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Frequency-domain equalization (FDE) is an effective technique for high-data-rate wireless communication systems suffering from very long intersymbol interference. Most of the existing FDE algorithms are limited to slow time-varying fading channels due to the lack of an accurate channel estimator. In this paper, we employ an interpolation method to propose new algorithms for frequency-domain channel estimation for both slow and fast time-varying fading. We show that least squares (LS)-based channel estimation and minimum mean square (MMSE)-based channel estimation with interpolations are equivalent under certain conditions. Noise variance estimation and channel equalization in the frequency domain are also discussed with fine-tuned formulas. Numerical examples indicate that the new algorithms perform very well for severe fading channels with long delay spread and high Doppler spread. It is also shown that our new algorithms outperform the recently developed frequency-domain least mean squares (LMS) and recursive LS (RLS) algorithms which are capable of dealing with moderate fading channels. [ABSTRACT FROM AUTHOR]

Abstract-This paper proposes a dynamic resource-allocation (DRA) algorithm for packet data services in wireless communication systems based on Hopfield neural networks (HNNs). The resource-allocation algorithm assumes a delay-centric approach in that it maximizes resource utilization of the overall system while minimizing the packet delay. The real-time (RT) working capability of HNN hardware implementation means that a very powerful scheduling DRA algorithm can be obtained. A generic formulation of the algorithm is presented to establish the optimal bit rate allocation. In addition, some illustrative examples of this formulation are given, considering specific wireless communication systems, such as General Packet Radio Service (GPRS) or Universal Mobile Telecommunications System (UMTS). lo be more precise, the performance of the proposed DRA algorithm is evaluated in a realistic UMTS scenario, considering both RT and nonreal-time (NRT) services. To obtain the best resource distribution and fulfill the different quality-of-service (QoS) levels required by RT and NRT services, the new HNN-based delay-centric DRA algorithm is performed twice. Initially, only the RT services are considered, and following this, all the NRT services are taken into account. The results reveal that the proposed DRA algorithm outperforms other reference algorithms in terms of not only average packet delay but the allocated total bit rate as well. [ABSTRACT FROM AUTHOR]

This paper considers the optimal distributed assignment of rates to elastic users in a broadband multicell code-division multiple-access (CDMA) network with variable rate assignments, which is connected to a traditional wired Internet Protocol (IP) network. We show that by using an optimization framework, it is possible to construct a distributed rate assignment algorithm similar to current congestion control protocols that addresses both media access control and transport layer issues (i.e., addresses both interference and congestion control). Practical implementation of this algorithm, as well as its impact on convergence and performance, is also addressed. [ABSTRACT FROM AUTHOR]

High-data-rate cellular systems, such as 1xEVolution-Data Only (1xEV-DO), can provide data at high rates to users, but generally, these high rates will only be available to users with good links from the base station (BS). Using multihop, where a relay can receive and retransmit a signal to the destination, has the potential to improve the data rates for users with poor links from the BS. In this paper, we propose a method for implementing two-hop relaying on the downlink of a high-data-rate system. Unlike conventional routing algorithms, our method (called presumptive routing) exploits multiuser diversity by selecting the target user after the relay has been selected. This means that the interference experienced by a user does not have to be predicted because it can be determined through the use of pilot signals. The signaling overhead is not much greater than that of conventional high-data-rate systems. We give results for the performance of presumptive routing and compare these to those of single-hop and ideal two-hop systems. [ABSTRACT FROM AUTHOR]

Time dispersion is one of the most important characteristics of the wireless channel. The knowledge about the time dispersion of a channel can be used to design better systems that can adapt themselves to the changing nature of the transmission medium. In this paper, algorithms to estimate the time dispersion (frequency selectivity) of the channel, which use the frequency-domain channel estimates or the frequency-domain-received signal, are proposed. The proposed algorithms estimate the power delay profile (PDP) from which the two important dispersion parameters, namely root-mean-squared (RMS) delay spread and maximum excess delay of the channel, are estimated. It is shown that synchronization errors bias the performance of the estimators based on the channel correlation, and this bias is removed by obtaining the PDP using the magnitude of the channel estimates. Moreover, the Cramér-Rao lower bound (CRLB) for the estimation of the RMS delay spread is derived, and the performances of the proposed algorithms are compared against this theoretical limit. [ABSTRACT FROM AUTHOR]

With a small amount of software modification, wireless extension points (EPs), which are now commercially available, can be used to improve the throughput capacity of a wireless local area network (WLAN). An EP is an immobile device that has access to the power supply or is equipped with a high-capacity battery but does not have direct access to the Internet. They wirelessly relay data between the access point and the mobile hosts. In this paper, we investigate the optimal placement of the EPs such that the throughput capacity of an urban rectilineal WLAN can be maximized. Two channel models that are based on the Shannon capacity bound and IEEE 802.11 specifications are studied. We first formulate a solution for the optimal EP placement problem in a general network scenario as a nonlinear programming problem; then, we propose an efficient algorithm that determines the optimal locations of a fixed number of EPs in a rectilineal network. Our results show that, for a wide range of system parameters, the optimally placed EPs can significantly increase the network throughput capacity. Moreover, we study how the number of EPs, transmission power, path loss exponent, channel models, and traffic characteristics affect the optimal EP placement and expected throughput capacity of the network. [ABSTRACT FROM AUTHOR]

