at high signal-to-noise ratio (SNR) and the throughput of individual HARQ processes increases as a result.

Performance of a decode-and-forward (DF) based two-hop multiuser cooperative transmission system is usually restricted by the link quality between a base station (BS) and a relay station (RS) as the number of users grows. Thus the BS-RS link quality should be improved to enhance the performance. In this paper, we propose two-hop cooperative communication systems with multiple receive antennas at the RS to boost the quality of the BS-RS link. With M-QAM signal constellations, our proposed optimize the system performance with a symbol error constraint. By evaluating the performance via simulations, we will show that the proposed schemes improve the performance of the DF based cooperative transmission systems significantly by exploiting advantages of multiple antennas at the RS efficiently.

This paper considers the performance of the multiuser multi-antenna downlink where NTbase station antennas transmit to K non-collocated, single antenna users over correlated channels. A practical and near-capacity multi-user technique called vector perturbation precoding (VPP) is considered. For these scenarios, we derive a lower bound to the average energy of the precoded vector. We use this to approximate the effective noise gain at the receivers due to the presence of transmit side correlation. Furthermore, we obtain simple approximations for the noise gain for constant and exponential transmit correlation models. Simulation results show that our approximations predict the performance loss due to correlation remarkably well regardless of the correlation parameter.

When multi-user multiple-input multiple-output (MU-MIMO) is applied to predominantly line-of-sight (LoS) environments, such as in the case of fixed wireless access in rural areas where a central access point (AP) equipped with an antenna array with NAPantenna elements serves NUTuser terminals (UTs) each equipped with a single antenna, the problem of ill-conditioned channels arises. This paper investigates the performance of zero-forcing preceding based MU-MIMO downlink when the AP is equipped with a uniform circular array (UCA) in an LoS environment. The performance is analyzed as a function of the spacing and the number of AP UCA antenna elements for NAP≥ NUT. The analysis reveals a complex yet orderly pattern of the performance nulls indicating different optimal antenna spacing for different number of antenna elements. The performance nulls can be largely eliminated by employing NAP≥ 2NUT.

This paper investigates the achievable sum rate of multiple-input multiple-output (MIMO) wireless systems employing linear minimum mean-squared error (MMSE) receivers. We present a new analytic framework which exploits an interesting connection between the achievable sum rate with MMSE receivers and the ergodic mutual information achieved with optimal receivers. This simple but powerful result enables the vast prior literature on ergodic MIMO mutual information to be directly applied to the analysis of MMSE receivers. The framework is particularized to various Rayleigh and Rician channel scenarios to yield new exact closed-form expressions for the achievable sum rate, as well as simplified expressions in the asymptotic regimes of high and low signal-to-noise ratios (SNRs). These expressions lead to the discovery of key insights into the performance of MIMO MMSE receivers under practical channel conditions.

Quality of Service (QoS) and queue management are important issues for IEEE 802.11 systems. However, existing 2-dimensional (2-D) Markov chain models of 802.11 systems are unable to capture the complete QoS performance and queueing behavior due to the lack of an adequate finite buffer model. We present a 3-dimensional (3-D) Markov chain that integrates the 802.11 system contention resolution and queueing processes into one model. The 3rddimension, that models the queue length, allows us to accurately capture important QoS measures, delay and loss, plus throughput and queue length, for realistic 802.11 systems with finite buffer under finite load. We derive an efficient method for solving the steady state probabilities of the Markov chain. Our 3-D Markov chain is the first finite buffer model defined and solved for 802.11 systems. The solutions, validated by extensive simulations, capture the system dynamics over a wide range of traffic load, buffer capacity, and network size. Our 3-D model points to the existence of an effective maximum throughput and shows its relationship with buffer capacity. We demonstrate that our 3-D model can also be used in resource allocation to determine adequate buffer sizes under a particular QoS constraint.

This paper considers the multiuser multiple-input multiple-output (MIMO) broadcast channel. We consider the case where the multiple transmit antennas are used to deliver independent data streams to multiple users via vector perturbation. We derive expressions for the sum rate in terms of the average energy of the precoded vector, and use this to derive a high signal-to-noise ratio (SNR) closed-form upper bound, which we show to be tight via simulation. We also propose a modification to vector perturbation where different rates can be allocated to different users. We conclude that for vector perturbation precoding most of the sum rate gains can be achieved by reducing the rate allocation problem to the user selection problem. We then propose a low-complexity user selection algorithm that attempts to maximize the high-SNR sum rate upper bound. Simulations show that the algorithm outperforms other user selection algorithms of similar complexity.

In this paper, we consider multiuser cooperative multiplexing schemes in cellular networks with fixed relays and address the problem of inter-user interference. We propose two schemes to mitigate the effect of the interference: an interference cancellation scheme and a cooperative precoding scheme. The interference cancellation scheme utilizes the broadcast nature of the signal transmitted to the fixed relay, and is based on a decode-and-forward relaying protocol. We provide a capacity bound for the proposed scheme, and also propose a power reduction scheme for the fixed relay. For the cooperative precoding scheme, we employ a cooperative linear filter at the transmitter to eliminate interference. Simulation results show that both proposed schemes enhance the achievable throughput significantly.

By constructing the cliques of the compatibility graph, the heuristic spectrum sharing (SS) method is proposed to enable opportunistic frequency reuse between two networks possessing the adjacent bands in the centralized manner. With the method, the minimal satisfaction of cells is maximized and the spectral utilization is improved. However, the method suffers the prohibitive complexity, especially if the number of cells is large. To cope with the complexity, the suboptimal SS method has been developed with the same principle. Simulations reveal that the suboptimal SS method can provide similar performance in terms of spectral utilization and minimal satisfaction to the heuristic solution.

We derive new exact closed-form expressions for the symbol error rate (SER) of cooperative selection diversity (CSD) with amplify-and-forward (AF) transmission using channel-state-information (CSI)-based gain relaying. We consider the general fading condition of independent but not necessarily identically distributed (i.n.d.) Nakagami-m fading. We also present a closed-form expression for i.n.d. Rayleigh fading as a special case. We highlight the impact of the m fading parameter on the SER performance in unbalanced fading conditions. Numerical results substantiate the validity of our analysis.

We propose a new algorithm for noncoherent sequence detection of M-ary phase-shift-keying (M-PSK) symbols transmitted over a block fading channel. The algorithm is of complexity O(T), where T is the sequence length, and is therefore computationally superior to existing maximum-likelihood (ML) detectors of complexity O(T logT). Our detector is based on a new approximation we propose to the noncoherent ML function. We show that by using this close approximation, the detection problem reduces to a nearest lattice point problem for the lattice An*, from which we derive our O(T) approach. Simulation results are provided that show the difference in bit error rate is negligibly small for a wide range of signal-to-noise ratios.

Decentralized multiple access networks require dynamic spectrum allocation to efficiently and fairly allocate resources among multiple users. In this paper, we consider the problem of spectrum allocation from the standpoint of diversity combining, and in particular as an explicit case of selection combining (SC). General order selection allocation (GOSA) was previously proposed by the authors as a low-complexity spectrum allocation scheme for decentralized multiple access networks. In this paper, noting that previous analytical results on the error performance of GOSA are for independent identically distributed (i.i.d.) Rayleigh fading, we carry out a thorough and exact analysis of GOSA for the i.i.d. Nakagami-m fading scenario. In particular, based on new results on the exact and asymptotic average error probability of the r-th order statistic, we obtain exact and asymptotic closed-form expressions for the error performance of GOSA. Numerical results show that the performance of the algorithm is close to that of the highly complex optimal search method.

We introduce a 3-dimensional Markov chain that integrates the IEEE 802.11 DCF contention resolution and queueing processes into one model. Important QoS measures, delay and loss, plus throughput and queue length, can be obtained for a realistic systems with finite buffer under finite load. We present an efficient method for solving the steady state probabilities of the Markov chain. Simulations confirm the accuracy of our model, and demonstrate that the model provides new insights into the 802.11 DCF protocol.

