The provision of Quality of Experience (QoE) for wireless video streaming has become a necessity. From this perspective, we design a QoE-aware scheduling (QoEAS) scheme for video streaming over IEEE 802.11n/ac networks. We consider an application scenario where videos are streamed in an area with high density of users. To improve the streamed video quality, we enhance the conventional gradient based scheduling scheme (U'R) by incorporating the packet delay and channel transmission rate with video packet importance index in scheduling. This index is derived based on the gradient of the QoE function for video, which accurately reflects the usefulness of a packet in enhancing the video quality. To be compatible to practical networks such as IEEE 802.11n/ac, the packet importance index is embedded in the Type-of-Service (ToS) field of IP header and is employed at Media Access Control (MAC) layer to perform scheduling. The proposed QoEAS significantly enhances the streamed video quality and achieves good fairness among users. It surpasses the conventional scheme by as much as 5 dB in Peak Signal-to-Noise Ratio (PSNR) at the lower 10 percentile of the users. To demonstrate the superiority and practicability of QoEAS, we also set up a lab test bed on a real 802.11ac network. Compared to conventional schemes, the proposed QoEAS shows notable QoE enhancement in lab test.

This paper uses a multi-channel spatial Aloha model to describe a distributed autonomous wireless network where a group of transmit-receive pairs (users) share multiple collision channels via slotted-Aloha-like random access. The design objective is to enable each autonomous user i to select a channel c_i and decide a medium access probability (MAP) q_i to improve its throughput, while providing a certain degree of fairness among the users. Game theoretic approaches are applied, where each user i is a player who chooses the strategy (c_i,q_i) to improve its own throughput. To search for a Nash Equilibrium (NE), a Multi-Leader Stackelberg Game (MLSG) is formulated to iteratively obtain a solution on each dimension of the (c_i,q_i) strategy. Initially, multiple Stackelberg leaders are elected to manage the MAPs of all players. Then under the resulting MAP profile, each player iteratively chooses its channel to improve its throughput. An Oscillation Resolving Mechanism (ORM) is further proposed to stabilize the design in some special cases where the operating points of some players in a local region would oscillate between the two dimensions of the myopic search. Compared to existing methods of pre-allocating MAPs, the MLSG game further improves the overall network throughput by iteratively tuning the MAPs toward max-min throughput in each subnet. Simulation results show that the MLSG game gradually improves the total throughput until reaching a NE, which also provides good throughput fairness for the players.

Knowing channel sight condition is important as it has a great impact on localization performance. In this paper, a RSS-based localization algorithm, which jointly takes into consideration the effect of channel sight conditions, is investigated. In our approach, the channel sight conditions experience by a moving target to all sensors is modeled as a hidden Markov model (HMM), with the quantized measured RSSs as its observation. The parameters of HMM are obtained by an off-line training assuming that the LOS/NLOS can be identified during the training phase. With the HMM matrices, a forward-only algorithm can be utilized for real time sight conditions identification. The target is localized by extended Kalman Filter (EKF) by suitably combining with the sight conditions. Simulation results show that our proposed localization strategy can provide good identification to channel sight conditions, hence results in a better localization estimation.

In this paper a new method is proposed for classifying randomly deployed sensor nodes over an area of interest into distinctive categories. The problem of event region and event boundary detection in Wireless Sensor Networks (WSNs) is addressed. Particularly, analysis is provided for a scenario whereby an area of interest featuring two distinctive phenomena is being monitored with a randomly deployed network of wirelessly connected sensor nodes. Each sensor node in the network is asked to acknowledge whether or not it classifies itself as an event-region node based only on its own environment reading. The key decision factor employed in this approach is the statistical attributes of received signal distribution at each sensor node. Applying this algorithm results in reducing the required bandwidth for transmitting the environmental reading to the base station to be proportional to the size of the event-region. This is opposed to other approaches where the required bandwidth is proportional to the size of the entire network.

In this paper, we propose a novel mobile terminal (MT) tracking approach performed at the fixed terminal (FT). The method involves three steps: motion-dependent parameters estimation, extended Kalman filter (EKF) based tracking and enhanced estimation accuracy through additional partial location information. An algorithm based on the space-time correlation of the received signal is first proposed to estimate the radial velocity (both speed and direction) of the MT. The EKF-based tracking is next adopted to estimate the current location of the MT by using the estimated parameters and the previous location estimate. Finally, additional high-resolution angle-of-arrival (HR-AoA) estimate is applied and we show how this partial location information can be fused with the tracking results to further improve the tracking accuracy. The performances of the algorithms are studied through simulations.

Aloha games with spatial reuse study the interactions among a group of selfish transmit-receive pairs which share a common collision channel using slotted-Aloha-like protocols. These Tx-Rx pairs are allowed to reuse the channel if they cause negligible interference to each other. Our work in [1] has proved the existence of a Least Fixed Point (LFP) which is the most energy-efficient operating point as well as the unique Nash Equilibrium (NE) in such games. Based on the earlier derived conditions for the stability of this NE and the way to converge to this NE, it is possible to design a self-adaptive algorithm for the players to self-adjust their target rates based on a set of pre-installed rules so that the network always achieves Pareto optimal bandwidth utilization. In this paper, we implement such an algorithm in a fully distributed manner, which requires no information exchange among the players. Each player repeatedly measures its current throughput and uses the measured value to make myopic best response to the current channel idle rate. Our simulations show that the system indeed achieves close to Pareto optimal performance while guaranteeing a certain degree of fairness. The algorithm is robust and can handle various practical issues such as the dynamic arrival/departure of players, parameter estimation errors, etc.

Aloha games study the transmission probabilities of a group of non-cooperative users which share a channel to transmit via the slotted Aloha protocol. This paper extends the Aloha games to spatial reuse scenarios, and studies the system equilibrium and performance. Specifically, fixed point theory and order theory are used to prove the existence of a least fixed point as the unique Nash equilibrium (NE) of the game and the optimal choice of all players. The Krasovskii's method is used to construct a Lyapunov function and obtain the conditions to examine the stability of the NE. Simulations show that the theories derived are applicable to large-scale distributed systems of complicated network topologies. An empirical relationship between the network connectivity and the achievable total throughput is finally obtained through simulations.

Fair and efficient subcarrier assignment for an infrastructure-based cellular OFDMA network is a challenging problem due to interferences from neighboring cells. In this paper, we investigate this problem using potential game theory, where the utility function adopted is meant for minimizing the co-channel interferences among different players. Each of these players is considered to be a cell with a central base station (BS) and its multiple mobile stations (MS) in a downlink scenario. Under such formulation, we establish the potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game, which can be achieved via certain strategy dynamics such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and present numerical results to evaluate the performance of our game. Improvement in efficiency and fairness is observed in this study.

This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.

We use a Bayesian game-theoretic approach to model transmission control in energy-harvesting wireless sensor networks. In general, the energy state of an energy-harvesting sensor varies more dramatically with time as compared to traditional battery-powered sensors. Therefore, each energy-harvesting sensor is aware of its instantaneous energy state, which is modeled as its private information. Each sensor decides its transmission strategy according to its belief of its opponents' energy states. There exists a Bayesian Nash equilibrium (BNE) where a sensor with energy higher than its energy threshold will decide to transmit at fixed power, and wait otherwise. We show how each sensor determines its threshold to maximize its utility function. Moreover, we show via simulations that the performance of the Bayesian game model is close to that of a perfect-information game where energy states are common information to all sensors. In addition, since the proposed Bayesian game has the advantage of requiring less information exchange overhead, it seems to be more feasible to implement than the perfect-information game.

To realize opportunistic spectrum access, spectrum sensing is applied to detect the presence of spectrum holes. If secondary radios (SRs) randomly or sequentially sense the channels until a spectrum hole is detected, significant amount of the scarce spectrum resource will be wasted, since SRs transmit only after a decision has been made. On the other hand, with the use of an intelligent predictive method, SRs can learn from the past activities of each channel to predict the next channel state. By prioritizing the order in which channels are sensed according to the channels availability likelihoods, the probability that an SR gets a channel upon its first attempt significantly increases, and thus reduces the possible waste. This paper introduces a learning-based hidden Markov model (HMM) to predict the channel activities. Simulation results show that the proposed HMM can predict the channel activities with high accuracy after sufficient training. Our algorithm predicts the availability of the channels by only making use of the current state of the spectrum. Furthermore, by incorporating the outcome of the actual channel sense, our algorithm is able to make self-regulation before next decision, so that errors will not propagate.