In this paper, a reduced-complexity soft-interference- cancellation minimum mean-square-error (SIC-MMSE) iterative equalization method for severe time-dispersive multiple-input-multiple-output (MIMO) channels is proposed. To mitigate the severe time dispersiveness of the channel, a single carrier with cyclic prefix is employed, and the equalization is performed in the frequency domain. This simplifies the challenging problem of equalization in MIMO channels due to both the intersymbol interference (ISI) and the coantenna interference (CAl). The proposed iterative algorithm works in two stages. The first stage estimates the transmitted frequency-domain symbols using a low-complexity SIC-MMSE equalizer. The second stage converts the estimated frequency- domain symbols in the time domain and finds their means and variances to incorporate in the SIC-MMSE equalizer in the next iteration. Simulation results show the bit-/symbol-error-rate performance of the SIC-MMSE equalizer, with and without coding, for various modulation schemes. [ABSTRACT FROM AUTHOR]

Channel conditions in wireless local area networks (WLANs) are variable due to mobility and interference. Autorate algorithms are commonly used in WLANs to maximize the data rate over the variable physical channel. However, the widely used automatic rate fallback (ARF) algorithm does not work properly in the presence of multiaccess collisions due to its inability to differentiate frame losses caused by link errors from those caused by collisions. This paper proposes an improved ARF algorithm that is capable of differentiating between these two types of losses with minimal modifications to the existing medium access control protocol. The performance evaluations show substantial through-put improvements over ARF and other existing algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we present an opportunistic packet scheduling algorithm based on buffer management (OSBM) over the downlink of a packet cellular network. OSBM is a channel-dependent scheduling algorithm with a provable delay bound. It is able to provide differentiated services to both real-time and nonreal-time applications. Particularly, these features of OSBM are achieved through a novel buffer management scheme. Since this buffer management scheme does not involve any complex online computation, OSBM is very efficient and easy to implement in an operational environment. We also present a new analytical approach for performance analysis of opportunistic scheduling in wireless networks based on the proposed concept of effective downlink capacity (EDC). This approach attempts to adapt the service curve tool for deterministic quality-of-service analysis to the wireless environment, and the concept of the EDC serves to bridge the deterministic method and the stochastic nature of the wireless link. Using this approach, the explicit expression of the delay bound of the OSBM algorithm is obtained. Simulation results are presented to demonstrate the effectiveness of the proposed opportunistic scheduling algorithm. [ABSTRACT FROM AUTHOR]

In order to improve the performance of multicarrier code division multiple access (MC-CDMA) in the uplink channel, quasi-synchronous MC-CDMA with minimum-mean-square-error (MMSE)-based subcarrier-combining method is effective. However, conventional MMSE methods require a lot of pilot symbols for derivation of optimal weights. In this paper, in order to reduce the number of pilot symbols for uplink MC-CDMA systems, we propose a multistage recursive-least-square (MS-RLS) method for the derivation of the weights for the MMSE subcarrier combining. In the MS-RLS, the received symbols are stored in the buffer memory, and the RLS algorithm is repeatedly performed with a multistage structure by using the same pilot symbols. In this method, the weights and the inverse matrices of correlation matrices of the adjacent subcarriers are utilized for the initial values of the next-stage weight updating. Through computer simulation, we confirm that the performance of MC-CDMA in the uplink channel is improved by using the proposed MS-RLS method, even with short pilot symbols. [ABSTRACT FROM AUTHOR]

State-of-the-art vehicles are now being equipped with multiple video channels for video-data transmission from multiple surveillance cameras mounted on the automobile, navigation videos reporting the traffic conditions on the planned route, as well as entertainment-multimedia streaming for passengers watching on rear-seat monitors. Wireless LANs provide a low-cost and flexible infrastructure for these emerging in-vehicle multimedia services aimed at the driver's and passengers' safety, convenience, and entertainment. To enable the successful simultaneous deployment of such applications over in-vehicle wireless networks, we propose delay-sensitive streaming and packet-scheduling algorithms that enable simple, flexible, and efficient adaptation of the video bitstreams to the instantaneously changing video source and wireless-channel characteristics while complying with the a priori negotiated quality-of-service (QoS) parameters for that video service. Our focus is on real-time low-cost solutions for multimedia transmission over in-vehicle wireless networks that are derived based on existing protocols defined by QoS-enabled networks, such as the IEEE 802.11e standard. In addition, the aim of this paper is to couple the proposed solutions with a novel multitrack-hinting method that is proposed as an extension of conventional MP4 hint tracks in order to provide real-time adaptation of multimedia streams to multiple quality levels for different in-vehicle applications, depending on their importance and delay constraints. First, the scheduling constraints for these simultaneous wireless video-streaming sessions are analytically expressed as a function of the negotiated QoS parameters. This is imperative because a video stream received from an in-vehicle road-surveillance camera will have a different set of delay and quality constraints in comparison to that of traffic monitoring received from remote video cameras located on the planned route. Hence, transmission parameters, such as peak data rate, maximum burst size, minimum transmission delay, maximum error rate, etc., will differ for the various video streams. For this reason, new low-complexity packet-scheduling algorithms that can fulfill diverse QoS streaming conditions are proposed and analyzed. The proposed algorithms produce viable schedules (i.e., strictly QoS.compliant) that jointly consider the delay constraints and the in-vehicle video-receiver-buffer conditions. Hence, these scheduling schemes can completely avoid the underflow or overflow event of the receiving-device buffer while guaranteeing the agreement between the real-time video traffic and the predetermined traffic specification reached during QoS negotiation for various in-vehicle video channels. When combined with multitrack hinting, an integrated flexible system for adaptive multimedia streaming over QoS-enabled in-vehicle wireless networks can be constructed. We demonstrate the viability of the proposed scheduling mechanisms experimentally by using real video traces under multiple quality levels, as derived by the multitrack-hinting design. In addition, simulations under realistic conditions are also performed to validate the ability of the method to satisfy buffer-occupancy constraints. [ABSTRACT FROM AUTHOR]