This paper investigates the performance of point-to-point spatial multiplexing with stream control and slotted ALOHA in ad hoc networks. In particular, we derive new closed-form outage probability, network throughput and transmission capacity expressions for spatial multiplexing with maximum-ratio-combining (MRC) and zero forcing (ZF) receivers. From these expressions, we show that the relative throughput of MRC and ZF receivers is dependent on node intensity and SINR threshold levels. In addition, we present a new transmission capacity scaling law for ZF receivers, which shows that increasing the number of transmitted data streams can either increase or decrease the transmission capacity depending on the path loss exponent and number of receive antennas. We also present conditions such that the transmission capacity using spatial multiplexing with ZF receivers is greater than orthogonal space time block codes.

We present an interesting and powerful new framework connecting the achievable sum rate of multiple-input multiple-output (MIMO) wireless systems employing linear minimum mean-squared error (MMSE) receivers, and the ergodic MIMO mutual information. This allows the vast literature on ergodic MIMO mutual information to be directly applied to the analysis of MMSE receivers. As an example, the framework is particularized to spatially-correlated Rayleigh fading to yield new exact closed-form expressions for the achievable sum rate, as well as simplified expressions for high and low signal to noise ratios.

This paper considers the multiuser multiple-input multiple-output (MIMO) Rayleigh fading broadcast channel. We consider the case where the multiple transmit antennas are used to deliver independent data streams to multiple users via a multi-user technique known as vector perturbation. We derive expressions for the capacity in terms of the average energy of the preceded vector, and use this to derive a closed-form high-SNR upper bound, which we show to be tight via simulation. We then turn to the practical issue of user selection. We propose a low-complexity user selection algorithm that attempts to maximize the high-SNR sum rate upper bound. Simulations show that the algorithm outperforms other user selection algorithms of similar complexity.

This paper proposes reflected simplex codebooks for limited feedback beamforming in multiple-input multiple-output (MIMO) wireless systems. The codebooks are a geometric construction based on simplices and the Anlattice. We propose a fast codebook search and indexing algorithm. We show that such codebooks perform superior or comparable to other codebooks, with much lower implementation complexity.

This paper considers MIMO-OFDM transmission with low density parity check (LDPC) codes. We employ a low complexity minimum mean-square-error (MMSE) soft-interference-cancelation (SIC) based double iterative receiver (DIR). Results are presented for a real system implementation at 5.2 GHz. We achieve zero packet errors at 90% of the measured indoor locations, when transmitting at 600 Mbit/s, with 15 bit/s/Hz spectral efficiency and 26 dB signal-to-noise ratio. We show that the proposed receiver actually outperforms a list sphere detection (LSD) based single iterative receiver (SIR) at high coding rates, in practice. Investigations reveal that the LSDSIR is adversely affected by the non-Gaussian noise present at the receiver, while at the same time the MMSE-SIC-DIR is better able to handle transmitter noise present in the practical system.

We present new exact closed-form expressions for the symbol error rate (SER) of cooperative selection diversity (CSD) with a single fixed gain amplify-and-forward (AF) relay. We consider the general fading condition of independent but not necessarily identically distributed (i.n.d.) Nakagami-m fading. We also present a closed-form expression for i.n.d. Rayleigh fading as a special case. We highlight the performance improvements provided by CSD with fixed gain relaying in unbalanced fading conditions. Numerical results substantiate the validity of our analysis.

In this paper, we consider multiuser cooperative multiplexing schemes in cellular networks with fixed relays and address the problem of inter-user interference. We propose two schemes to mitigate the effect of the interference: an interference cancellation scheme and a cooperative preceding scheme. The interference cancellation scheme utilizes the broadcast nature of the signal transmitted to the fixed relay, and is based on a decode-and-forward relaying protocol. The second scheme we propose is a cooperative preceding technique which employs a cooperative linear filter at the transmitter to eliminate interference. Simulation results show that both proposed schemes enhance the achievable throughput significantly.

In this paper, we consider efficient power control scheme for a multiuser cooperative multiplexing system with fixed relays employing decode-and-forward relaying schemes. We take two power control problems into account and propose efficient schemes for each problem: transmission power control for the fixed relay and power allocation problem between a base station and the fixed relay. Proposed schemes utilize only reported channel state information required to perform multiuser scheduling. Simulation results show that the power control scheme for the fixed relay significantly reduces unnecessary power consumption and the power allocation scheme for the base station and the fixed relay enhances the system performance by optimizing transmit power to maximize sum capacity.

We consider joint optimization problems among link, MAC, and routing layers for wireless sensor networks with hetrogeneous nodes where battery lifetime maximization for a certain portion of nodes is more important than the maximization across all nodes in the network. For such applications, we propose two battery lifetime maximization schemes: a sequential joint link, MAC, and routing optimization, and a receive antenna selection for burst data applications. Numerical results show that proposed schemes greatly increase the battery lifetime for the node group regarded as more critical while the total energy consumption degradation maintains in a reasonable amount.

This paper analyzes the performance of multiuser optimum combining systems. We consider the practical scenario where the desired user undergoes Rician fading, and the received signals are corrupted by Rayleigh-faded interference and noise. We derive new closed-form expressions for the symbol error rate, ergodic capacity, level crossing rate, and average fade duration. These results are given as either accurate approximations or asymptotic (eg. high signal-to-noise ratio (SNR)) expressions, and are based on new closed-form statistical properties which we derive for the signal-to-interference noise ratio (SINR). Specifically, we derive exact first order expansions and accurate gamma approximations for the SINR distribution, as well as simplified exact expressions for the moments. We also present closed-form expressions for key performance parameters such as the diversity order and array gain, wideband slope, and high SNR power offset, and analyze the impact of the Rician K-factor, which is shown in all cases to yield a performance improvement.

We analyze scheduling algorithms for multiuser communication systems with users having multiple antennas and linear receivers. When there is no feedback of channel information, we consider a common round robin scheduling algorithm, and derive new exact and high signal-to-noise ratio (SNR) maximum sum-rate results for the maximum ratio combining (MRC) and minimum mean squared error (MMSE) receivers. We also present new analysis of MRC, zero forcing (ZF) and MMSE receivers in the low SNR regime. When there are limited feedback capabilities in the system, we consider a common practical scheduling scheme based on signal-to-interference- and-noise ratio (SINR) feedback at the transmitter. We derive new accurate approximations for the maximum sum-rate, for the cases of MRC, ZF and MMSE receivers. We also derive maximum sum-rate scaling laws, which reveal that the maximum sum-rate of all three linear receivers converge to the same value for a large number of users, but at different rates.

This paper considers the analysis of optimum combining systems in the presence of both co-channel interference and thermal noise. We address the cases where either the desired-user or the interferers undergo Rician fading. Exact expressions are derived for the moment generating function of the SINR which apply for arbitrary numbers of antennas and interferers. Based on these, we obtain expressions for the symbol error probability with M-PSK. For the case where the desired-user undergoes Rician fading, we also derive exact closed-form expressions for the moments of the SINR. We show that these moments are directly related to the corresponding moments of a Rayleigh system via a simple scaling parameter, which is investigated in detail. Numerical results are presented to validate the analysis and to examine the impact of Rician fading on performance.

This paper considers the problem of beamforming in multiple-input multiple-output (MIMO) wireless systems. Assuming perfect channel state information at the receiver, the choice of the beamforming vector is made possible through a noiseless limited-rate feedback of one or more bits per coefficient to the transmitter. This paper proposes the use of beamforming codebooks based on quadrature amplitude modulation (QAM) and phase-shift keying (PSK) constellations, which essentially eliminates the need for storage of the codebook. We show that such codebooks perform arbitrarily close to the perfect feedback case as the constellation size increases, and that full diversity order is achieved. We demonstrate an equivalence between the beamforming codebook search problem with that of noncoherent sequence detection. Based on this we propose fast beamforming vector search algorithms. Monte-Carlo simulations are presented to show that the performance is comparable to the best known codebooks, and that the search complexity can be reduced by several orders of magnitude.