We study power and rate adaptation for cognitive radios in fading channels, with the objective to maximize the average spectral efficiency of the secondary user (SU) transmitter. The average transmit power and bit error rate (BER) constraints of the SU is considered, together with either the short-term or the long-term outage constraint over the channel state of the primary user (PU). In each case, the optimal power and rate solutions are derived. Unlike previous works on power and rate adaptation for cognitive radios, in this work the cochannel interferences between the SU and PU are explicitly modeled and related to their respective average BER and outage requirements, as well as their respective power and rate variables. Numerical results are presented to provide insights into the dynamics of the power and rate solutions.

In opportunistic spectrum access (OSA), secondary radios (SRs) are allowed to access the channel whenever primary radios (PRs) are not transmitting. The PR's spectrum activities are normally assumed to be a 2-state continuous Markov on-off process which can be modeled as two independent exponential random variables. On the other hand, some simulations prefer using a 2-state discrete Markov chain. As SRs periodically sense the channel to determine its availability before transmitting, maintaining the same false alarm and missed detection probabilities is necessary but still insufficient when discretizing the continuous PR on-off process. Earlier work has shown that type II missed detection error, which is a function of spectrum sensing period, occurs because PR, which is sensed to be inactive in the last sensing duration, can become active before the next spectrum sensing is performed. Hence, it is insufficient to simply perform simulation at the time stamp of spectrum sensing period as information about the type II missed detection error will be lost. This paper looks into the context of spectrum sensing on how we should select the time stamp of the simulation, i.e., the transition probabilities of the 2-state discrete Markov chain, so as to approximate the 2-state continuous Markov process without losing any valuable information. We first derive the expression for type II missed detection error based on the discrete PR on-off model. Then we present the method to decide the time stamp of the simulation so that type II missed detection probability is kept within a given error bound. The same approach can be generalized to other probability distributions of the spectrum activities.

In this paper, we propose a novel algorithm to improve the accuracy in estimating the angle-of-arrival (AoA) when the MUSIC (MUltiple SIgnal Classification) algorithm is used. An optimal precoder, with the objective to minimize the estimation errors of the AoAs, is first derived. However, to compute the optimal precoder requires the channel state information (CSI) exclusive of the receiver array, which cannot be separately estimated practically. A more feasible precoder design approach, which leverages on the feedback instantaneous CSI estimated at the receiver, is next proposed. Using the ideal optimal design to benchmark the performance, our simulation shows that the proposed practical precoder can achieve near-optimal performance, and both can achieve about 4-6 dB improvement in signal-to-noise ratio (SNR) compared to the case when only MUSIC algorithm is applied without precoding. Finally, the performance of the AoA estimator under channel estimation errors is studied through simulation, to demonstrate the robustness of the proposed approach.

Evolutionary algorithms like genetic algorithms and ACO are potential candidates for solving any NP-hard problem, because of their ability to obtain acceptable suboptimum (or sometimes could be the optimum) solutions. This paper proposes an Ant Colony Optimization (ACO) based algorithm to solve the centralized resource allocation problem of a multicell multiuser OFDMA network. The proposed ACO is assisted by a water filling algorithm for power allocation. Two metrics used in ACO algorithms: the visibility and the trail intensity are defined so that they are suitable to evaluate the solution. Visibility is used to select subcarriers and power which increase the total transmitted bit of the cell while trail intensity gives solutions which decrease the inter-cell interference. Simulation results show that with these definitions, the proposed algorithm is working successfully and increases the total network transmitted bits without increasing the maximum transmit power level.

Two adaptive joint power and bandwidth control schemes are proposed for multiple secondary user (SU) transmitters to optimize the spectral efficiency in cognitive radio transmission through spectrum sharing. By exploiting agile bandwidth transmission strategy for cognitive radio users, we present a unified solution to two problems of joint power/rate control and joint power/bandwidth control in dynamic spectrum allocation. Our main objective is to maximize the average spectral efficiency of the commonly in-used portion of the frequency band, subject to the tolerable interference limit at the primary user (PU) that is present. The proposed schemes are applicable to many scenarios, for examples, where two or more SUs are accessing the same frequency band with equal right, or where two or more SUs are accessing the frequency spectrum used by a PU who has a higher priority. Simulations results are presented to show that the proposed suboptimal algorithm also achieves near optimal spectral efficiency.

We study and propose joint power control and cell-site selection schemes for cognitive cellular radios in fading channels. New analytical result on the cognitive radio cell coverage is presented in terms of the outage probability requirement of the primary cellular radio user. A new interference model for the secondary user (SU) is proposed, which includes the transmit powers from all the primary radio (PR) system co-channel base stations, as well as the transmit powers from multiple secondary transmitters. Joint power control and cell-site selection schemes are presented to maximize the total throughput of the SUs, and to guarantee the quality-of-service (QoS) of the primary cellular radio user in terms of outage probability.

This paper addresses relay precoder designs for amplify-and-forward MIMO relay networks with imperfect channel state information (CSI). We first derive the capacity of a MIMO relay network with imperfect CSI. Two relay precoding schemes are then proposed - Scheme I maximizes the upper bound of the capacity obtained by applying Jensen's equality, whilst scheme II simply ignores the error of CSI of the channel from the relay to the destination. Numerical results show that, the capacity increases with the correlation coefficients between the CSI known to the estimating nodes and the CSI known to other nodes. Furthermore, the correlation coefficient of the channel from the source to the relay has more impact on the capacity than the channel from the relay to the destination. Numerical results also show that, the proposed relay precoder Scheme I achieves better capacity than Scheme II and the existing scheme, while Scheme II in some cases performs better than the existing scheme.

We study and propose power control schemes for cognitive radios in Nakagami fading channels. A general model is adopted, which includes the effects of transmit power control from the primary user (PU) transmitter, as well as the transmit power control from multiple secondary user (SU) transmitters, to the PU and each SU. We found that for high signal-to-interference-ratio (SIR) case in Nakagami and Rayleigh fading channels, the outage probability constraint can be upper bounded by an equivalent interference constraint, and the problem for maximizing the total SU spectrum utility can be written as a convex optimization problem which can be solved efficiently. An iterative power control scheme is also presented to maximize the total spectrum utility of the SUs, and to guarantee the quality of service (QoS) of the PU in terms of outage probability.

This paper studies the relay precoding design for a MIMO relay network, where the relay only possesses imperfect channel state information (CSI). We consider a downlink non- regenerative MIMO relay network comprised of a base station (BS, or the source S), a fixed relay (the relay R) and a mobile station (MS, or the destination D). We model the discrepancy between the CSI of the R-D link available at the relay and the actual R-D link gain as a Gaussian random matrix. An upper bound of the mutual information of the considered MIMO relay network is first obtained assuming imperfect CSI knowledge of the R-D link at the relay. The relay precoder to maximize this upper bound is then derived. Numerical results show that by choosing a proper feedback rate, the proposed precoding design is able to achieve ergodic capacity nearly approaching that of the optimal precoder obtained under perfect CSI if a=f_d T <0.01. With fewer antennas used, the loss in capacity is less significant.

A novel channel representation for a two-hop decentralized wireless relay network (DWRN) is proposed, where the relays operate in a completely distributive fashion. The modeling paradigm applies an analogous approach to the description method for a double-directional multipath propagation channel, and takes into account the finite system spatial resolution and the extended relay listening/transmitting time. Specifically, the double-directional information azimuth spectrum (IAS) is formulated to provide a compact representation of information flows in a DWRN. The proposed channel representation is then analyzed from a geometrically-based statistical modeling perspective. Finally, we look into the problem of relay network tomography (RNT), which solves an inverse problem to infer the internal structure of a DWRN by using the instantaneous double-directional IAS recorded at multiple measuring nodes exterior to the relay region.

This paper addresses distributed precoding design for MIMO interference networks, where multiple MIMO links share the same bandwidth. In our proposed design, the precoding matrix for an individual link is given as the product of two matrices obtained in two sequential steps. In particular, the first matrix is derived by maximizing the desired signal power given the leakage power as a penalty and the second matrix is obtained by suppressing the interference among data streams belonging to one link (inter-stream interference). Comparing to the naive precoding design, where each transmitter selfishly employs waterfilling transmission scheme, the achievable rate achieved by our proposed two-step precoding design increases as the SNR increases. Moreover, the performance gain of our proposed precoding design over the naive design depends on the available spatial degrees-of-freedom.

Wireless service providers often have to maximize their profit while satisfying the pre-specified Grade-of-service (GoS). However, the uneven traffic demand over a day has adverse effect to the design - the high blocked call probability during the peak-load hour limits the possible number of admitted users while low traffic during the off-peak hour results in the inefficient use of radio spectrum. The aim of this work is to study how a monopoly service provider can maximize the profit given that the daily traffic demands are time-varying. A possible way is to alter traffic demands through pricing differently at different periods of a day. Earlier study has shown that such peak-load pricing mechanism can reshape the traffic demand. As a result, the overall profit increases by moving some of the traffic to off-peak hour while at the same time improves the GoS of the group of users who are willing to pay more during the peak. There is generally a lack of theory to model the change even though some measurement has been made in the literature. We develop a simple model to predict the effect of peak-load pricing - one of the key features in the mechanism is the inter-temporal substitutability between the peak-load and off-peak period. We calibrate the model against the empirical evidences available.