With various wireless technologies developed over the past few years, a ubiquitous and integrated architecture is envisioned for future wireless communication. An important optimization issue in such an integrated system is how to minimize the overall communication cost by intelligently utilizing the avail- able heterogeneous wireless technologies while, at the same time, meeting the quality-of-service requirements of mobile users. In this paper, we first identify the cost-minimization (CM) problem to be NP-hard. We then present an efficient minimum-cost data- delivery algorithm based on linear programming (LP), with various constraints, such as channel bandwidth, link costs, delay budgets, and user mobility, taken into consideration. In case of insufficient bandwidth for communication with the core network, prefetch is employed to fully utilize the wireless-network capacity. If multiple routes are available, a probability-based approach is taken for CM. Extensive simulations are carried out to evaluate the proposed CM scheme. Our results show that the proposed LP approach can effectively reduce the overall communication cost, with small overhead (< 3%) for signaling, computing, and handoff. We expect that minimum-cost data delivery will become imperative for the future heterogeneous wireless networks and the emerging 4G wireless systems. [ABSTRACT FROM AUTHOR]

Many applications in wireless sensor networks re- quire sensor nodes to obtain their absolute or relative geographical positions. Although various localization algorithms have been recently proposed, most of them require nodes to be equipped with range-determining hardware to obtain distance information. In this paper, we propose a concentric anchor beacon (CAB) localization algorithm for wireless sensor networks. CAB is a range-free approach and uses a small number of anchor nodes. Each anchor emits beacons at different power levels. From the information received by each beacon heard, nodes can determine in which annular ring they are located within each anchor. Each node uses the approximated center of intersection of the rings as its position estimate. We also propose two heuristics, namely CAB with Equal Area and CAB with Equal Width, to determine the transmitting power levels of the beacons. Simulation results show that the estimation error is reduced by half when anchors transmit beacons at two different power levels instead of at a single power level. CAB also gives a lower estimation error than some other range-free localization schemes (e.g., Centroid and Approximated Point-In-Triangulation) when the anchor-to-node range ratio is less than 4. [ABSTRACT FROM AUTHOR]

In this paper, we consider the high-K-factor Ricean channel, where the channel mean is of arbitrary rank, and the fading channel components are correlated. We propose two suboptimal linear precoding schemes based on the knowledge of the channel mean and covariance at the transmitter. The first precoder is derived from an approximate ergodic capacity expression for the high-K-factor Ricean channels, whereas the second is derived from Jensen's inequality. We compare the capacity obtained to the true ergodic capacity found by using a numerical convex optimization algorithm. We further investigate the impact of the fading channel covariance, the rank of the channel mean, and the K-factor on the precoding schemes and the achievable ergodic capacity limit. [ABSTRACT FROM AUTHOR]

Orthogonal space-time block coding (OSTBC) in multiple-antenna wireless systems has recently emerged as one of the most promising reliability-enhancing technologies for high-speed, high-quality data services. In this paper, we propose a technique to achieve joint channel estimation and symbol detection for OSTBC in frequency-selective fading channels. The key observation is that a multiple-input-single-output system, which is using OSTBC, can be transformed into an equivalent single-input-multiple-output system using the implicit redundancy in OSTBC. This allows a probabilistic method, known as the Baum-Welch algorithm, to be applied at each output branch. As each output branch is a function of the same input, redundant information may be exchanged between the multiple branches to improve detection performance. The proposed technique does not require multiple antennas at the receiver and only has moderate computational complexity. Furthermore, the Cramer-Rao lower bound (CRB) is also developed to facilitate performance analysis. Simulation results are provided to demonstrate the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Mobile positioning has drawn significant attention in recent years. Nonline-of-sight (NLOS) propagation error is the dominant error source in mobile positioning. Most previous research in this area has focused on NLOS identification and mitigation. In this paper, we investigate new positioning algorithms to take advantage of the NLOS propagation paths rather than canceling them. Based on a prior information about the NLOS path, a geometrical approach is proposed to estimate mobile location by using two NLOS paths. On top of this, the least-squares (LS)-based position estimation algorithm is developed to take multiple NLOS paths into account, and its performance in terms of root mean-square error (RMSE) is analyzed. A general LS algorithm considering both LOS and NLOS paths is also derived, and the maximum likelihood-based algorithm is presented to jointly estimate the mobile's and scatterers' positions. The Cramer-Rao lower bound on the RMSE is derived for the benchmark of the performance comparison. The performance of the proposed algorithms is evaluated analytically and is done via computer simulations. Numerical results demonstrate that the derived analytical results closely match the simulated results. [ABSTRACT FROM AUTHOR]

In this paper, a new channel-estimation algorithm based on maximum-likelihood (ML) algorithm for estimation and tracking of the multiple-input-multiple-output (MIMO) channels is presented. The ML algorithm presents the optimum estimation when the exact channel model is known. The derived channel-estimation algorithm is very efficient, with a computational complexity comparable to the least mean square and much lower than the recursive least squares and the Kalman algorithms. The proposed algorithm is analyzed, and the effect of the channel-tracking error is applied as a modifying component for the derived algorithm. The proposed algorithm is simulated for half- and full-rank flat-fading time-varying MIMO channels for the different values of fDT, Eb/No, and training lengths via Monte Carlo simulation technique. The minimum mean-square-error (mmse) joint detector is considered as the detection algorithm. The output of the mmse receiver is considered as the virtual training data in the blind mode of operation: the same as in the decision-directed algorithm. By various simulations, the bit error rate and the mse of tracking the proposed algorithm for different values of fDT, presenting the speed of channel variations, are evaluated and compared with the Kalman filtering approach. By simulating the proposed algorithm for different values of the training length, the minimum training length required for different channel conditions is extracted. [ABSTRACT FROM AUTHOR]