This paper considers the multiuser multiple-input multiple-output (MIMO) Rayleigh fading broadcast channel. We consider the case where the multiple transmit antennas are used to deliver independent data streams to multiple users via a multiuser technique known as vector perturbation. We propose lattice-theoretic and rate-distortion based approaches to analyze the performance of these systems, taking into account the practical restrictions imposed by limited feedback and training. We show that performance is primarily determined by the ratio between the number of users and the number of transmit antennas. We then propose a new practical low-complexity low-rate feedback scheme, and show that the performance approaches the ideal rate-distortion based scheme.

In this paper, we propose and analyze three new transmit antenna selection schemes with reduced feedback rate requirement compared with the conventional scheme. In scheme 1, Ltavailable transmit antennas are divided as equally as possible into two groups with consecutive antennas. The best single antenna within each group is selected. In scheme 2, only the best one among Ltantennas is made known to the transmitter, and the other one is selected at random. In Scheme 3, Ltantennas are divided into multiple subsets each consisting of two adjacent antennas, and the best subset is selected. Bit error rate (BER) expressions for the proposed schemes with Alamouti code are derived for independent flat Rayleigh fading channels. It is found that all the three schemes achieve a full diversity order. The relative merit of each proposed scheme is delineated based on the trade-off between the asymptotic performance loss and feedback reduction, both relative to the conventional scheme. We conclude that Schemes 1 and 3 are more favorable for practical applications, and the appropriate application scenarios are also identified. The proposed schemes enrich the choices for antenna selection system design for various feedback channel bandwidths and different requirements for quality of service.

We analyze the sum capacity achieved by linear receivers in a multiple-input multiple-output broadcast channel. We consider a simple and practical opportunistic scheduling algorithm, based on the signal to interference noise ratio (SINR) feedback from each user. Each transmit antenna sends data to a particular user, selected based on SINR. Under this scheduling scheme, we derive new accurate approximations for the sum capacity, for the cases of maximum ratio combining, zero forcing, and minimum mean-squared error receivers. We also derive capacity scaling laws, which reveal that the capacity of all three linear receivers converge to the same value for a large number of users. Our results are confirmed through comparison with Monte Carlo simulations.

This paper analyzes the performance of adaptive antenna arrays employing linear combining techniques designed to maximize the SINR. In the communications literature, these systems are referred to as optimum combining (OC) systems. We consider the practical case where the desired signal undergoes Rician fading, and is corrupted by Rayleigh-faded interfering signals and noise. We first propose new closed-form gamma approximations for the SINR distribution at the output of the OC combiner, which we show to be remarkably accurate. We then employ these approximations to derive new closed-form expressions for the ergodic capacity and simplified expressions for the high-SNR regime. These results reveal that the capacity improves monotonically with Rician K-factor.

This paper analyzes the performance of multiuser optimum combining (OC) systems where the desired user undergoes Rician fading, and the received signals are corrupted by Rayleigh-faded interference and noise. We consider the SER and ergodic capacity in asymptotic SNR regimes, and derive new closed-form expressions for key performance parameters such as the diversity order, array gain, and wideband slope. These results clearly reveal the impact of the Rician if-factor, which is shown to be advantageous to performance in all cases.

This paper investigates an important tradeoff in wireless ad hoc networks concerning the allocation of resources to the PHY and MAC layers. We compare two approaches: One which employs a non-coordinated slotted ALOHA MAC with multi-antenna PHY, and one which employs a tightly coordinated MAC and single-antenna PHY. For both cases, we derive new closed-form throughput expressions. Based on these, we show that using simple slotted ALOHA in conjunction with multiple antennas can provide a higher throughput than fully coordinated access protocols in various practical scenarios. Our results are confirmed through comparison with Monte Carlo simulations.

This paper considers the use of multiple transmit antennas to deliver independent data streams to multiple users. In particular, we examine a multi-user technique known as vector perturbation. We provide a new lattice-theoretic approach to analyze its performance in the presence of Rayleigh fading. Vector perturbation is based on performing a channel inversion, with the additional step of perturbing the data signal prior to linear preceding to significantly reduce the required transmit power. To analyze such systems it is necessary to calculate the resulting average energy of the sphere-encoded signal vector, as this determines the signal-to-noise ratio (SNR) at the output of the demodulator. Previous results presented in the literature were partially analytic, requiring further numerical evaluation. Here, we derive a concise approximation to the output SNR. We also provide tight upper and lower bounds on the bit error rate for the reception of QAM symbols using the required modulo demodulator, as a function of the average energy of the sphere- encoded signal vector.

We derive two new energy efficient reliable data transport protocols for overcoming the negative impact of asymmetric radio links in wireless sensor networks. The energy efficiency of these algorithms is explicitly derived using our theoretical model, and validated by results obtained from simulations and field trials. The analytical, simulation and field trials demonstrate that our proposed protocols perform well in networks with asymmetric links and can save energy of up to 27% compared to conventional ARQ schemes.

We propose an efficient reliable data collection(eRDC) algorithm. The eRDC is designed for energy-constraint wireless sensor networks (WSN) to balance reliability and energy consumption. We derive energy efficiencies of the proposed reliability schemes, and evaluate their performances. These analyses provide a guideline to determine the number of retransmissions for reliable data delivery. Dynamic programming concept is used to find the optimal solution. We present a distributed eRDC implementation to dynamically control the maximum number of retransmissions based on the guideline provided. Discrete event simulations and field trials with wireless sensor nodes confirmed our results.

We present a novel technique for the detection of spatially multiplexed transmitted symbols in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. The method, termed Selective Detection, observes errors caused by a simple zero-forcing (ZF) on different OFDM sub-carriers, and selectively performs list sphere detection (LSD) on sub-carriers with larger errors. Compared with the full-complexity LSD, the proposed algorithms could significantly reduce the receiver complexity at a small signal-to-noise ratio (SNR) loss. For example, simulation results for a coded MIMO- OFDM system using four transmitters and four receivers with 16 quadrature amplitude modulation (16-QAM) and low density parity check (LDPC) coding show that more than 90% of SNR gain that can be achieved by the use of LSD over ZF can be achieved if only 20% of sub-carriers are intelligently selected for LSD.

This paper presents analysis of performance measurements from a MIMO-OFDM IEEE 802.11n hardware implementation at 5.2 GHz using four transmitters and four receivers. Two spatial multiplexing systems are compared; one which uses a zero-forcing (ZF) detector and the other a list sphere detector (LSD). We show that the measured results do not align with standard prediction based on simulation assuming uncorrelated receiver noise. We show that the discrepancy can be explained by the inclusion of transmitter noise into the channel model. This effect is not included in existing MIMO-OFDM channel models. The measured results from our hardware implementation show successful packet transmission at 600 Mb/s with 15 bits/s/Hz spectral efficiency at 73% coverage for ZF and 84% coverage for LSD with an average receiver signal to noise ratio (SNR) of 26 dB.

This paper analyzes MIMO systems with multichannel beamforming in Ricean fading. Our results apply to a wide class of multichannel systems which transmit on the eigenmodes of the MIMO channel. We first present new closed-form expressions for the marginal ordered eigenvalue distributions of complex noncentral Wishart matrices. These are used to characterize the statistics of the signal to noise ratio (SNR) on each eigenmode. Based on this, we present exact symbol error rate (SER) expressions. We also derive closed-form expressions for the diversity order, array gain, and outage probability. We show that the global SER performance is dominated by the subchannel corresponding to the minimum channel singular value. We also show that, at low outage levels, the outage probability varies inversely with the Ricean A*-factor for cases where transmission is only on the most dominant subchannel (i.e. a singlechannel beamforming system). Numerical results are presented to validate the theoretical analysis.