In this paper, we look into the channel allocation problem for a non-cooperative cognitive vehicular ad-hoc communication network with multiple communicating pairs distributed spatially apart. An algorithm which can search for all pure Nash Equilibrium (NE) solutions is presented. We study how the number of pure NEs grows when either the size of the network or the number of available channels gets higher. Myopic play of a game, in which the players take turn to choose its best response strategy, is a common approach to obtain one of these NE solutions, if the algorithm converges. However, we found that for myopic play of the game, the probability of convergence to the NE which has the desired best global utility is not guaranteed. We further propose two player ordering schemes to study how the probability of hitting the best global solution among all possible NEs is affected. We find that by allowing the node with the lowest "expected" utility to decide first increases the chance of hitting the NE solution with better utility value.

In opportunistic spectrum access, a secondary radio (SR) periodically senses for a vacant channel to transmit. Common performance measures of the adopted sensing algorithm include missed detection and false alarm probabilities. However, minimal effort is made to incorporate the primary radio (PR) spectrum activities in the design. This paper models the errors arising from the mismatch between the SR channel sensing period and PR ON/OFF spectrum activities. Since the status of the channel is known, only at the sensing epoch, the PR may become active again in between the SR sensing periods, even if the idle channel is correctly sensed. The SR transmission thus collides with the PR transmission, and we refer to such a scenario as Type II missed detection error (MDE). Four performance metrics which serves as an indication of the SR sensing performance are identified, namely, the probability of Type II MDE, probability of missed SR transmission opportunity, probability of successful transmission and probability of SR blocked access. Based on results from renewal theory, we first model these metrics and then study their impact on the SR for Markovian and non-Markovian distributed PR spectrum activities. We then study the SR performance tradeoffs for different sensing periods. Simulated results verify the correctness of the analytically derived expressions. These results are important for designing an efficient SR system in the future.

In this paper, for the first time, an Ant Colony Optimization (ACO) based algorithm is used to solve the bit and subcarrier resource allocation problem of single-cell OFDMA systems. It results in a directed multigraph if the vertexes are used to represent the subcarrier and each path corresponds to a possible chosen modulation index of a specific user. Earlier studies which applied evolutionary algorithms (EAs) focused on single-class service, with no guarantee on individual QoS requirement in terms of bit rate and bit-error-rate performance. The proposed ACO guarantees the required minimum bit rate for all users while minimizes the total power consumption at the base station (BS). Simulation results show that comparing to other classes of EAs such as the Genetic algorithm, and the extended version of water-filling algorithm to support QoS traffic, ACO can obtain better solutions more often. We also observe that the performance is significantly better when the minimum demand bit rates for users are higher. Comparing to earlier developed GA, our proposed ACO algorithm also converges much faster but it needs more memory space to implement the ACO algorithm.

In this paper, we consider a scenario where distributed users in an OFDM-based system share the spectrum for transmission. Each network user (player) comprises a pair of transmit and receive nodes and will be allocated a given number of subcarriers. We propose a utility function that aims at efficiently allocating subcarriers to all players by minimizing the amount of interference generated. We first show that for the utility function used in the subcarrier assignment problem, it is possible to find a network potential function for the game. This guarantees the existence of at least one pure Nash equilibrium if each player is assigned with a predetermined number of subcarriers for transmission. Hence, convergence to Nash equilibrium can be achieved by iteratively playing the best-response game (also known as myopic game) among the players. Our simulation results show that distributing power over a number of subcarriers can achieve better per user capacity compared to the case where transmission is made through only a single subcarrier.

We address the adaptive allocation of subcarrier, bit and power resources among the base stations (BSs) of a downlink multi-cell OFDMA system using the non-cooperative game theoretic approach. Unlike the information theoretic approach where continuous bit-loading is used, our algorithm allocates integer number of bits to each subcarrier. Using a utility function with linear pricing on both the transmit bit rate and power, we first show that for a simple two-cell system with single user and fixed modulation, a Nash equilibrium (NE) solution always exists. However, for games formulated on more complicated systems such as with more than two cells, with more than one user in a cell, or when adaptive modulation is used, we observed that the existence of NE cannot be guaranteed. If NE points exist, the game can be played repeatedly with each BS (the player) selects its best strategy until the solution converges, or known as the myopic game. Based on the framework of potential games with coupled constraints, we propose an algorithm which can achieve a stable solution among the players despite that NE solution to the originally problem does not necessarily exist. The convergence of the proposed algorithm is verified by simulation.

Subcarrier and bit allocation has been extensively investigated in the literature to improve the spectral efficiency of multiuser OFDM systems. However, most of the earlier studies using genetic algorithms (GA) focused on single-class service and users of best effort data rate. In this paper, a novel GA method which allocates subcarriers and bits to rate guaranteed users is presented. As the reproduction process generates chromosomes which do not fulfill the constraints, our algorithm integrates the invisible walls technique used in Particle Swam Optimization to retain the diversity of the chromosomes. Simulation results show that the subcarrier and bit allocation strategy computed based on our proposed GA can achieve lower total power consumption compare to an algorithm modified from one of the pervious works. This verifies that our algorithm has better convergence rate and lower risk that the solution will be trapped at local optimums, while guarantees the required bit rate for each class of service.

We address the allocation of subcarriers, bits and power among the base stations (BSs) of downlink multi-cell OFDMA systems using the non-cooperative game theoretic approach. The utility function of a player is defined as the difference between the revenue generated from transmitting the bits and the cost of the power consumed. Unlike the commonly adopted water-filling approach where continuous bit loading is used, we consider assigning integer number of bits to subcarriers. We address the existence of pure Nash equilibrium (NE) of the static games for two-cell modulation adaptive and three-cell single modulation OFDMA systems. Theorems related to the existence of pure NE for the two games are developed. Using these results, we show that the existence of a stable solution for the OFDMA games cannot be guaranteed if minimum rate requirements must be satisfied.

Conclusion drawn from field measurement is that the allocation of radio spectrum to operators in a static manner does not make efficient use of the scarce spectrum resources. Dynamically allocating radio spectrum based on the demands using auction is one possible approach to improve spectrum utilization efficiency. In this paper, we consider a spectrum auction game, each spectrum supplier (SS) is competing against other suppliers so as to sell as much quantity as possible to maximize its own profit. On the other hand, bandwidth bidders (BBs) are also competing against each other to get the amount of demand spectrum at a lower price. In general, understanding the supply and demand relationship decides the selling price. We propose an auction game which jointly taking in consideration the competition among SSs and BBs, where the bid for the secondary reused spectrum takes place. Given that each SS knows the bandwidth available for secondary reuse over a period of time, with the assistance of a spectrum broker, our approach uses the open bid auction theory to decide the equilibrium point. Towards the end of the bidding process, suppliers and bidders will settle at an equilibrium point, whereby the selling quantities and bidding price are obtained. Our scheme can achieve a rather stable price per bandwidth when total demands do not exceed the total supply.

Although cell planning techniques have been widely applied, these formulations generally assumed static demand traffic, and either the average or worst case values are used in the design. Further, the impact of user mobility is usually ignored. We use examples to illustrate that better radio resource usage is possible by incorporating the time-varying traffic in the design, and that the user mobility can be similarly converted to multi-period optimization problem. We next formulate the one-dimensional cell planning problem, and demonstrate how it can be converted into a binary linear programming problem before solving for the optimal solution.

Two new precoding schemes based on the minimum mean-square error (MMSE) criterion for amplify-and-forward MIMO relay networks with quality-of-service (QoS) requirements are proposed. In the optimal joint source and relay precoding (OJSRP) scheme, primal decomposition technique is employed to decompose the non-convex optimization problem into a sub-problem and a master problem, which are convex and solvable. To relax the computation complexity of the OJSRP scheme, the suboptimal relay only precoding (SROP) scheme, which assumes equal power distribution over source antennas and has closed form solution, is also studied. Our numerical results show that both the minimum mean-square (MSE) performance and the capacity achieved by the two proposed schemes improve with the increase in signal-to-noise- ratio (SNR). Furthermore, OJSRP scheme has better MSE performance and capacity than SROP scheme. Finally, given a total transmission power, it is found that there exists an optimal power distribution over the source and the relay to achieve the best MSE performance and capacity. This indicates that transmission power should be distributed delicately over the source and the relay to optimize the resource utilization.