This paper proposes a joint power and rate assignment (JPRA) algorithm to deal with multirate soft handoffs (SHOs) in mixed-size wideband code division multiple access cellular systems. This JPRA algorithm contains a link proportional power allocation scheme and an evolutionary computing rate assignment method to determine an appropriate allocation of transmission power and service rate for multirate SHOs. It can achieve power balancing among cells better than the conventional site-selection diversity transmission scheme with best effort rate allocation. Simulation results show that the JPRA algorithm can achieve better cell's service coverage and higher system capacity with and without the measurement errors during the active set selection. [ABSTRACT FROM AUTHOR]

One of the key challenges of next-generation wireless networks (such as enhanced general packet radio service) is the ability to provide different grades of quality of service to users. Weighted fair queueing (WFQ) is a popular scheduling algorithm to guarantee bounded delay, guaranteed throughput, and fairness. However, adapting the WFQ scheduler to wireless networks is not trivial due to location and weather-dependent variable data rates. In this paper, optimal schemes that are based on combining the WFQ with compensation techniques are proposed, which swap channel accesses among traffic flows that experience variable data rates, so that the variable data rates are transparent to the flows. It is also proposed here three periodic compensation methods and two event-driven methods. Two of the periodic methods provide maximum achievable throughput and maximum fairness. The two event-driven methods are completely distributed and are executed much less frequently than the periodic methods. [ABSTRACT FROM AUTHOR]

In this paper, novel connection admission control (CAC) algorithms that take into account the effect of mobility of users both inside and outside the cell in the downlink of third-generation mobile systems are developed. First, the system capacity, including the other-cell interference, subject to feedback between cells is studied. Then, effective bandwidth expressions for calls are obtained as a function of both their location in the cell as well as their class of traffic (i.e., voice versus data). Next, this formulation is used to derive two mobility-aware admission control algorithms, i.e., a priority CAC, where calls are accepted not only upon resource availability, but also through acceptance ratios that reflect their levels of priority, and a squeezing CAC, where elastic calls may be squeezed to a minimum agreed value, giving way to admit more calls in the system and to secure further ongoing mobile users. Using Markovian analysis, several performance measures are obtained, namely the blocking probability, the dropping probability, both intracell and intercell, as well as the overall cell throughput. The authors eventually investigate the performance of our CAC and show how to extend the Erlang capacity bounds, i.e., the set of arrival rates such that the corresponding blocking/dropping probabilities are kept below predetermined thresholds. [ABSTRACT FROM AUTHOR]

The problem of providing throughput fairness in a wired-cum-wireless network where the wireless portion is an 802.11 wireless local area network (WLAN) is addressed. Due to the distributed nature of the primary 802.11 media access control protocol and the unpredictability of the wireless channel, quality of service guarantees in general and fairness in particular are hard to achieve in WLANs. This fact seriously compromises the interaction between 802.11-based networks and well-established architectures such as DiffServ. The focus of this paper is on transmission control protocol (TCP) traffic, and two fundamental problems related to throughput fairness are identified. First, the basic requirement of providing fair access to all users conflicts with the nature of TCP, which is fair only under certain conditions and hardly met by 802.11b WLANs. Second, short-lived TCP flows that are sensitive to losses during the early stages of TCP window growth need to be protected. To address these issues, a logical-link-control-layer algorithm that can be implemented at both access points and wireless stations is proposed. The algorithm aims at guaranteeing fair access to the medium to every user, independent of their channel conditions. At the same time, the proposed scheme protects short-lived flows, while they strive to get past the critical "small window regime." A simulation study that shows the effectiveness of the new algorithm in comparison to the standard 802.11b implementation is presented. [ABSTRACT FROM AUTHOR]

It has been well recognized that significant throughput gains can be leveraged in multiuser wireless communication systems by exploiting multiuser diversity with a smart scheduler. This scheduler collects channel state information (CSI) from all users and allocates the resources to the user(s) experiencing favorable channel conditions. However, for a frequency-division-duplex system with a large number of users, how to efficiently collect the required CSI will be a challenging task, especially when the feedback links are of limited capacity. In this paper, we propose a scheduling algorithm to exploit multiuser diversity with possibly imperfect one-bit channel state feedback. The basic idea is to define a threshold λ and let each user report one-bit information to the scheduler about the comparison between its measured channel fading level and λ. Correspondingly, the scheduler uses these feedback bits to classify all users into two sets and assigns the channel to one user belonging to the set experiencing favorable channel conditions. Several implementation schemes are developed by attacking the optimization of λ under different system configurations, covering both the case when the one-bit feedback is perfect and those when the one-bit feedback is imperfect. Computer simulations show that when the user number is large, say, more than ten users, the proposed scheduling supports significantly larger data rate over the round-robin scheduling, while in comparison with the optimum scheduling with complete CSI, the performance loss is limited if the one-bit feedback is of high reliability. In addition, our studies show that we can effectively enhance the robustness against feedback imperfectness by incorporating the feedback reliability into optimization of λ. [ABSTRACT FROM AUTHOR]