In this paper, we consider an automatic-repeat-request (ARQ) retransmission protocol signaling over a block-fading multiple-input–multiple-output (MIMO) channel. Unlike previous work, we allow for multiple fading blocks within each transmission (ARQ round), and we constrain the transmitter to fixed rate codes constructed over complex signal constellations. In particular, we examine the general case of average input-power-constrained constellations with a fixed signaling alphabet of finite cardinality. This scenario is a suitable model for practical wireless communications systems employing orthogonal frequency division multiplexing (OFDM) techniques over a MIMO ARQ channel. Two cases of fading dynamics are considered, namely, short-term static fading where channel fading gains change randomly for each ARQ round, and long-term static fading where channel fading gains remain constant over all ARQ rounds pertaining to a given message. As our main result, we prove that for the block-fading MIMO ARQ channel with a fixed signaling alphabet satisfying a short-term power constraint, the optimal signal-to-noise ratio (SNR) exponent is given by a modified Singleton bound, relating all the system parameters. To demonstrate the practical significance of the theoretical analysis, we present numerical results showing that practical Singleton-bound-achieving maximum distance separable codes achieve the optimal SNR exponent.

This communication considers the distribution of the mutual information of frequency-selective spatially uncorrelated Rayleigh fading multiple-input–multiple-output (MIMO) channels. Results are presented for orthogonal frequency-division multiplexing (OFDM)-based spatial multiplexing. New exact closed-form expressions are derived for the variance of the mutual information. In contrast to previous results, our new expressions apply for systems with both arbitrary numbers of antennas and arbitrary-length channels. Simplified expressions are also presented for high and low signal-to-noise ratio (SNR) regimes. The analytical variance results are used to provide accurate analytical approximations for the distribution of the mutual information, and the outage capacity.

This paper uses an incremental matrix expansion approach to derive asymptotic eigenvalue distributions (a.e.d.'s) of sums and products of large random matrices.We show that the result can be derived directly as a consequence of two common assumptions, and matches the results obtained from using R-and S-transforms in free probability theory.We also give a direct derivation of the a.e.d. of the sum of certain random matrices which are not free.This is used to determine the asymptotic signalto-interference-ratio of a multiuser CDMA system with a minimum mean-square error linear receiver.

This paper analyzes bit error rate (BER) and outage probability of singular value decomposition-based multiple-input multiple-output systems with channel estimation error and feedback delay over uncorrelated Ricean fading channels. By utilizing marginal unordered and ordered eigenvalue distributions of complex noncentral Wishart matrices, we derive exact closed-form expressions on the average system performance and high signal- to-interference-plus-noise ratio (SINR) approximations on the individual eigen-subchannels, respectively, under the assumption of equal power allocation. Our expressions apply for various modulation formats and arbitrary numbers of transmit and receive antennas. Our results show that in low-to-moderate SINR regimes, both the BER and the outage probability increase with channel estimation error, feedback delay and the Ricean K-factor at a polynomial rate that is inversely proportional to the difference between the numbers of transmit and receive antennas. We also show that, with channel estimation error and feedback delay, the diversity orders of the BER and outage probability are zero and an irreducible error floor exists at high SINR.

This paper investigates the capacity of multiple- access and broadcast channels with MIMO-MRC systems in spatially correlated environments. We present new capacity approximations which are shown to be accurate. The approximations are based on new simple expansions which we derive for the maximum eigenvalue distribution of correlated Wishart matrices. We then proceed to analyze the affects of correlation and show it is beneficial for capacity. Our results are confirmed through comparison with Monte Carlo simulations.

This paper investigates the performance of spatial diversity techniques in dense ad hoc networks. We derive analytical expressions for the contention density in systems employing MIMO-MRC or OSTBC. In the case of MIMO- MRC the expressions are based on new expansions for the SIR distribution in the high interference regime typical in dense networks. Our results are confirmed through comparison with Monte Carlo simulations.

One of the main difficulties in echo cancellation is the fact that the learning rate needs to vary according to conditions such as double-talk and echo path change. Several methods have been proposed to vary the learning. In this paper we propose a new closed-loop method where the learning rate is proportional to a misalignment parameter, which is in turn estimated based on a gradient adaptive approach. The method is presented in the context of a multidelay block frequency domain (MDF) echo canceller. We demonstrate that the proposed algorithm outperforms current popular double-talk detection techniques by up to 6 dB.

This paper analyzes the average bit error rate (BER) performance of singular value decomposition-based multiple-input multiple-output systems with channel estimation error and feedback delay over uncorrelated Ricean fading channels. By utilizing marginal unordered eigenvalue distributions of complex noncentral Wishart matrices, we derive exact closed- form BER expression under the assumption of equal power allocation. Our results apply for various modulation formats and arbitrary numbers of transmit and receive antennas. Our results show the average BER increases with channel estimation error, feedback delay and Ricean A'-factor at a polynomial rate that is inversely proportional to the difference between the numbers of transmit and receive antennas. We also show that the achievable BER performance is limited by the presence of an irreducible error floor as the signal-to-interference-plus-noise ratio increases.

This paper investigates the capacity of multiuser MIMO-MRC systems in spatially correlated environments. We present new capacity approximations which are shown to be accurate. The approximations are based on new simple expansions which we derive for the maximum eigenvalue of correlated Wishart matrices. We show that for a large number of users there is a capacity offset due to correlation. Through this, we show that correlation is beneficial for capacity. Our results are confirmed through comparison with Monte-Carlo simulations.

We derive new analytic approximations to the capacity distribution of frequency-selective Rayleigh fading MIMO channels. The results apply specifically to OFDM-based spatial multiplexing. In particular, we present a new closed-form Gaussian approximation which yields very high accuracy in many scenarios. For the low SNR regime, we also present a new simpler closed-form Gamma approximation, which we show to be even more accurate than Gaussian in this case. Our approximations are based on new exact closed-form expressions which we derive for the variance of the mutual information which, in contrast to previous results, apply for systems with both arbitrary numbers of antennas and arbitrary-length channel delay profiles.

This paper analyzes the performance of optimum combining systems in the presence of both co-channel interference and thermal noise, addressing the case where the desired- user undergoes Rician fading. Exact expressions are derived for the moment generating function of the SINR which apply for arbitrary numbers of antennas and interferers. Based on these, we obtain expressions for the symbol error probability with M-PSK. We also derive exact closed-form expressions for the moments of the SINR, and show that they are directly related to the corresponding moments of a Rayleigh system via a simple scaling parameter. Numerical results are presented to validate the analysis, and to examine the impact of Rician fading.

This paper proposes a new QAM based codebook for beamforming in multiple-input multiple-output (MIMO) wireless systems with a limited-rate feedback channel. We show that such codebooks perform arbitrarily close to the perfect feedback case as the constellation size increases, and that full diversity order is achieved. We demonstrate an equivalence between the problems of beamforming codebook search and noncoherent sequence detection. Based on this we propose a fast beamforming vector search algorithm. Monte-Carlo simulations are presented to show that the performance is comparable to the best known codebooks, and that the search complexity can be reduced by several orders of magnitude.

In this paper, we consider an automatic-repeat-request (ARQ) retransmission protocol signaling over a block-fading multiple-input, multiple-output (MIMO) channel. In particular, we consider fixed rate codes constructed over discrete complex signal constellations. We show that the optimal signal-to-noise ratio (SNR) exponent is given by a modified Singleton bound, relating all the system parameters. To demonstrate the practical significance of the theoretical analysis, we present numerical results showing that practical Singleton-bound-achieving maximum distance separable codes achieve the optimal SNR exponent.

In this paper, we propose three different transmit antenna selection schemes with reduced feedback requirement compared with the conventional scheme. In Scheme 1, all the Lt available transmit antennas are divided as equally as possible into two groups. The best single antenna within each group is selected. In Scheme 2, only the best one among Lt antennas is made known to the transmitter, and the other one is selected at random. Scheme 3 is for even Lt, and Lt antennas are divided into multiple subsets each consisting of two adjacent antennas, among which the best subset is selected. Analytical performances of these three schemes with the Alamouti space-time block code (STBC) are derived for flat Rayleigh fading channels. The asymptotic signal-to-noise ratio (SNR) loss of each proposed scheme relative to the conventional transmit antenna selection scheme is quantified. Together with the reduction in feedback requirement, the relative merit of each proposed scheme is delineated. In general, all of the three schemes provide a good trade-off between error performance and feedback requirement. And the application scenario for each scheme is also identified. The results in this paper provide guidance for the design of transmit antenna selection systems with various feedback channel bandwidths, different requirements for quality of service, and specific antenna configuration.