In this paper, a hybrid network consisting of both WiMAX and WiFi links is set up and used as a testbed for Voice-over-IP (VoIP) performance studies. Relevant metrics are defined and used to analyse the performance of this hybrid network and its ability to support VoIP calls. End-to-end delay and packets loss are measured as a function of number of ongoing VoIP calls. Based on these measured results, we propose a procedure to evaluate the maximum number of ongoing calls can be supported by the hybrid network while maintain the call quality at the desired level using the ITU-T specified E-model. The experimental studies show that this hybrid network is capable of supporting real-time VoIP calls, and that the network is able to support up to 12 simultaneous G.711-based VoIP calls and more than 20 simultaneous G.729-based VoIP calls. While it remains a challenge to ascertain the exact reasons behind the low network utilization, the proposed procedure for determining the maximum number of VoIP calls which meet the QoS requirements will be useful and valuable to service providers with the intention to provide VoIP services over such hybrid networks that interoperate these two technologies in the near future.

The development of reconfigurable and multimode terminals enable service providers to use the excess bandwidth to support services from other networks, at the expense of terminals performing vertical handover when a call is served by another network. The improvement in the performance of such an overlay heterogeneous network is expressed in terms of the increase in capacity while fulfilling each networks’ grade-of-service (GoS). Our results show that if there is no proper control in the admission of handover requests from other networks and only a simple first-come-first-serve (FCFS) policy is adopted, although each network can achieve better spectrum usage, the overall service capacity is still limited by the network which first violates its GoS requirement. We propose and analyze the performance of two admission control schemes for efficient resource sharing, namely, the reservation and the random early discard (RED) schemes. In the reservation scheme, the performance limiting network reserves some resources for exclusive access by its users. For the RED scheme, selective admission is used to limit the requests from the other networks. Using a four-dimensional Markov model, the call blocking probabilities and the vertical handoff probabilities for the case where there are two overlay networks are computed. Our results show that the two proposed schemes achieve higher service capacity and hence better spectrum usage when compared with the FCFS scheme. In addition, the RED scheme is more effective in balancing the two service loads over the reservation scheme. Analytical results derived from the Markov chain model show good agreement with the simulated results.

Gravity model has recently proposed for use to predict the movement of cellular mobile subscribers. In this paper, additional data are collected and similar validation process is performed to further our investigation. The results also verify that Gravity model can be used to predict user movements accurately, with the exception that the computed number of trips needs to be scaled by a factor ranging from 0.98 to 0.99. The impact of user mobility on cell planning is then discussed. The optimal design can be obtained through performing multi-period joint optimization.

We investigate the impact on the overall throughput of ad-hoc networks using two node connectivity control schemes. We propose a varying power constant connectivity (VPCC) scheme, where each node in a network regulates its transmission power until the number of its neighbors (node connectivity) is maintained at some desired number, whose optimal value is a design parameter to be determined. The achievable throughput is compared with the commonly adopted constant power varying connectivity (CPVC) scheme, where each node transmits at a constant power and hence has fixed transmission coverage but the connectivity changes from node to node. We derive the theoretical probability mass function of the number of neighbors of a given node for the CPVC scheme, and the probability density function of the coverage radius for the VPCC scheme. Simulation results are made to study the achievable throughput of the two schemes under the Poisson packet arrival assumption and when carrier- sense multiple access with collision avoidance and exponential back-off timer are used. The results from the simulation show that even if VPCC may result in a higher average number of hops per transmission under the same traffic condition, it can still achieve a much higher throughput than CPVC scheme. To have a better insight, we postulate and verify via simulations that the overall system throughput depends only on a parameter, which is equal to the frequency reuse factor divided by the average number of hops regardless of the schemes and the nodal density. This relationship provides a useful guide to designers, in which the parameter can be computed to predict the throughput before the most suitable scheme is selected.

We address the adaptive allocation of subcarrier, bit and power in the downlink of multicell OFDMA systems which are operating at a frequency reuse factor of one. When a centralized scheduler is used, the presence of co-channel cell interference inter-relates the assignment of the subcarriers and powers in all the cells, making the optimal allocation of radio resources a challenging problem. The lack of optimal solution in the literature for such a centralized approach is attributed to the difficulties in solving the mixed integer nonlinear programming problem. We show that through some manipulations, the solution to the original problem can be decoupled into solving two sub- problems sequentially: first solve for power allocation which is a linear programming and then subcarrier-bit allocation which is a binary linear programming. The elimination of the nonlinear constraints in our approach results in the significant reduction in the computation complexity, making optimal solution becomes possible. Although optimal solution not always can be computed in real time when the number of subcarriers is large, it can still serve as a performance benchmark to future developed heuristic algorithms. Finally, results in our paper are more practical since discrete values are used for bit-loading. This is different to most of the reported work in the literature which adopted information theoretic approach.

Subcarrier allocation for multiuser MC-DS-CDMA systems is much more complicated when compared to OFDM systems due to the presence of multiple access interference (MAI) when multiple users transmit simultaneously on the same subcarrier. In this paper, we propose a novel suboptimal algorithm to adaptively allocate subcarriers for MC-DS-CDMA systems, with the effect of MAI taken into consideration. An earlier proposed algorithm minimizes the bit- error-rate (BER) of respective users rather than minimizes the overall system BER. Each user performs channel estimation, orders subcarrier channel gains and feedbacks an index vector to the base station (BS). BS uses these index vectors from all the users, together with subcarrier allocation coefficients of the previous updating stage, to adaptively generate subcarrier allocation coefficients of the current updating stage so that BER performance is optimized. However, since the assignment process depends on the earlier allocation coefficients of other users, an error can propagate and affect the decision to be made in the next stage. In the proposed approach, the problem is formulated using Quadratic Programming (QP), and a single objective function is used to optimize the overall system BER. The algorithm uses the actual values of channel gains and does not depend on any information from the previous updating stage. Thus, the discrepancy propagation is avoided. We use Kuhn-Tucker conditions to convert the formulated QP to a linear programming (LP) problem, and the solution can be obtained using standard LP solvers.

In the future, secondary radios may exploit to use the spectrum holes (or white space) available over a given frequency band for transmission, provided the performance of the primary radio using the same spectrum is not significantly degraded. However, primary transmissions occur in bursts and hence spectrum holes are available sporadically. We define the duration in which a spectrum hole is first available to the instance it immediately becomes unavailable as the duration of white space access opportunities for secondary radios. In this paper, our model assumes a portion of the licensed spectrum is partitioned into N frequency bins, with the primary radio activities between any two frequency bins follow independent exponential on/off process. Our previous analysis showed that the probability density function of the white space access opportunities follows a hyper-exponential distribution. We present the approach to compute the theoretical probability density function of the duration of white space access opportunities for two frequency bins using an irreducible Markov chain model. For more frequency bins, the theoretical expression consists of many terms and may be difficult to handle. We perform extensive simulations and our results showed that in general only three exponential terms are needed to describe the continuous time distribution of white space access opportunities for secondary radios. The probability density function provides insightful information for the secondary usage of frequency bands.

An analytical formulation of the saturated throughput of burst mode prioritized contention access (PCA) with hard distributed reservation protocols (DRPs) and beacon period (BP) in WiMedia MAC is presented. The analytical framework is formulated for one hard DRP class and N PCA classes. The state transition diagram for the ith priority PCA class is modeled by a tri-dimensional discrete-time Markov chain. One dimension of the Markov chain is for the backoff stage, the second dimension is for the value of the backoff counter, while the third dimension is mainly for the delay due to DRP transmissions or BP. The probability of the number of consecutive DRP MASs and the number of consecutive PCA MASs are derived, taking into consideration of all possible combinations of the DRP locations in a superframe. These probabilities are essential for the modeling of the Markov chain.

Abstract Three multirate access schemes, multicode, variable spreading gain (VSG), and spectral overlaid multiple‐symbol‐rate (MSR), for asynchronous space‐time block coded (STBC) multicarrier code division multiple access (MC‐CDMA) systems are proposed. The three possible spectral overlaid configurations for MSR systems are also investigated. The expressions to evaluate the multiple access interferences, bit error rate (BER) performances, and system capacities of a antenna STBC MC‐CDMA using the three multirate access schemes are obtained. Transmit power allocation is adjusted according to the service rates and the number of active users in each service class to maintain the link quality and to improve the system capacity. Our numerical results show that systems with multicode access scheme using orthogonal Gold spreading codes and with VSG access scheme have similar system performance and capacity, and both perform in general better than systems with MSR access scheme of any spectrum configurations. In case when non‐orthogonal Gold codes are used, multicode access scheme shows degradation in the system capacity as compared to VSG, due to the presence of larger self‐interference (SI) among the codes used by each user. The achievable capacities for the three spectral overlaid configurations of MSR multirate systems are also compared. Copyright © 2007 John Wiley & Sons, Ltd.