In this paper, a new mathematical programming formulation is developed for minimizing the schedule length in multihop wireless networks based on the optimal joint scheduling of transmissions across multi-access communication links and the allocation of transmit power levels while meeting the requirements on the signal-to-interference-plus-noise ratio at intended receivers. The authors prove that the problem can be represented as a mixed-integer linear programming (MILP) and show that the latter yields a solution that consists of transmit power levels that are "strongly Pareto optimal." It was demonstrated that the MILP formulation can be used effectively to derive optimal scheduling and power levels for networks with as many as 30 designated communication links. The authors show that the MILP formulation can also be effectively solved to provide upper and lower bounds (corresponding to an approximation factor Δ) for the optimum schedule length of networks with as many as 100 designated links. It is proved that the integrated link scheduling and power control problem (ILSP) is NP-complete. Consequently, a heuristic algorithm of polynomial complexity is developed and investigated for solving the problem in a timely and practical manner. The algorithm is based on the properties of a novel interference graph, i.e., the "generalized power-based interference graph," whose "chromatic" and "independence numbers" provide fundamental bounds for the ILSP. It is demonstrated that the frame length of schedules realized by the heuristic scheme resides in the 25th percentile of those attained by the optimal mechanism for randomly generated topologies with as many as 30 designated communication links. Furthermore, it is shown that the algorithm significantly outperforms a corresponding algorithm presented in the literature. [ABSTRACT FROM AUTHOR]

Applying adaptive modulation combined with scheduling in a shared data channel can substantially improve the spectral efficiency for wireless systems. This performance gain results from the multiuser diversity, which exploited independent channel variations across multiple users. In this paper, we present a cross-layer analysis to integrate physical-layer channel characteristics, media access control (MAC) layer scheduling strategies, and the network layer issue of heterogeneous traffic intensity across near-far users. Specifically, for radio channel characteristics, we take account of path loss, slowly varying log-normal shadowing and fast-varying Nakagami fading. We also evaluate the impact of selective transmit diversity on the throughput and fairness of wireless data networks. Furthermore, we consider three MAC schedulers: random scheduler, greedy scheduler (GS), and a newly proposed queue-length-based scheduler (QS). By applying the proposed cross-layer analytical framework, the following insights can be gained. First, for the three considered schedulers, channel fluctuations induced by Nakagami fading or log-normal shadowing can improve both total throughput and fairness. Second, using selective transmit diversity can improve throughput, but is unfavorable for the fairness performance. Third, the GS and the QS methods can improve throughput at the expense of unfairness to the far users. However, the throughput improvement from using the GS and the QS decreases as the traffic intensity of the far user increases. In summary, this cross-layer analysis can be used to develop new scheduling mechanisms for achieving better tradeoff between the fairness and throughput for wireless data networks. [ABSTRACT FROM AUTHOR]

Energy constraints have a significant impact on the design and operation of wireless sensor networks. This paper investigates the base station (BS) selection (or anycast) problem in wireless sensor networks. A wireless sensor network having multiple BSs (data sink nodes) is considered. Each source node must send all its locally generated data to only one of the BSs. To maximize network lifetime, it is essential to optimally match each source node to a particular BS and find an optimal routing solution. A polynomial time heuristic is proposed for optimal BS selection and anycast via a sequential fixing procedure. Through extensive simulation results, it is shown that this algorithm has excellent performance behavior and provides a near-optimal solution. [ABSTRACT FROM AUTHOR]

Energy-efficient routing is a critical problem in multihop wireless networks due to the severe power constraint of wireless nodes. Despite its importance and many research efforts toward it, a distributed routing algorithm that maximizes network lifetime is still missing. To address this problem, this paper proposes a novel utility-based nonlinear optimization formulation to the maximum lifetime routing problem. Based on this formulation, a fully distributed localized routing algorithm is further presented, which is proved to converge at the optimal point, where the network lifetime is maximized. Solid theoretical analysis and simulation results are presented to validate the proposed solution. [ABSTRACT FROM AUTHOR]

A new multicarrier system, termed multisymbol encapsulated orthogonal frequency division multiplexing (MSE-OFDM), is proposed, in which one cyclic prefix (CP) is used for multiple OFDM symbols. The original motivation for the MSE-OFDM proposal is to reduce the redundancy due to the CP in static-channel environments. The authors then found that an alternative implementation of the system can be used to improve the robustness to frequency offset and reduce the peak-to-average power ratio (PAPR). Equalization and demodulation algorithms for the MSE-OFDM system are proposed. A new preamble and the corresponding frequency-offset and channel estimation techniques are studied for the MSE-OFDM system. Using the proposed MSE-OFDM preamble, the joint maximum likelihood (ML) estimation of the frequency offset and the channel impulse response (CIR) is investigated in this paper. Possible ways to reduce the joint estimation complexity, including exploitation of the preamble structure, approximation of the joint ML estimator, and fast Fourier transform (FFT) pruning, are discussed. The performance of the proposed MSE-OFDM systems and channel estimators are analyzed and verified through numerical simulations. An analysis on the bandwidth efficiency, the performance with frequency offset, and the PAPR of the MSE-OFDM system are also presented. [ABSTRACT FROM AUTHOR]