In this paper, we investigate the performance of optimum combining multiple antenna systems in the presence of Rician-faded interferers. We assume that the desired user is subjected to Rayleigh fading but interferers undergo Rician fading. Unlike other approaches addressing optimum combining with Rician fading, we consider the effect of both interference and thermal noise. Our methodology is based on the evaluation of the moment generating function of the signal-to-interference-plus-noise (SINR) ratio at the output of the combiner. Our results are exact, and allow the calculation of the symbol error probability (SEP) for M-PSK signals with arbitrary number of antennas and interferers.

This letter derives the asymptotic symbol error rate (SER) and outage probability of multiple-input multiple-output (MIMO) maximum ratio-combining (MRC) systems. We consider Rayleigh fading channels with both transmit and receive spatial correlation. Our results are based on new asymptotic expressions that we derive for the p.d.f. and c.d.f. of the maximum eigenvalue of positive-definite quadratic forms in complex Gaussian matrices. We prove that spatial correlation does not affect the diversity order but that it reduces the array gain and hence increases the SER in the high SNR regime

An interference-normalized least mean square (INLMS) algorithm for robust adaptive filtering is proposed. The INLMS algorithm extends the gradient-adaptive learning rate approach to the case where the signals are nonstationary. In particular, we show that the INLMS algorithm can work even for highly nonstationary interference signals, where previous gradient-adaptive learning rate algorithms fail.

We consider multiple-input multiple-output (MIMO) transmit beamforming systems with maximum ratio combining (MRC) receivers. The operating environment is Rayleigh fading with both transmit and receive spatial correlation. We present exact expressions for the probability density function (pdf) of the output signal-to-noise ratio, as well as the system outage probability. The results are based on explicit closed-form expressions which we derive for the pdf and cumulative distribution function of the maximum eigenvalue of double-correlated complex Wishart matrices. For systems with two antennas at either the transmitter or the receiver, we also derive exact closed-form expressions for the symbol-error rate. The new expressions are used to prove that MIMO-MRC achieves the maximum available spatial diversity order, and to demonstrate the effect of spatial correlation. The analysis is validated through comparison with Monte Carlo simulations

In this letter we derive tight analytical expressions for the coded bit error rate of MIMO bit-interleaved coded modulation (BICM) in spatially-correlated Rayleigh fading channels. We consider the case where low complexity zero-forcing receivers are employed. The analysis is simpler and more direct than the standard BICM error event expurgation technique, and yields efficient, accurate expressions for the error probability. Based on the analytical results, we obtain the diversity order and show that it is independent of the spatial correlation. Moreover, we show that the presence of spatial correlation induces an SNR loss with respect to i.i.d. channels. We quantify this loss, and show that it is a function of the antenna configuration and the eigenvalues of the spatial correlation matrices, and is independent of the coding and modulation parameters

We consider the optimal performance of noncoherent channel estimation, that is, where the codebook is known to the receiver but the actual transmitted data is not. It is well known that when training data is known to the receiver, the minimum variance of the channel estimation error for unbiased channel estimation is bounded by the Cramer-Rao lower bound. However, in the noncoherent case, where joint estimation of both a continuous channel and discrete data is required, the Cramer- Rao bound is not applicable. We derive a new bound for this mixed multiple parameter estimation problem for flat fading channels, based on the Hammersley-Chapman-Robbins bound for restricted parameters. We show that the new noncoherent bound asymptotically approaches the Cramer-Rao bound with increasing SNR and sequence length. As an example we consider channel estimation for BPSK over a positive real-valued channel. We show that the noncoherent ML detector is asymptotically unbiased and achieves the lower bound with increasing SNR. We also observe that for moderate SNR the noncoherent ML estimator can actually outperform the optimal coherent ML estimator.

This paper considers multiple-input multiple-output (MIMO) antenna systems employing transmit beamforming (BF) with maximum ratio combining (MRC) receivers. Rayleigh fading environments are considered, with both transmit and receive spatial correlation. Exact expressions are presented for the probability density function (p.d.f.) of the output signal-to-noise ratio (SNR), as well as the system outage probability. The results are based on efficient closed-form expressions which we derive for the p.d.f. and c.d.f. of the maximum eigenvalue of double-correlated complex Wishart matrices. The results are validated through comparison with Monte-Carlo simulations, and used to examine the effect of spatial correlation on the SNR p.d.f. and the outage probability

We present a novel, maximum-likelihood (ML), lattice-decoding algorithm for noncoherent block detection of QAM signals. The computational complexity is polynomial in the block length; making it feasible for implementation compared with the exhaustive search ML detector. The algorithm works by enumerating the nearest neighbor regions for a plane defined by the received vector; in a conceptually similar manner to sphere decoding. Simulations show that the new algorithm significantly outperforms existing approaches.

This paper considers low complexity transmission for MIMO bit-interleaved coded modulation (BICM) in spatially-correlated Rayleigh channels. We consider both statistical beam-forming (SB) and spatial-multiplexing with a zero-forcing (ZF) receiver. We derive tight closed-form bit error rate (BER) expressions based on a saddlepoint approximation. We then propose a practical adaptive algorithm which selects, based on the analytical results, the combination of code-rate, modulation format, and MIMO transmission scheme (SB or ZF) that maximizes throughput whilst maintaining a pre-defined BER.

We derive closed-form expressions for the ergodic capacity and symbol error rate (SER) of MIMO beamforming with maximum ratio combining (MRC) receivers in uncorrelated and semi-correlated Rayleigh channels. Our results are exact, finite expressions, applying for arbitrary numbers of antennas, and all SNRs. Based on the analytical results, we examine the effect of spatial correlation on the capacity and SER.

This paper presents new statistical properties of complex noncentral matrix-variate quadratic forms. In contrast to previous results, the expressions do not involve infinite sums over partitions, or matrix-variate polynomials, and are easily and efficiently computable. These properties are used to derive new upper and lower bounds on the ergodic mutual information of double-sided correlated Rician MIMO channels with arbitrary-rank channel mean matrices. The bounds are shown to be tighter than previous reported bounds in the literature

This paper examines type-II ARQ (incremental redundancy) systems over equalized inter-symbol interference (ISI) channels. We study the error rate and throughput performance of hybrid ARQ using convolutional codes, turbo codes and serially concatenated single parity check (SCSPC) codes. SCSPC codes are shown to provide an excellent performance complexity trade-off. Results demonstrate that both convolutional and SCSPC codes can outperform turbo codes in the ARQ framework. This is in direct contrast to previous work on AWGN channels. Finally, we propose a design rule to find good packet lengths for systems based on SCSPC

We present a low complexity adaptive transmission approach for spatially correlated MIMO channels. The proposed scheme adaptively switches between orthogonal space-time block codes (OSTBC) and spatial multiplexing (SM), depending of the channel correlation and SNR. We derive an exact closed-form expression and tight upper bound on the OSTBC capacity in double-correlated channels, and examine the relative capacity of OSTBC and SM in terms of the spatial correlation. We then derive efficient closed-form BER expressions for practical OSTBC transmission employing bit-interleaved coded modulation (BICM). Based on these results, we propose a practical adaptive algorithm which selects the combination of MIMO transmission scheme (OSTBC or SM), and BICM mode, which achieves the highest spectral efficiency whilst satisfying a pre-defined BER

This paper considers automatic gain control (AGC) and quantization for multiple-input multiple-output (MIMO) wireless systems. We examine the effect of clipping and quantization on capacity and bit error rate (BER). We find that even quite low resolution quantizers can perform close to the capacity of ideal unquantized systems. Results are presented for BPSK and M-ary QAM, and for 2 × 2, 3 × 3, and 4 × 4 MIMO configurations. We find that in each case less than 6 quantizer bits are required to achieve 98% of unquantized capacity for SNRs above 15dB.