An analytical formulation of the saturated throughput of Prioritized Contention Access (PCA) with Hard Distributed Reservation Protocols (DRPs) and Beacon Period (BP) in the presence of bit error for WiMedia MAC is presented. The analytical framework is formulated for one Hard DRP class and N PCA classes. The state transition diagram for the ith priority PCA class is modeled by a tri-dimensional discrete-time Markov chain. One dimension of the Markov chain is for the backoff stage, the second dimension is for the value of the backoff counter, while the third dimension is mainly for the delay due to DRP transmissions or BP. Numerical results of the saturated throughput corresponding to data rate of 1 Gbps are presented.

Subcarrier-and-bit allocation (SBA) has been extensively investigated in the literature to improve spectral efficiency of multiuser OFDM systems. In this paper, the analysis of adaptive SBA for multiclass multiuser OFDM systems which is generally formulated as a nonlinear integer programming problem is presented, whose solution is highly intricate. Some measures are conducted to ensure convexity and to reduce computational complexity, and the optimal solution to the modified equivalent problem is derived. The instantaneous total system revenue is maximized with the quality-of-service (QoS) in terms of data rate and bit error rate of each class guaranteed. The quadratic fitting scheme is further proposed to speed up the computation without significant performance penalty. We also discuss how to choose the system parameters appear in the objective function to facilitate the resource allocation.

This paper proposes a new blind source separation (BSS) technique for underdetermined MIMO system using space-time-frequency distributions. The sparseness in time-frequency domain is exploited for underdetermined BSS. The paper also proposed a new detection technique for auto sources time-frequency points, which is incorporated into the BSS technique. The proposed BSS technique applicable to the situations where sources' time-frequency signatures overlap at certain points in the time-frequency plane and even in situations where there are sources with multicomponent signals. In these situations, where time-frequency planes cannot be partitioned (masked) into groups of fewer or equal number sources than antennas, the existing overdetermined time-frequency BSS techniques could not be applied. Simulation results are included to show its effectiveness.

Gravity model used to model transport flow has proven invaluable in urban planning. Some recent work has proposed to use gravity model to predict user movements in cellular networks, however, there is generally a lack of practical evidence to justify the use of gravity model for such application. In this paper, we briefly summarize the theory of mobility gravity model which is derived based on the maximization of entropy. A simple algorithm which can be used to fit a set of observed trips as close to gravity model as possible is presented. We apply the algorithm to the census data collected in year 2000 from the train stations in the Tokyo metropolitan area. Statistical test is finally performed to validate the suitability in using gravity model to predict user movements for this set of data. Finally, how the model can be used to predict user behavioral change when there is a change in design parameters is discussed.

To obtain optimal location area (LA) partitioning in cellular radio networks is important since it maximizes the usable bandwidth to support services. However, we feel that the solution is insufficient to the problem, since values taken by the parameters of a mathematical model at the time of its formulation are only estimates of the practical scenarios. The optimal solution should instead be treated as a starting point for sensitivity study of the problem. This is particularly important in helping to identify any vast deviation of the parameters that affect the performance of the networks. We present the approach to perform sensitivity study on the LA design of GSM networks which is modeled as a nonlinear binary programming problem. The sensitivity of the total signaling cost when either one or more of the parameters: cell crossing rates, call arrival rates, paging and update costs, deviate from the designed values are investigated. Examples are given to illustrate how these bounds are obtained, within which the parameters can change but the LA partitioning remains optimal.

An analytical formulation of the saturated throughput enhancement of IEEE 802.11e using double increment plus one/ minus one half decrement (DIPO/MOHD) backoff mechanism for multiclass traffic is presented The analytical framework is formulated for N classes. The state transition diagram for the ith priority class is modeled by a two-dimensional discrete-time Markov chain One dimension of the Markov chain is for the backoff stage, and the second dimension is for the value of the backoff counter. The backoff stage moves to its previous backoff stage after a successful packet transmission and not back to the backoff stage 0 as in IEEE 802. lie. The advantages of this backoff mechanism are that it is easy to be implemented and can enhance the saturated throughputs. Numerical results of the saturated throughput corresponding to typical parameter values are presented The results show that the total saturated throughput using DIPO/MOHD can be better than that of IEEE 802. lie by up to 19%.

An analytical formulation of the saturated delay of Prioritized Contention Access (PCA) in the presence of Hard Distributed Reservation Protocols (DRPs) and Beacon Period (BP) in WiMedia MAC is presented. The analytical framework is formulated for one Hard DRP class and N PCA classes. The state transition diagram for the ith priority PCA class is modeled by a tri-dimensional discrete-time Markov chain. One dimension of the Markov chain is for the backoff stage, the second dimension is for the value of the backoff counter, while the third dimension is mainly for the delay due to DRP transmissions or BP. A numerical result of the saturated delay corresponding to typical parameter values is presented.

Adaptive subcarrier-and-bit allocation in orthogonal frequency division multiplexing (OFDM) systems can significantly improve spectral efficiency and reduce power consumption. The combinatorial optimization on the power, bit and subcarrier allocation in multiclass multiuser OFDM systems normally involved nonlinear objective functions and constraints, resulting in highly complex and computation intensive optimization problems. In this paper, we propose a method to linearize and simplify the optimization problem formulated on subcarrier-and-bit allocation in multiclass multiuser OFDM systems. With a drastically reduced complexity, the converted linear optimization problem can be solved in close to real time and the solutions found are optimal, as no relaxation is made during the linearization. Different approximate relationships between symbol error rate (SER) and bit error rate (BER) are also used to investigate the calculation on the required transmit power.

An analytical formulation of the saturated throughput of prioritized contention access (PCA) in the presence of soft distributed reservation protocols (DRPs) and beacon period (BP) in WiMedia MAC (formerly multi-band OFDM alliance (MBOA) MAC) is presented. The analytical framework is formulated for one soft DRP class and N PCA classes. The state transition diagram for the ith priority PCA class is modeled by a tri-dimensional discrete-time Markov chain. One dimension of the Markov chain is for the backoff stage, the second dimension is for the value of the backoff counter, while the third dimension is mainly for the delay due to DRP transmissions or BP. Numerical results of the saturated throughput corresponding to typical parameter values are presented.

An analytical formulation of the saturated throughput of prioritized contention access (PCA) in the presence of hard distributed reservation protocols (DRPs) and beacon period (BP) in WiMedia MAC (formerly multi-band OFDM alliance (MBOA) MAC) is presented. The analytical framework is formulated for one hard DRP class and N PCA classes. The state transition diagram for the ith priority PCA class is modeled by a tri-dimensional discrete-time Markov chain. One dimension of the Markov chain is for the backoff stage, the second dimension is for the value of the backoff counter, while the third dimension is mainly for the delay due to DRP transmissions or BP. Numerical results of the saturated throughput corresponding to typical parameter values are presented.

The deployment of wireless networks needs to consider both the cost and system performance metrics. The design objective is to decide the optimal placement of access points (or base stations) and to assign the available radio resources to respective traffic demand points with guaranteed performance, while keeping the deployment cost at its minimum. However, we feel that it would be better to adopt a design which can achieve long-term optimal rather than just at the instant of deployment. This paper set up a platform to look into the deployment of wireless networks which is able to optimize the profit generated over multiple periods each with different spatial traffic demands. Given a set of candidate sites, we first derive the placement and compute the transmission power of the access points to support a given spatial traffic demand over a specific period of time. The problem was formulated using a mixed integer linear programming model. Adjustable transmission range is made possible through power control to minimize the amount of interference among neighboring access points. With the knowledge on the projected demand traffic in subsequent periods, algorithms to maximize the long term profit are developed, both when the projected traffic are probabilistic and deterministic.

This paper looks into the allocation of unused frequency bands to secondary users. We propose a centralized model, where the secondary radio has a base station which can support the transmission of secondary users having either OFDM-based or CDMA-based communication systems, and the frequency bands assigned to each secondary user can be dynamically assigned. We set up a nonlinear binary integer programming model to allocate frequency bands to all secondary users, either in the presence or absence of primary users. We show that the problem can be converted to a quadratic integer programming problem with linear constraints to compute the optimal allocation. Finally, a suboptimal heuristic approach is proposed.

In this paper, we consider the problem of blind multiple-input multiple-output (MIMO) finite impulse response (FIR) channel identification driven by spatially uncorrelated and temporally white input signals. A method that can entirely identify the MIMO channel based only on the second-order statistics (SOS) of the observed data is proposed. The complete identification of the convolutive mixture is accomplished by exploiting the diversity of the channel orders. The uniqueness of the proposed solution is proved. Numerical simulation results are presented to illustrate the performance of the proposed algorithm.