A network of sensors can be used to obtain state-based data from the area in which they are deployed. To reduce costs, the data, sent via intermediate sensors to a sink, are often aggregated (or compressed). This compression is done by a subset of the sensors called ‘aggregators.’ Inasmuch as sensors are usually equipped with small and unreplenishable energy reserves, a critical issue is to strategically deploy an appropriate number of aggregators so as to minimize the amount of energy consumed by transporting and aggregating the data. In this paper, the authors first study single-level aggregation and propose an Energy-Efficient Protocol for Aggregator Selection (EPAS) protocol. Then, they generalize it to an aggregation hierarchy and extend EPAS to Hierarchical EPAS. The optimal number of aggregators with generalized compression and power-consumption models was derived, and fully distributed algorithms for aggregator selection were presented. Simulation results show that the algorithms significantly reduce the energy consumption for data collection in wireless sensor networks. Moreover, the algorithms do not rely on particular routing protocols and are thus applicable to a broad spectrum of application environments. [ABSTRACT FROM AUTHOR]

Joint scheduling and power control schemes have previously been proposed to reduce power dissipation in wireless ad hoc networks. However, instead of power consumption, throughput is a more important performance concern for some emerging multihop wireless networks, such as wireless mesh networks. This paper examines joint link scheduling and power control with the objective of throughput improvement. The MAximum THroughput link Scheduling with Power Control (MATH-SPC) problem is first formulated and then a mixed integer linear programming (MILP) formulation is presented to provide optimal solutions. However, simply maximizing the throughput may lead to a severe bias on bandwidth allocation among links. To achieve a good tradeoff between throughput and fairness, a new parameter called the demand satisfaction factor (DSF) to characterize the fairness of bandwidth allocation and formulate the MAximum Throughput fAir link Scheduling with Power Control (MATA-SPC) problem is defined. An MILP formulation and an effective polynomial-time heuristic algorithm, namely, the serial linear programming rounding (SLPR) heuristic, to solve the MATA-SPC problem are also presented. Numerical results show that bandwidth can be fairly allocated among all links/flows by solving the MILP formulation or by using the heuristic algorithm at the cost of a minor reduction of network throughput. In addition, extensions to end-to-end throughput and fairness and multiradio wireless multihop networks are discussed. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of two control parameters of the Universal Mobile Telecommunications System (UMTS) handoff algorithm on the total peak base station (BS) transmit power required per mobile station (MS) to satisfy a prescribed outage probability. Denoting the set of BSs supporting an MS in soft handoff (SH) as the active group, the first parameter n is the maximum allowed size of the active group. The second, denoted r, is the upper limit on the difference between the path loss of the dominant BS and that of any other member of the active group, where the term "dominant" refers to the BS with the lowest path loss to the MS. It was assumed that the MS is equipped with a Rake receiver capable of performing "maximal ratio combining" of the signals it receives from the transmitting BSs. General analytical derivations along with results derived for specific situations through numerical integration are presented. [ABSTRACT FROM AUTHOR]

In this paper, we present a unified approach for the computation of the outage probability, the level crossing rate (LCR), and the average outage duration (AOD) of selection combining (SC) in the presence of multiple cochannel interferences and under both minimum signal-to-interference ratio (SIR) and desired signal power constraints. We consider three selection algorithms, namely, 1) the best signal power algorithm; 2) the best SIR algorithm; and 3) the best total power (desired plus interference) algorithm. As a specific application example, we analyze the three algorithms for a low-complexity dual-branch SC receiver subject to multiple interferers over Rayleigh fading channels. When applicable, the new results are compared to those previously reported in the literature dealing with the outage probability, AOD, and LCR of 1) interference-limited systems and 2) power-limited systems. Numerical examples show that the minimum desired signal power constraint induces a floor to the outage probability, AOD, and LCR performance measures. They also show that the best SIR algorithm provides the best outage probability and AOD performance for low average SIR. On the other hand, the best signal power algorithm and the best S + I algorithm outperform the best SIR algorithm for high average SIR. It is also shown that the best SIR algorithm tends to have more outage level crossings. [ABSTRACT FROM AUTHOR]

This paper deals with a class of power control problems where the system link gains are assumed to be time varying and the signal-to-interference ratio (SIR) estimates are allowed to be corrupted with bounded noises. A simple control algorithm is devised by applying a distributed, fixed step approach. It is a feedback algorithm that requires only local information. By modifying the distributed, fixed step power control algorithm proposed by Sung and Wong, we obtain here a more robust version that can handle time varying link gains and measurement noises. The convergence property of the new algorithm is established and simulation studies were carried out to show that it is effective. [ABSTRACT FROM AUTHOR]

A novel full rate space-time turbo trellis code, referred to as an assembled space-time turbo trellis code (ASTTTC), is presented in this paper. For this scheme, input information binary sequences are first encoded using two parallel concatenated convolutional encoders. The encoder outputs are split into four parallel streams and each of them is modulated by a QPSK modulator. The modulated symbols are assembled by a predefined linear function rather than punctured as in the standard schemes. This results in a lower code rate and a higher coding gain over time-varying fading channels. An extended two-dimensional (2-D) log-MAP (maximum a posteriori probability) decoding algorithm, which simultaneously calculates two a posteriori probabilities (APP), is developed to decode the proposed scheme. Simulation results show that, under the same conditions, the proposed code considerably outperforms the conventional space-time turbo codes over time-varying fading channels. [ABSTRACT FROM AUTHOR]