In this paper we present a novel maximum-likklihood polynomial-time algorithm for noncoherent detection of PAM over fading channels. The algorithm is based on a geometric interpretation of the noncoherent detection metric. This interpretation leads to a novel low complexity decoder based on an angular criterion, rather than the usual Euclidean distance sense. We prove that the ML estimate of the data must lie in a reduced search space which is of log-linear complexity with the block length. We then provide an algorithm that enumerates the codewords and their corresponding metrics in an efficient, recursive manner. We also consider detection of ASK, by combining the maximum-likelihood algorithm with a simple phase estimator.

This paper presents an asymptotic analysis of multisignature code-division multiple access (CDMA) in the presence of frequency-selective channels. We characterize the sum spectral efficiency and spectral efficiency regions for both the optimal and linear minimum mean-squared error (MMSE) multiuser receivers. Both independent and identically distributed (i.i.d). signatures and isometric signatures, which are orthogonal at each transmitter, are considered. Our results are asymptotic as the number of signatures per user and processing gain both tend to infinity with fixed ratio. The spectral efficiency of the MMSE receiver is determined from the asymptotic output signal-to-interference-plus noise ratio (SINR). For isometric signatures, our results rely on approximating certain covariance matrices with unitarily invariant matrices that are asymptotically free. This approximation is shown to be very accurate through comparison with both simulation and an "incremental-signature" analysis, which can be used to compute asymptotic moments. Also, a novel proof of the convergence of the empirical spectral distribution of the signal correlation matrix is presented. From these results, we derive the optimal coding-spreading tradeoff, which maximizes the MMSE spectral efficiency, for the case of a single user with multiple i.i.d. signatures. Simulation studies demonstrate that the asymptotic results accurately predict the performance of finite-size systems of interest. The resulting expressions are used to highlight and infer properties of the multisignature CDMA system, including the benefit of orthogonal relative to i.i.d. signatures, and the tradeoff between spectral efficiency and the versatility of providing a variable data rate service through multiple signatures

We present a unified large-system analysis of linear receivers for a class of random matrix channels. The technique unifies the analysis of both the minimum-mean-squared-error (MMSE) receiver and the adaptive least-squares (ALS) receiver, and also uses a common approach for both random independent, identically distributed (i.i.d.) and random orthogonal precoding. We derive expressions for the asymptotic signal-to-interference-plus-noise ratio (SINR) of the MMSE receiver, and both the transient and steady-state SINR of the ALS receiver, trained using either i.i.d. data sequences or orthogonal training sequences. The results are in terms of key system parameters, and allow for arbitrary distributions of the power of each of the data streams and the eigenvalues of the channel correlation matrix. In the case of the ALS receiver, we allow a diagonal loading constant and an arbitrary data windowing function. For i.i.d. training sequences and no diagonal loading, we give a fundamental relationship between the transient/steady-state SINR of the ALS and the MMSE receivers. We demonstrate that for a particular ratio of receive to transmit dimensions and window shape, all channels which have the same MMSE SINR have an identical transient ALS SINR response. We demonstrate several applications of the results, including an optimization of information throughput with respect to training sequence length in coded block transmission

This correspondence considers block detection for blind wireless digital transmission. At high signal-to-noise ratio (SNR), block detection errors are primarily due to the received sequence having multiple possible decoded sequences with the same likelihood. We derive analytic expressions for the probability of detection ambiguity written in terms of a Dedekind zeta function, in the zero noise case with large constellations. Expressions are also provided for finite constellations, which can be evaluated efficiently, independent of the block length. Simulations demonstrate that the analytically derived error floors exist at high SNR

This paper considers the ergodic capacity of spatially-correlated Rician MIMO channels. We address the case where the Rician component has a single dominant path and where the correlation occurs at one end of the MIMO link. We derive upper bounds which are tight for all signal to noise ratios (SNR), and lower bounds which converge to the exact capacity at high SNR. For frequency-flat channels we investigate the capacity variation with Rician K-factor and correlation. For frequency-selective channels we also examine the effect of the total angle spread

Large system analysis has been used extensively in recent years to evaluate the performance of code division-multiple access (CDMA) and multi-input/multi-output (MIMO) communications systems. A key feature of this analysis is application of results on eigenvalue distributions and moments of large random matrices. These results enable the efficient computation of large system performance measures, such as spectral efficiency and probability of error, which are far more difficult to compute for finite-size systems. The large system results typically give an accurate prediction of the performance of finite-size systems, and offer important insights into system behavior. We give an overview of large system results for some different communications system models. Our emphasis is on techniques used previously by the authors to evaluate the performance of multi-carrier CDMA with the optimal linear receiver.

In this paper we derive tight upper and lower bounds on the MIMO capacity in correlated Rician fading channels. We assume that the receiver has perfect knowledge of the channel, and the transmitter has no knowledge (instantaneous or statistical). We examine two common power normalization models, and show how the capacity changes with Rician K-factor and with the amount of correlation.

This paper presents new statistical properties of complex noncentral Wishart matrices. The properties are then used to derive bounds on the ergodic capacity of single-sided correlated Rician MIMO channels with arbitrary-rank channel mean matrices. We present upper and lower bounds which are computationally efficient and tight

We consider a large system analysis of the minimum-mean-squared-error (MMSE) receiver and the adaptive least-squares (ALS) receiver for a class of random matrix channels. We give a relationship between the transient/steady-state SINR of the ALS and the MMSE receivers. We demonstrate that for a particular ratio of receive to transmit dimensions and window shape, all channels which have the same MMSE SINR, would have an identical transient ALS SINR response

This paper presents performance bounds for block-based detection of PAM and QAM transmitted over non-coherent channels. Such channels give rise to inherent detection ambiguities since multiple possible transmit sequences can have the same likelihood. The number of ambiguous sequences is a function of the block length. In this paper, we derive the probability of detection error in terms of a Dedekind zeta function of the block length, for infinite-sized constellations and zero noise. We also provide expressions for finite constellations which can be evaluated in polynomial time with the constellation size, as opposed to checking all possible sequences

We consider a low-complexity adaptive MIMO transmission approach for spatially correlated channels. The proposed scheme adaptively switches between different transmission modes depending on the changing channel conditions, as a means to enhance system capacity. Each mode is a combination of a transmission technique (i.e. statistical beamforming, double space-time transmit diversity and spatial multiplexing) and a modulation/coding scheme. We first motivate our adaptive algorithm by deriving new closed-form capacity expressions, and demonstrating significant information theoretic improvements over non-adaptive transmission. We then present a practical method to switch between different modes, based on the channel statistics. Our approach is shown to yield significant improvements in spectral efficiency for typical channel scenarios.

We consider a layered space-frequency (LSF) extension to bit-interleaved coded modulation (BICM) for MIMO-OFDM systems. We derive tight analytical bounds for the coded BER when using zero-forcing (ZF) detectors. The analysis does not rely on standard BICM expurgation techniques, and provides exact expressions for the codeword pairwise error probability at high SNR. We show that the LSF extension achieves the same diversity order as non-layered systems, while also achieving significant cant SNR gains when the number of transmit antennas is large. We quantify the SNR gain and show that it is a function of the antenna configuration only, and is independent of the modulation and coding parameters. We also present simulation results for MIMO extensions to IEEE 802.11a OFDM WLANs.

This work considers multiple-input multiple-output bit-interleaved coded modulation (MIMO-BICM) with linear zero-forcing (ZF) receivers. We derive the link-level capacity (LLC) under ideal fast-fading conditions, and show that it approaches the maximum-likelihood (ML) LLC as the number of receive antennas approach infinity. We also derive tight analytical bounds on the coded bit-error rate, and prove that with N/sub t/ transmit and N/sub r/ receive antennas, the diversity order is N/sub r/-N/sub t/+1 multiplied by the free Hamming distance of the convolutional code. For the case of a ML receiver, we show that a tight bound is not possible, in general. Our analysis provides insights to explain the relative performance of the ZF and ML receivers. Finally, we validate the analytical results and assess the performance in a practical environment with orthogonal frequency-division multiplexing and channel estimation.