Frequency-domain equalization (FDE) is an effective technique to mitigate the distortion induced by long-spanning inter-symbol interference, but the receiver requires to estimate the channel information. In this paper, we present a training-based frequency-domain channel frequency response (CFR) estimation scheme, which is hardware efficient when integrating with FDE for space-time (ST) coded multiple-input multiple-output (MIMO) transmissions over frequency-selective fading channels. In this proposed scheme, training sequences are ST block encoded at the transmitter. Similar to when performing FDE, the training sequences are processed after the FFT operation to obtain the CFR. A thorough analysis of the CFR estimation mean square error (MSE) is provided based on both the least squares (LS) and minimum MSE (MMSE) criteria, with the transmit power constraint and the optimal choices of training signals being taken into account. Finally, we demonstrate that when the number of transmit antennas is equal to 2, this CFR estimation could be implemented recursively by means of certain adaptive algorithms. Simulation results are presented to demonstrate the effectiveness of our proposed scheme in joint with FDE in multipath fading channels.

Transportation planning has proven invaluable in urban planning. As a portion of the cellular traffic is generated by private and public transport passengers during their travels, it is therefore reasonable to argue that transport models can be used as the underlying platform to study the telecommunication traffic generated by this group of high mobility users. This paper looks into this aspect. An introduction on the four-step transport model with feedback is first given. Gravity model based on the maximization of entropy are used to generate the trip distribution. An example is given to illustrate how cell crossing rates can be obtained using the transport model and its usefulness in cellular network planning.

In this paper, we evaluate the cell capacity of CDMA networks more accurately through simulation. Earlier work relating to the computation of Erlang cell capacity, other-cell interference imposed by an inter-cell mobile on the base station receiver is taken as the average with reference to all its possible spatial locations. This conventional approach implicitly is assuming that each inter-cell mobile has the same impact on the receiver performance. However, for interference-limited systems, mobiles located differently over the area will generate different amount of total other-cell interference, and hence, the receiver performance is expected to vary with instantaneous mobile locations. To investigate this effect, we first generate the mobile locations in all co-channel cells according to the known spatial distribution statistics. Perfect power control is applied to obtain the maximum number of mobiles in the referenced cell. By repeating for a large number of snapshots, the probability mass function for the maximum number of mobiles, which can be supported by the referenced cell, can be obtained to derive the Erlang cell capacity. Our results show that the Erlang cell capacity obtained using the conventional approach is smaller than that obtained from simulation, and unable to predict the variation in the maximum number of mobiles that can be supported by the referenced cell. We put forward an approach in quantifying the impact of mobile locations on the cell capacity without affecting the existing analytical approaches used in evaluating the Erlang cell capacity.

Radio propagation model when used in cell planning is normally assumed to be isotropic over the whole area under consideration. However, in practice, making such an assumption is idealistic since the environment and terrains are unlikely to be the same in all directions. In this paper, a heuristic approach to perform cell planning with the isotropic transmission medium assumption removed is first presented. Since the deployment of 3G networks will reduce the number of 2G GSM subscribers, we next look into a simple economic model to achieve efficient design of downsized 2G cellular networks. We show how our proposed cell planning algorithm is useful in limiting the search space to obtain the new optimal base station configuration.

The problem of finding the minimum number of base stations (BSs) required to provide full network coverage in a point-to-multipoint OFDM based fixed broadband wireless access network is investigated. We model this as a binary integer-programming problem (BIP) and use an efficient branch and bound algorithm to solve the problem. We also provide a design approach to determine the minimum number of BSs required when the traffic demands at all subscriber stations (SSs) are varying over a day.

The rate adaptation of MQAM systems is achieved by selecting suitable MQAM constellation sizes through comparing instantaneous received signal-to-noise-ratio (SNR) against the SNR threshold intervals. In this paper, we present an approach to study the capacity with imperfect channel estimation. Under channel estimation errors, there will be a shift in the SNR threshold intervals compared to perfect channel estimation, if a pre-defined BER performance needs to be satisfied. We first address the problem of how to obtain the SNR threshold intervals under imperfect channel estimation, given the statistics of fading channel and estimation errors, for both single receiver and diversity reception systems. Our derivation shows that the SNR threshold intervals in both cases remain unchanged. The capacity achieved by rate adaptive MQAM systems under imperfect channel estimation is computed after obtaining the SNR threshold intervals.

Due to a wide range of potential applications, on-body communication has attracted a lot of interests from the industry. As a good understanding on the equivalent transmission model for signal transmitting around human body might be important to optimize a body area network, in this paper, we perform measurement and investigate on the small-scale statistics of the transmission channels when UWB technology is used. With the transmitter fixed on the right waist and the receiver placed across 5 different positions on the human body, the frequency channels (3-6 GHz) on three individuals of different build are measured and analyzed. It is found that lognormal distribution fits very well to the small-scale fading statistics of the channel at each location. Our measurement results show that the parameter mu of the lognormal distribution differs across receiver locations. However, for a particular receiver location, they are nearly the same for all the people under experiment. The parameter mu of the lognormal distribution was found to fluctuate with a standard deviation sigmastd.devabout a mean value sigmaaverage, for each receiver location.

In this paper, we study various frequency-domain equalizers (FDE) for single-carrier space-time block coded transmissions over frequency-selective fading channels. The linear and decision feedback equalizers based on zero forcing (ZF) and minimum mean-square error (MMSE) criteria are considered. These methods offer different tradeoff in terms of performance and the a priori knowledge of the data and receiver noise statistics, which is discussed. Besides, we also consider the adaptive FDE based on some low-complexity block-wise recursive algorithms, which obviates the need for distinct channel estimation and realizes joint channel estimation and equalization. Performance of these FDE schemes are investigated by applying them to the EDGE system in the multipath fading environment. Simulation results demonstrate their effectiveness and also provide implications for selection of these FDE schemes in practice

Subcarrier-and-bit allocation has been extensively investigated in the literature to improve spectral efficiency of multiuser OFDM systems. However, in previous studies, nearly all the studies are focused on single-class service. In this paper, formulation of adaptive subcarrier-and-bit allocation for multiclass multiuser OFDM system is presented. The objective is to maximize the instantaneous total system revenue with the quality-of-service (QoS) of each class guaranteed. Since complexity to the exact solution is generally high and involves solving of nonlinear objective function and constraints, two suboptimal approaches to this problem are presented. The first approach uses a quadratic approximation to the objective function; while in the second approach, a two-step algorithm is developed to obtain the suboptimal solution. The solution is first relaxed to real numbers with some constraints removed before the integer solutions are obtained. The accuracy and complexity of these two approaches are compared with each other as well as with the optimal solution.

In this letter, two direction-of-arrival (DOA) estimators are proposed: one is a new fourth-order cumulant-based technique, and the other is a joint second- and fourth-order cumulant technique. Using the full set of cumulants for DOA estimation is computationally expensive; conversely, using a downsized quadricovariance matrix leads to poor DOA estimates. This letter proposes the choice of efficient quadricovariance matrices to be used in the fourth-order estimator. Then, together with these matrices, a joint second- and fourth-order DOA estimator is derived. Both algorithms perform reasonably better than existing fourth-order and second-order algorithms in a spatially correlated Gaussian noise environment

In this paper, a joint symbol timing and frequency-offset estimator based on the maximum likelihood (ML) criterion, is derived for OFDM systems over frequency selective fading channels. .We use the linear minimum mean square estimation technique (LMMSE) to estimate the nuisance parameters such as transmitted signals and fading gains, and arrive at an algorithm to jointly estimate symbol timing and frequency offset. Simulation results show that our proposed symbol timing estimator performs better than the estimator reported by van de Beek et al (1997), while our proposed frequency offset estimator achieves a lower MSE at higher SNR (/spl ges/ 15 dB). Simulation results also show that our proposed symbol timing and frequency offset estimator has better MSE performance than the cyclostationarity-based estimator studied in T. Pollet and M. Moeneclaey (1995) at higher SNR (for example 15 dB). However, in terms of probability of correct timing synchronization and MSE, our symbol timing estimator achieves roughly the same performance as the estimator by Lee et al (2002), although a different approach is used in our estimator. Our proposed estimator is next modified to two practical ones independent of SNR, furthermore, one of which needs only the knowledge of the maximum delay spread to perform estimation. We also extend our proposed estimator to applications where multiple OFDM symbols can be observed to perform synchronization.