With the convergence of multimedia applications and wireless communications, there is a need to support real-time traffic in wireless networks. In general, real-time packets must be delivered before a certain delay upper bound. In the literature, feasible earliest due date (FEDD) is one of the scheduling algorithms proposed to provide packet delay upper bound guarantees over a time-varying wireless channel. However, FEDD is reactive with respect to changes in the wireless channel. In view of this, we propose a novel deadline-based scheduling algorithm called proactive earliest due date (PEDD), which dynamically adjusts a packet's deadline in anticipation of an upcoming change in the channel condition. Similar to FEDD, PEDD is idealistic, as they both assume the availability of the exact channel knowledge. This is not implementable and, thus, this paper further proposes a realistic version of PEDD, called R-PEDD. R-PEDD uses a probing mechanism to acquire the channel knowledge, which in turn is used for the packet deadline adjustment. Since probe packets consume bandwidth, a modified version of R-PEDD, called R-PEDD+ is proposed to derive the required channel information from recent packet transmissions. We have performed extensive simulations using OPNET to evaluate the performance of these proposed algorithms. In short, PEDD always outperforms a couple of existing algorithms in the literature. R-PEDD and R-PEDD+ are both capable of approximating the performance of the idealistic PEDD in a realistic wireless channel. However, their performance deteriorates with more rapid changes in the channel condition. [ABSTRACT FROM AUTHOR]

For the fast access with high reliability, a single grant allows a transmitter to transmit multiple redundant packets with new redundancy information in the time domain without waiting for feedback from a receiver. However, entire redundant packets shall be retransmitted in response to a negative acknowledgment of those redundant packets, which increases the service latency. To reduce a long HARQ RTT due to a number of redundant packets, we propose packet-by-packet parallel processing that achieves lower latency by alleviating the long HARQ RTT of repeated transmission. We also provide a model and analysis for repeated transmission functionality, in terms of the wireless transmission latency with packet-by-packet processing. Numerical analysis and simulation in various network environments show that the proposed algorithm achieves lower latency without trading reliability off. [ABSTRACT FROM AUTHOR]

In this paper, the problem of subspace-based blind adaptive multiuser detection in multirate direct-sequence code-division multiple-access (DS-CDMA) systems adopting short (periodic) spreading codes is considered. The solution that we propose is based on the well-known formulation of the linear minimum mean-squared error and decorrelating detectors in terms of signal subspace parameters. Since in a multirate scenario the correlation properties of the observable (and, hence, the signal subspace parameters) are periodically time-varying, classical subspace tracking algorithms, which assume that the subspace to be tracked is time-invariant or slowly time-varying, are shown to be not useful in this situation. A new recursive cyclic subspace tracking algorithm is thus developed. This procedure, which is based on a generalization of the PASTd algorithm, is able to capture the periodical variations of the signal subspace, and thus enables subspace-based blind adaptive multiuser detection in multirate CDMA systems. The proposed algorithm has a smaller computational complexity than the recently developed cyclic recursive-least-squares procedure, and, as numerical results confirm, is capable of providing very satisfactory performance. [ABSTRACT FROM AUTHOR]

This paper deals with the performance evaluation of a pilot-aided channel parameter estimation method suitable for applications in direct-sequence code-division multiple-access (DS-CDMA) communication systems. Differently from previous approaches, a suitable selective interference cancellation algorithm is used in order to reduce multipath interference on the channel parameter estimation and the detection of the information-bearing signals due to pilot signal replicas. Simulation results demonstrate the good channel parameter estimation capability of the proposed method in the case of uplink communications and different types of receiving schemes. In order to highlight the good behavior of the proposed approach, performance comparisons are shown with the ideal case of perfect knowledge of the channel parameters values, as well as with the classical implementation of the channel parameter estimation algorithm considered herein. [ABSTRACT FROM AUTHOR]

We first extend the definition of the secrecy outage probability to wireless systems with adaptive transmission rates and secrecy rates. Then, we consider a scheduling problem in the aforementioned system, jointly considering the reliability, security, and stability, where the scheduler tries to allocate wireless resources to the legitimate users, stabilize the system, and minimize the secrecy outage probability. A stochastic network optimization framework is used to decompose the problem, and an online algorithm is proposed. We further consider a related problem, discuss the optimal solution, and show that the proposed algorithm cannot lead to optimal solution in some scenarios. By comparing the offline algorithm with our first algorithm, we further propose a second refined online algorithm, which is an optimal one. Extensive simulations are conducted to show the impact of the information arrival rate and the channel conditions on the system secrecy outage probability. These observations provide important insights and guidelines for the design and resource management of future wireless networks using secure communication technologies. [ABSTRACT FROM AUTHOR]

A multiple-relay assisted cooperative automatic-repeat-request (CARQ) system is proposed in interference-limited scenario, where multiple-user detection (MUD) receivers using successive interference cancellation (SIC) are employed at the relay nodes (RNs) and the destination node (DN) to combat cochannel interference (CCI). We analyze the outage performance and propose a novel best effort-detection-based opportunistic relay selection (BED-ORS) scheme, which achieves significantly better outage performance than the traditional highest SNR-based ORS scheme offered in the literature. Moreover, considering the effects of the outdated channel state information (CSI), an improved-BED-ORS (I-BED-ORS) scheme is proposed to enhance the robustness against CSI imperfections. [ABSTRACT FROM PUBLISHER]

Intercell interference coordination (ICIC) techniques not only help improve cellular data coverage but allow more efficient use of a valuable wireless spectrum as well. This paper investigates soft frequency reuse (SFR), which is a form of ICIC, for long-term evolution (LTE) systems. By analyzing the throughput of the SFR scheme, we find that classifying cell-edge users and cell-center users is critical. Thus, we develop low-complexity decentralized SFR scheduling algorithms that include optimal user classification and balance throughput and fairness among multiusers. We also propose suboptimal methods to reduce computational complexity. Computer simulation demonstrates that gains of the proposed SFR algorithm can improve the fifth percentile user throughput by 26% while maintaining the same cell average throughput, compared with a non-ICIC system. [ABSTRACT FROM PUBLISHER]