This paper considers properties of the extrinsic information transfer (EXIT) functions of turbo equalized intersymbol interference channels and finite-impulse response precoders. An analytic expression is derived for the maximum value of the EXIT function of the equalizer. Using this parameter, a design strategy is proposed for allocating redundancy between the equalizer and the decoder. The key quantities are pilot-symbol rate and code puncturing, for fixed overall data and symbol rates.

This paper considers the capacity of spatially correlated Rician multiple-input multiple-output (MIMO) channels. We consider the general case with double-sided correlation and arbitrary rank channel means. We derive tight upper and lower bounds on the ergodic capacity. In the particular cases when the numbers of transmit and receive antennas are equal, or when the correlation is single sided, we derive more specific bounds which are computationally efficient. The bounds are shown to reduce to known results in cases of independent and identically distributed (i.i.d.) and correlated Rayleigh MIMO channels. We also analyze the outage characteristics of the correlated Rician MIMO channels at high signal-to-noise ratio (SNR). We derive the mean and variance of the mutual information and show that it is well approximated by a Gaussian distribution. Finally, we present numerical results which show the effect of the antenna configuration, correlation level (angle spreads), Rician K-factor, and the geometry of the dominant Rician paths.

In this paper, we analyze a linear multiuser receiver for code-division multiple-access systems that is based on a matrix polynomial expansion. We focus on the receiver where the polynomial coefficients are chosen to minimize the mean squared error at the output and observe that the resultant coefficients are also signal-to-interference ratio maximizing. We present a simple derivation for the (known) large system coefficients and signal-to-interference ratio of this optimal multistage receiver and make a significant step toward a direct derivation of Honig and Xiao's recursive expression for this large system signal-to-interference ratio. Finally, we extend these results to take into account arbitrary power distributions.

Tight analytical bounds on the coded bit error rate are derived for a MIMO bit-interleaved coded modulation (BICM) system with a zero forcing receiver. We show that a minimal expurgated bound exists when using Gray-labelled constellations. We also show that with N/sub t/ transmit and N/sub r/ receive antennas, the diversity order is N/sub r/-N/sub t/+1 multiplied by the free distance of the code. For the maximum likelihood receiver, we demonstrate that expurgation does not lead to a tight bound. The analysis provides insight into the relative performance of the MIMO-BICM ZF and ML receivers.

In this paper we derive asymptotic performance measures for multiuser receivers in the uplink of multi-carrier (MC) CDMA communication systems with multiple signatures per user. We examine spectral efficiency regions of multi-signature CDMA, for both the optimal and optimal-linear receivers. We also derive an approximate expression for the asymptotic average signal to interference and noise ratio at the output of the optimal-linear multiuser receiver in the case of two users. Simulation studies demonstrate that the asymptotic results closely predict performance of practical finite systems.

We derive asymptotic performance measures for peer-to-peer multi-carrier CDMA networks with low data rate feedback channels between transmitter-receiver pairs. We derive expressions for the asymptotic average signal to interference and noise ratio at the output of the optimal linear multi-signature receiver using a simple feedback scheme in the single-user case, and an approximate ,expression in the two-user case. The asymptotic results closely predict performance of practical finite systems. We demonstrate that the simple feedback scheme yields most gain for either low system loads or low SNR. The power saving is in the order of 1-2 dB per signature for a wide range of system loads and SNRs.

We characterize the asymptotic spectral efficiency of the linear minimum mean squared error (LMMSE) receiver for multiuser multisignature multicarrier (MC) code-division multiple access (CDMA) communication systems. We consider signatures which are orthogonal at each transmitter. Our results are asymptotic as the number of signatures per user and processing gain both tend to infinity with fixed ratio. Our results rely on approximating covariance matrices with unitarily invariant matrices that are asymptotically free.

This paper presents a new low-complexity multicarrier modulation (MCM) technique based on lattices which achieves a peak-to-average power ratio (PAR) as low as three. The scheme can be viewed as a "drop in" replacement for the discrete multitone (DMT) modulation of an asymmetric digital subscriber line modem. We show that the lattice-MCM retains many of the attractive features of sinusoidal-MCM, and does so with lower implementation complexity, O(N), compared with DMT, which requires O(NlogN) operations. We also present techniques for narrowband interference rejection and power profiling. Simulation studies confirm that performance of the lattice-MCM is superior, even compared with recent techniques for PAR reduction in DMT.

This paper considers a multicarrier (MC) code-division multiple-access system where each user employs multiple signatures. The receiver is linear and minimizes the mean square error of the data estimate. Both multiple-user and single-user systems are considered, as well as single and multiple signatures per user. In each case, an asymptotic analysis is used to derive the output signal-to-interference-plus-noise ratio (SINR) as a function of the system loading, the noise power, and the fading properties of the channel. Asymptotic in this case means that the number of independent subcarriers and number of signatures per user each tends to infinity with fixed ratio. The associated bit-error rate (BER) is evaluated for binary phase-shift keying symbols. Simulations show that the asymptotic SINRs and BERs derived in each case are accurate for realistic finite systems.

This paper analyzes a fully adaptive maximum-likelihood sequence estimator (MLSE) equalizer in fast fading channel conditions. The receiver adaptively estimates the channel state information, and also adapts to learn the channel fading statistics. The equalizer is analyzed using pairwise error probabilities to derive lower bounds on performance. A decision delay adaption rule is proposed, based on the bit-error rate analysis. With this new rule, the fully adaptive MLSE equalizer is shown to outperform existing fixed-delay equalizers when channel statistics are unknown. Simulation studies confirm that the performance is close to the analytic bounds.

The paper presents a new multicarrier modulation (MCM) technique based on lattices which achieves a peak-to-average power ratio (PAR) as low as 3. The scheme can be viewed as a 'drop in' replacement for the discrete multitone (DMT) modulation of an ADSL modem. Performance is up to 8.5 dB better than standard DMT in amplifier-clipped conditions. Moreover, the new technique has a lower implementation complexity, O(N), compared with DMT which requires O(N log N) operations. Simulation studies confirm that the performance of the lattice-MCM is superior even compared to recent techniques for PAR-reduction in DMT.

We present an asymptotic analysis of a multi-signature multi-carrier CDMA communications system. Such a system is suited to scalable data rate services with decentralized control. Specifically, we derive the asymptotic SINR at the output of a multi-user linear minimum mean squared error (LMMSE) receiver and the asymptotic sum spectral efficiency of both the LMMSE and optimal receivers. Simulation studies demonstrate that the asymptotic results closely predict the performance of practical finite systems.

This paper analyzes a fully adaptive MLSE equalizer in fast fading channel conditions. The receiver requires no channel state information, and even adapts to learn the channel fading statistics. The equalizer is analyzed using pairwise error probabilities to derive lower bounds on performance for MPSK signals. Simulation studies confirm that the analytic bounds are close to the true performance. A new decision delay adaption rule is proposed, based on the bit error rate analysis. With this new rule, the fully adaptive MLSE equalizer is shown to outperform existing fixed-delay equalizers when channel statistics are unknown.

The paper considers performance and design issues for turbo equalizers. Analytic expressions are derived for the mutual information convergence point of the turbo equalizer. The BER is then found analytically. Results are obtained for both fixed and fading channels, and in conditions of both perfect channel state information as well as unknown estimated channels. Finally, we introduce design rules for adaptive turbo equalizers based on our analysis. The rules give optimal combinations of pilot rate and code puncturing for a range of fading and SNR conditions.

In this paper we derive asymptotic performance measures for multiuser receivers in multi-carrier CDMA communication systems. We consider both single-code-per-user and multi-code cases. Specifically, we derive the asymptotic average SINR and BER at the output of a multiuser LMMSE receiver. Simulation studies demonstrate that the asymptotic results closely predict performance of practical finite systems.

We analyze the performance of a second-order linear multistage multiuser code-division multiple-access receiver. The receiver's filtered output is designed to converge to that of the linear minimum mean-squared error solution as the number of stages increase. Our analysis is based on a related second-order stationary iterative solution method. We derive the large system output signal to interference-plus-noise ratio for each stage. We use this result to perform a numerical optimization with respect to the two second-order parameters of our receiver. Within this iterative framework, we can achieve performance extremely close to the optimal linear multistage multiuser receiver.