We present a mobility model for simulations of scenarios in UMTS networks. This new model has been developed to overcome the shortcomings of previous models in capturing mobile user behavior. The proposed model strikes a balance between the abstraction level of purely stochastic models which lack certain important properties of the real world and completely deterministic models. The proposed model generates destinations of the mobile users based on the maximization of entropy of the gravity model which was first used in transportation planning and which has proven invaluable in urban planning. Subsequently, the model then allows the detailed tracking of users, in particular, the path of mobile users based on some known statistical behaviors of the mobile users, such as service arrival rates, service holding times, velocities, etc. As tracking is done on a microscopic level, it is possible to simulate and collect parameters which are important for wireless network planning and optimization, without the use of unrealistic assumptions.

In this paper, we present a closed-form solution for blind multiple-input multiple-output (MIMO) finite impulse response (FIR) channel estimation driven by colored sources whose second-order statistics (SOS) are assumed to be known a priori. The proof for the uniqueness of the system solution is provided. Numerical simulation results are presented to illustrate the performance of the proposed algorithm.

We address the throughput and delay performance of a direct sequence spread spectrum (DS-SS) slotted ALOHA packet radio system, where all users use a common spreading code to communicate with a central station. Unlike in previous works where packets are constrained to arrive on a finite set of discrete times, we consider in this paper that packet arrivals are continuously and uniformly distributed over an arbitrary uncertainty interval. We derive a closed form multi-packet capture probability and obtain the throughput and delay expressions for the DS-SS slotted ALOHA packet radio system. We use simulations to validate our analysis.

In this paper, we present low-complexity adaptive frequency-domain equalization (FDK) for space-time block coding (STBC) direct-sequence code-division multiple access (DS-CDMA) downlink system. The proposed scheme is powerful and computationally efficient, as the sophisticated matrix decomposition operations are not required in the processing and some block recursive processing, such as block least mean square (BLMS) algorithm and modified block recursive least squares (BRLS) algorithm can be easily incorporated for equalizer adaption. Simulation results demonstrate the effectiveness of such adaptive FDE with regard to different Doppler shifts.

In universal mobile telecommunication system (UMTS), the interference caused by location management procedures is expected to have an impact on the capacity of the network, since it is an interference-limited system. The grouping of the cells into LAs, RAs and URAs will affect the amount of paging and thus, will have an impact on the capacity of the network. In this work, we set up a simulation platform to study the effects of paging procedures in the Release 99 version of UMTS on the network capacity. Simulation results show how the capacity of the system changes as the paging load is increased. The results presented are important in providing an insight into the impact of paging procedures on the system throughput and capacity of the UMTS forward link.

The problem of finding an optimal base station (BS) configuration for CDMA networks given a set of candidate BS sites is investigated. The design is first formulated as an optimization problem. Features which are unique to CDMA, such as power control, intra-cell and other cell interference, etc., are included in our consideration. In particular, the signal-to-interference ratio (SIR) in both uplink and downlink of each MS is taken as the quality of measure. The solution to the problem is simplified by using a heuristic algorithm. The heuristic begins from all candidate BS sites being activated and assignment of each mobile station (MS) to BS is based on smallest path loss. It then proceeds to deactivate the sites one by one until the minimum number of sites needed to serve the traffic is obtained.

In this paper, a new approach to study the effect of carrier frequency offset (CFO) due to the mismatch between the transmitter and receiver oscillators on the bit error rate (BER) performance of asynchronous multicarrier code division multiple access (MC-CDMA) systems is proposed. The closed form BER expression when the maximum ratio combining (MRC) is used is derived. The correctness and effectiveness of the proposed approach is verified through computer simulations. Numerical results show that small CFO has insignificant effect on the BER performance of MC-CDMA systems.

We present a modeling framework for studying header compression performance. For the first time, a source model is developed for header compression. By varying the source and channel models in our framework, different source and deployment scenarios can be modeled. Using this new paradigm, we study the tradeoff dependencies between performance metrics. We also demonstrate how a scheme can be designed to optimize tradeoffs based on the desired level of performance.

We present a closed-form solution for blind single-input multiple-output finite impulse response channel estimation driven by colored sources. The second-order statistics of the input source are known a priori. The uniqueness of the system solution is proved by exploiting the derived property of companion matrices that are constructed from the inherent structural relationship between the source autocorrelation matrices. Numerical simulation results are presented to illustrate the performance of the proposed algorithm.

In third generation telecommunication mobile communication system, signaling requirements due to location updates and paging are expected to be noteworthy, mainly due to increasing number of mobile users. Location management (LM) is marked by the trade-off between the amount of location updates and the amount of paging loads that will be incurred onto the system. In this work, a hybrid simulation platform is set up to study and analyze the effects of parameters such as the size of various registration areas have on a R99 Universal Mobile Telecommunication System (UMTS), of which are related to the level of interference to be incurred by the system. The results obtained provide an insight on the performance of the LM design and varying degrees of changes in the updating and paging loads for varying sizes of registration areas.

A decoupled maximum likelihood (DEML) estimator is employed to estimate the multipath delays and channel coefficients of all users. This estimator starts with a training mode then reverts to a decision-directed mode. In the training mode, the initial values of multipath delays and channel coefficients of all users are estimated. These initial parameters are used for parallel multiuser interference cancellation. Once the multiuser interference is cancelled, the signal is fed back to the estimator for fine estimation of delays and channel coefficients of all users. These fine estimates are used for the next symbol interval. This process continues in the decision-directed modes. The performance of channel estimation with interference cancellation has shown considerable improvement under multipath environments compared to the one without interference cancellation. Conclusively, the proposed scheme removes the intersymbol interference (ISI) resulting from multipath propagation and obtains more accurate channel estimates for further data detection. Finally, analysis is done to justify the simulation results.

In this paper, we developed a subspace projection method for blind MIMO FIR identification, based on fourth order statistics of the output signals. The proposed method employs a subspace projection technique to identify the channel. The method identifies MIMO channels up to a nonsingular matrix, and it does not require exact knowledge of each user's channel order. Simulation results are included to verify our theoretical claims.

A DS-CDMA RAKE receiver architecture is proposed. Unlike the conventional receiver, the proposed /spl Sigma//spl Delta/-CDMA receiver does not require a /spl Sigma//spl Delta/ demodulator and a root-raised-cosine (RRC) filter, and hence its despreader can be implemented mainly using simple XNOR gates and 2-bit adders. The conditional BER for DS-CDMA forward link is derived and the averaged BER is obtained by Monte Carlo simulation. It is shown that the BER performance of the proposed receiver can match that of the conventional DS-CDMA receiver, which is implemented using a /spl Sigma//spl Delta/ analog-to-digital converter (ADC), with the proper choice of over-sampling ratio. And the proposed receiver achieves a much smaller gate-count than the conventional receiver when implemented on FPGA.

A power control scheme with outage probability specifications is derived and studied for interference-limited wireless cellular systems in Rician/Rician fading channels. We first define a performance index, so-called signal-to-interference power ratio margin (SIRM) for each desired communication link in Rician fading channels. We also explain and discuss the relationship between the outage probability of a desired link and its SIRM. A power control scheme is then proposed to balance the outage probabilities of all the desired links and we show that applying the well-known Perron-Frobenius theory can solve such a problem. Simulation results verify the effectiveness of the proposed power control scheme. As expected, our scheme is shown to cover a previous scheme for Rayleigh fading channels as a special case.

In this paper, two types of spectrally overlaid multiple symbol-rate (MSR) asynchronous space-time block coded (STBC) multicarrier code division multiple access (MC-CDMA) systems are proposed. One of the systems has constant spreading gain (CSG) and the other has variable spreading gain (VSG) for different services. Both systems have different symbol rates at each subcarrier for different services. Two possible configurations of CSG systems are also proposed. A transmit power control is proposed to maintain the link quality and improve the system capacity. The multiple access interferences and hence system capacities for the two types of MSR STBC MC-CDMA systems are investigated. From the numerical results obtained, it can be concluded that both the MSR STBC MC-CDMA systems with VSG and with CSG configuration 2 can obtain much steadier performance and system capacity than the system with CSG configuration 1. And the system capacity of MSR system with CSG configuration 2 is the best when the number of low rate user is moderate.

With the growth of wireless industry, demand for high-speed wireless data services is expected to overtake voice services and a hybrid wireless wideband CDMA/ wireline Internet protocol (IP)-based network will be the main platform for providing multimedia services to both mobile and fixed users. We first present a multiclass admission control scheme with UMTS QoS classes in the DiffServ IP network. We further extend this scheme for end-to-end admission control from the 3G WCDMA to the DiffServ IP networks and investigate how to interconnect a future wireless network with the Internet for seamless end-to-end information transmission. Simulation results show that the scheme provides flexible and efficient multiclass QoS guarantees over the end-to-end connections.

A multicarrier transmission technique using two dimensional fast Fourier transform (2D FFT) is suggested in this paper. It modulates the data symbols onto the subcarriers that is located in a planar array by the 2D FFT transformation. Frequency domain channel equalization is performed at the receiver. We study the performance of this 2D FFT modulated signal and the relative merits and demerits of the method are compared with the conventional OFDM technique. Simulation results for the 2D FFT modulated signal is presented. In general, 2D FFT transmission scheme shows performance improvement by spiking the conventional OFDM FFT block into two smaller FFT blocks to avoid the time selective fading conditions, and simultaneously introduce better immunity from narrow-band jamming signal and impulse noise.

This paper presents an analytical framework for balancing the reverse and forward links capacities by searching for the optimal soft handoff probability. A cross-layer framework involving the link layer and the network layer is designed to determine the optimal soft handoff probability. Using the network layer parameter, call blocking probability, as the metric of system performance, the system is optimized by subjecting to the SIR requirement at the link layer. The admission region is calculated by maintaining the outage requirements for both the reverse and forward links, and the optimal soft handoff probability is obtained by looking for the lowest penalty of call blocking and found that the optimal soft handoff probability used in the voice-oriented cellular system is required to be kept at 0.35/spl sim/0.45. Furthermore, the optimal soft handoff probability should be reduced with the increase of the transmission traffic load from video/data service and other unbalanced services on the forward link.

An adaptive SNR-priority-based channel allocation scheme over multiple access fading channel is proposed. The performance of this scheme is a compromise between the conventional TDMA scheme which has short channel access waiting time but poor spectral efficiency, and the best SNR user transmitting scheme which has better bandwidth efficiency but longer channel access waiting time. The capacity achieved by this scheme is studied and compared with the conventional rate adaptive TDMA systems. The operation of this scheme requires channel estimation which is performed at the frame period for all N mobiles. For the SNR-priority -based system, the frame period is divided into K slots and only K mobiles that observe the first K best channel conditions are assigned to transmit. By assuming that only best-effort traffic is served, the channel capacity and the system throughput of the SNR-priority-based TDMA system achieved with rate adaptive MQAM modulation technique are studied. The average channel inter-access time for such a system is also studied through simulation.

We propose an efficient two-stage DS-CDMA multiuser detector (MUD). The first stage is a reduced linear detector and the second stage is a matrix graduated nonconvexity annealed neural network (MGN-ANN). By using a first stage linear detector, the computational complexity in the second stage can be significantly reduced. We carried out extensive simulations in order to compare the error probability performance of our proposed detector with other competing multiuser detectors, which are based on conventional matched filter detector (CD), Hopfield neural network (HNN), multistage detector (MS-10) and annealed neural network (ANNMD). We also use the optimum multiuser detector (OMD) as comparison benchmark for all the MUDs. We show that the error probability performance of our proposed detector is significantly better than the other suboptimum MUD's and approaches the performance of the OMD.

We study the performance of adaptive M-ary quadrature amplitude modulation (MQAM) in wireless cellular system with Nakagami fading and log-normal shadowing. An interference-limited system is assumed and the statistic of co-channel interference is analyzed. Our analysis shows that the instantaneous signal-to-interference ratio (SIR) in cellular system with Nakagami fading and log-normal shadowing can be approximated as having the log-normal distribution. We derive the probability density function (PDF) of the instantaneous SIR and use it to evaluate the spectrum efficiency of MQAM in cellular systems. The impacts of Nakagami fading, shadowing and the target bit error rate (BER) on average throughput and average outage probability are presented and discussed.

This paper studies the capacity of a multiple chip rate (MCR) system under a practical environment. In our analysis, the use of non-orthogonal spreading codes, differences in carrier frequencies and power spectrum density of signals for different users, are taken into consideration. Capacities of the two MCR systems with different subsystem configurations are obtained. A comparison between the capacity of an MCR system and a multiple processing gain (MPG) system is also given. From the numerical results obtained, it can be concluded that for MCR systems, the full assignment configuration (a) can provide a higher system capacity than configuration (b), and configuration (b) with /spl Delta//spl omega/ = 0 achieves the same capacity as that of the MPG systems. Hence with good control of the spectrally overlaid structure, MCR systems can achieve higher capacity than MPG systems.

In this paper, an adaptive parallel interference cancellation (PIC) scheme is proposed for the asynchronous multicarrier direct sequence code division multiple access (MC-DS-CDM A) system. An adaptive MAI estimation algorithm is applied before the PIC stage to improve the accuracy of the MAI cancellation. The performance behaviour of our proposed detector is investigated and its analytic hit error probability is derived. The theoretical results agreed well with the simulations. It is shown that the adaptive PIC receiver outperforms the matched filter and the conventional PIC receiver for the MC-DS-CDMA system in a fading channel.

To achieve high system capacity over frequency-selective fading channel, multi-carrier code-division-multiple-access (MC-CDMA) system with spatial diversity using space-time block coding (STBC) is considered. We present a subspace-based semi-blind channel estimation method under multiuser environment to resolve the inherent scalar ambiguity when blind estimation technique is used. Mean-square-error (MSE) expression for the proposed channel estimation technique is derived. Bit-error-rate (BER) when using linear zero-forcing (ZF) and minimum-mean-square-error (MMSE) multiuser detection techniques taking the channel estimation error into consideration are obtained through simulation. The correctness of the BERs is further verified through estimating the signal-to-interference and noise-ratio (SINR) at the multiuser detectors.

This paper investigates capacity of CDMA system employing adaptive transmission technique under multipath fading channel. Three power control schemes with rate adaptive capability are proposed to exploit the time variation of channel fading. In all the three schemes, adaptive transmission employing BPSK is realized through adapting the processing gain (PG) to the channel conditions. A minimum PG constraint is made to ensure multiple access capability. When PG is at this minimum value, the system can have an option to adjust the transmission rate through using higher constellation QAM. For scheme 1, system capacity rather than the lower bound reported in [Kim, S.W., 1999] is obtained. System capacities for scheme 2 and 3 are analyzed and computed using numerical calculations. Our numerical results show that the proposed power control schemes 2 and 3 can obtain higher system capacities than that of ideal constant received power at the base station, for a given constant average transmission power per user.

In this letter, we extend the baseband impulse noise modeling over the subscriber loop conducted over the German Telephone Network to the passband scenario. We apply an in-phase (I) and quadrature (Q) resolution of the passband impulse noise and model these components as a generalized error distribution. We use simulation to verify our postulation. Closed-form symbol error rate (SER) expressions for M-ary quadrature amplitude modulation over this passband impulse noise channel are then derived. From the computed SER results, we conclude that the system performance is not sensitive to the dependency factor between the I and Q noise components.

In a spectrally overlaid multi-band CDMA (SOM-CDMA) system, wide-band, medium-band and narrow-band CDMA subsystems with different spreading bandwidths are spectrally overlaid with each other. This system architecture has an advantage that different traffic types can exist together within a given band of spectrum, without having to allocate a separate spectrum band for each type of traffic. However, spectrally overlaid subsystems may also induce more interference on particular reference mobiles. Under this scenario, to study the effect of interference on the system capacity becomes necessary in order to ensure that the system can provide the required quality of service (QoS) for each type of service. Previous works on SOM-CDMA systems focused only on interference from mobiles in an isolated cell. In this paper, the capacity of SOM-CDMA cellular system in terms of aggregate data rate, by taking both inter-cell and intra-cell interferences into consideration, is investigated. Our results show that under the standard path loss model and ideal power control assumptions, the maximum aggregate data rate of SOM-CDMA systems will be degraded to approximately 50% of the isolated cell case. We also observed that the system capacity increases with the cell radius, while below a certain radius, spectral overlay becomes impractical. The bound of maximum mobiles admitted in SOM-CDMA with given SNR requirement and data rate of each frequency band can be a guide to system designers who design the call admission scheme.

This paper investigates quality-of-service (QoS) performance of voice services in hybrid fiber/coax (HFC) networks. We focus on the upstream channel and the performance of the system is evaluated in terms of voice packet loss probability. Two different classes of voice services are considered. For voice without speech activity detector (SAD), there is no packet dropping and hence the analysis is trivial. For voice with SAD, we develop an elaborate discrete-time Markov chain model to obtain the voice packet dropping probability. We also describe the voice traffic models and the performance measures, and include an overview of the media access (MAC) protocol. Numerical examples are presented to demonstrate the performance the system.

A single edge detector for coded mark inversion, data transmission is proposed. Its detection performance depends mainly on the false transition probability if the bandwidth of the receiver low-pass filter is reasonably large, say equal to twice the data rate. An approximate expression for the bit error rate (BER) performance of this detector operating in white Gaussian noise is derived by considering the level crossing probability of the noise process. Measurements show that this approximation is closer to the actual BER performance than results obtained from a previously established theoretical approach in some cases.>