We analyse the optimal linear multistage receiver based on a weighted matrix polynomial expansion. We prove that the optimal linear multistage receiver which minimises the mean squared error for a particular stage also maximises the signal-to-interference-plus-noise ratio for a particular stage. We present an alternative derivation of the large system signal-to-interference-plus-noise ratio. We observe an important link between the optimal linear multistage receiver and the multistage reduced rank Wiener filter receiver.

We derive upper bounds on the symbol error probability for a communication system that sends quadrature amplitude modulated data over a frequency-flat Rayleigh fading channel. We first derive simple error bounds in terms of a key parameter, namely, the channel estimation error variance. We move on to derive expressions for the this parameter for a pilot symbol assisted channel estimation scheme. The estimation error variance, and thus the symbol error probability, are expressed succinctly in terms of the statistics of the channel fading process, the frequency of insertion of pilot symbols, and the average signal-to-noise ratio.

In this paper, we derive an expression for the signal to interference-plus-noise ratio of a linear multistage parallel interference cancellation receiver. We focus on a linear multistage receiver which converges to the linear minimum mean-squared error receiver as the number of stages increases. The signal to interference-plus-noise ratio is given in terms of the system loading, the partial cancellation factor, the number of stages, and the signal-to. noise ratio. Our expression also allows a simple approximation for the bit error rate at each stage. Finally, we perform a numerical optimization to maximize the signal to interference-plus-noise ratio expression with respect to the partial cancellation factor of the resulting linear multistage receiver.

We derive an expression for the signal-to-interference-plus-noise ratio (SINR) of a second order iterative receiver. We focus on a second order linear iterative receiver which converges to the linear minimum mean squared error receiver as the number of stages increases. The SINR is given in terms of the system loading, the two receiver parameters, the number of stages and the signal-to-noise ratio. We can now estimate the bit error rate performance of iterative receivers. Finally, we perform a numerical optimisation of the SINR with respect to the parameters of the resulting second order linear iterative receiver. Within this iterative framework we can achieve performance close to the optimal linear multistage receiver.

Recently a number of modified MMSE receivers have been efficiently applied to code-division multiple-access (CDMA) communications with dynamic fading channels. These receivers can successfully cope with multiple access interference (MAI) but are limited to BPSK signals. This paper presents new adaptive implementations of MMSE receivers for higher order signals in multi-user environments. High-order signal constellations, e.g. MQAM, have been extensively investigated in single-user fading channels due to their high spectral efficiency. This paper provides performance evaluations and analysis for the proposed adaptive multiuser receiver. It also presents a new computationally efficient adaptive algorithm for these high-order signal constellations.

We derive an expression for the signal to interference-plus-noise ratio of a multistage parallel interference cancellation receiver. We focus on a linear multistage receiver employing partial parallel interference cancellation which converges to the linear minimum mean squared error receiver as the number of stages increase. The signal to interference-plus-noise ratio is given in terms of the system loading, the partial cancellation factor, the number of stages and the background noise variance. The expression allows a simple approximation for the bit error rate at each stage. Finally, we verify and apply our results to optimise the signal to interference-plus-noise ratio of the resulting linear multistage receiver.

This letter compares pilot-aided phase-shift keyed (PSK) and differential PSK (DPSK) modulation when using new maximum a posteriori joint channel estimation and equalization receivers with frequency-selective fast-fading channels. We conclude that pilot-aided PSK has superior bit-error rate performance in this case. However, at low signal-to-noise ratio, performance is similar, and DPSK is competitive due to reduced receiver complexity.

This paper presents a new fractionally-spaced maximum a posteriori (MAP) equalizer for data transmission over frequency-selective fading channels. The technique is applicable to any standard modulation technique. The MAP equalizer uses an expanded hypothesis trellis for the purpose of joint channel estimation and equalization. The fading channel is estimated by coupling minimum mean square error techniques with the (fixed size) expanded trellis. The new MAP equalizer is also presented in an iterative (turbo) receiver structure. Both uncoded and conventionally coded systems (including iterative processing) are studied. Even on frequency-flat fading channels, the proposed receiver outperforms conventional techniques. Simulations demonstrate the performance of the proposed equalizer.

This paper considers new maximum a posteriori (MAP) receivers for phase-shift keyed (PSK) digital mobile communication systems. The focus is on the benefits of pilot-aided PSK over differential PSK (DPSK) when using these receivers in fast fading channel conditions. For fading channels, DPSK is typically employed in preference to PSK because it avoids the need for accurate channel tracking. However, for both the PSK and DPSK MAP receivers considered here, non-coherent quadrature analog front-ends are used, with channel estimation being performed digitally in conjunction with data estimation. Channel estimates are formed along each branch of an expanded MAP trellis. In the case of absolutely encoded PSK, phase ambiguity is resolved using pilot symbols. For the new MAP receivers, the choice between PSK and DPSK is no longer clear. This paper shows that pilot-aided PSK outperforms DPSK for these new receivers, despite the SNR penalty associated with pilot symbols. From a computational point of view however, the new MAP DPSK receiver developed in this paper is more efficient.

This paper presents a new algorithm for on-line identification of hidden Markov model (HMM) parameters. The scheme is gradient based, and provides parameter estimates which recursively maximise the likelihood function. It is therefore a recursive maximum likelihood (RML) algorithm, and it has optimal asymptotic properties. The only current on-line HMM identification algorithm with anything other than suboptimal rate of convergence is based on a prediction error (PE) cost function. As well as presenting a new algorithm, this paper also highlights and explains a counter-intuitive convergence problem for the current recursive PE (RPE) algorithm, when operating in low noise conditions. Importantly, this problem does not exist for the new RML algorithm. Simulation studies demonstrate the superior performance of the new algorithm. compared to current techniques.

Blind channel equalization has been a very active research topic due to its potential application in mobile communications and digital TV systems. In this paper, we present a new blind zero-forcing equalizer that utilizes second order statistics from the multi-channel configuration. The algorithm is simple and relies only on nullspace decomposition. It can actively select the desired delay of the equalizer output signal. The performance of this new algorithm is demonstrated through simulation examples.

This letter presents a new method for identification of fast-fading mobile channels (for which combinations of vehicle speed and carrier frequency give rise to significant fading). Our new algorithm estimates both the channel statistics and the time-varying channel impulse response on-line. Simulation studies demonstrate the performance of the new estimator which couples an augmented Kalman filter with a recursive least squares algorithm.

We present a new method for on-line identification of time-varying FIR channels. Two conditionally coupled estimators are proposed. In both cases an augmented-state adaptive Kalman filter is employed for tracking the time-varying channel and estimating the mean channel response. Coupled to the Kalman filter is an algorithm for estimating the parameters of the underlying auto-regressive (AR) model which describes the time evolution of the channel. For the first coupled estimator, we propose a new recursive least squares algorithm for estimation of these AR parameters directly from the channel observations. An alternative algorithm based on estimation of the channel covariance is used in the second coupled estimator. A simulation example demonstrates the performance of the proposed estimators.

This paper considers on-line identification of hidden Markov models via multiple-prediction-horizon recursive prediction error (RPE) methods. Working with multiple-prediction-horizons ensures that there is consistent parameter estimation, under appropriate excitation conditions. Simulation studies are included to illustrate the advantages of the proposed approach when compared to standard methods (which do not ensure consistent parameter estimation).

Kalman filtering (KF) and hidden Markov model (HMM) signal processing techniques are coupled to demodulate signals transmitted through noisy fading channels. The demodulation scheme presented can be applied to both digital M-ary differential phase shift keyed (MDPSK) and analog frequency modulated (FM) signals. Adaptive state and parameter estimation algorithms are devised based on the assumption that the transmission channel introduces time-varying gain and phase changes, modelled by a stochastic linear system, and has additive Gaussian noise. Our technique is to use an HMM filter, for signal estimation, coupled with a KF, for channel parameter tracking. The approach taken can easily be generalised for other transmission schemes, such as continuous phase modulated (CPM) signals.>