This paper presents a novel concept that is intended to exploit more thoroughly the sharable bandwidth of public-shared networks, such as FON networks, through the construction of an efficient, robust, and high-availability video delivery system. By using bandwidth expansion, only a small amount of bandwidth is spent on the video streaming source, despite the system being capable of streaming content to numerous clients simultaneously. Two algorithms were designed to optimize the public-shared bandwidth, wherein the needs of all clients are addressed, despite minimal usage of system resources. In this research, a resource management scheme was developed for recycling and reusing resources to improve the continuity of streaming experienced by clients and to reduce the overall system load on the devices involved. An implementation of the proposed system demonstrates the overall feasibility of the concept. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the resource allocation problem in a single-user relay-aided cognitive radio (CR) underlay network. Both the CR network and the primary network operate under the orthogonal frequency-division multiplexing (OFDM) scheme. Different from the conventional resource allocation problem, the relay node here is capable of performing subcarrier permutation over two hops such that the signal received over a particular subcarrier is forwarded via a different subcarrier. The objective is to maximize the throughput of the CR network subject to a limited power budget at the secondary source and the relay node and to interference constraints at the primary receiver. Optimization is performed under a unified framework where power allocation at the source node, power allocation at the relay node, and subcarrier pairing at the two hops are jointly optimized. The joint resource-allocation scheme yields an asymptotically optimal solution. We further design a suboptimal algorithm that sacrifices little on performance but could significantly reduce computational complexity. Finally, numerical examples are provided to corroborate the proposed studies. [ABSTRACT FROM PUBLISHER]

Enhancing the transmission rate for a better spectral utilization is always the ultimate goal of any wireless network. In this paper, we consider the problem of optimal power and rate allocation to maximize the transmission rate of a cognitive radio (CR) operating in the spectrum sharing (SS) CR network (CRN). Unlike previous literature that takes into account the amount of interference to the primary system (PS) as the protection criterion, we reconsider the protection to the PS and CRs through different levels of protection in signal-to-interference-plus-noise ratio (SINR). We propose the concept of effective signal coverage called the permissible space for optimal power and rate adaption. The permissible space for a cognitive transmitter spans over a 3-D space, and it varies according to the channel statistics. Through detecting to which permissible space the cognitive receiver belongs, a novel algorithm suited for distributed CR operation is proposed. Numerical results confirm that our algorithm implemented in the SS CRN achieves a significant enhancement in sum rate, as compared with that of an opportunistic spectrum access (OSA) CRN. [ABSTRACT FROM PUBLISHER]

We study the problem of minimum-number full-view area coverage in camera sensor networks, i.e., how to select the minimum number of camera sensors to guarantee the full-view coverage of a given region. Full-view area coverage is challenging because the full-view coverage of a 2-D continuous domain has to be considered. To tackle this challenge, we first study the intrinsic geometric relationship between the full-view area coverage and the full-view point coverage and prove that the full-view area coverage can be guaranteed, as long as a selected full-view ensuring set of points is full-view covered. This leads to a significant dimension reduction for the full-view area coverage problem. Next, we prove that the minimum-number full-view point coverage is NP-hard and propose two approximation algorithms to solve it from two different perspectives, respectively: 1) By introducing a full-view coverage ratio function, we quantify the “contribution” of each camera sensor to the full-view coverage through which we transform the full-view point coverage into a submodular set cover problem and propose a greedy algorithm (GA); and 2) by studying the geometric relationship between the full-view coverage and the traditional coverage, we propose a set-cover-based algorithm (SCA). We analyze the performance of these two approximation algorithms and characterize their approximation ratios. Furthermore, we devise two distributed algorithms that obtain the same approximation ratios as GA and SCA, respectively. Finally, we provide extensive simulation results to validate our analysis. [ABSTRACT FROM PUBLISHER]

Channel estimation error results in severe performance deterioration in wireless networks. In this paper, we study the impact of imperfect channel estimation (ICE) on the outage performance of bidirectional relaying where the two sources have asymmetric traffic requirements (ATRs). In particular, we focus on the amplify-and-forward (AF) relay-assisted multiple-access broadcast (MABC) protocol, i.e., MABC-AF, which has received much attention due to its high spectrum efficiency and low complexity. In the single-relay scenario, we derive exact and generalized closed-form expressions for system outage probability, which indicate that the system outage is determined by the unidirectional outage in the case of highly asymmetric traffic patterns. For more insights into our approach, the closed-form asymptotic expressions are also evaluated, manifesting the interesting error floor (EF) phenomenon due to ICE. Using these analytical results, we further develop a robust and practical optimum power-allocation (OPA) algorithm that minimizes the system outage probability under aggregate and individual node power constraints. In the multirelay scenario, by taking into account the traffic knowledge, a novel relay selection criterion is proposed for asymmetric MABC-AF, followed by its impact on the system outage probability in the presence of ICE. Numerical results validate the accuracy of our analytical results and highlight the effect of the proposed OPA algorithm under various traffic requirements and channel estimation errors. Furthermore, the results also show that the proposed relay selection criterion is superior to the classical max–min criterion with ATRs, and the performance improvement becomes remarkable as channel estimation error increases. [ABSTRACT FROM PUBLISHER]

In this paper, we propose two cross-layer algorithms, namely, the Power-optimal Scheduling Algorithm (PSA) and the Throughput-optimal Scheduling Algorithm (TSA), to minimize energy consumption and to maximize throughput, respectively, in multihop wireless networks. Our algorithms guarantee a flow-based minimum data rate and jointly integrate congestion control, power allocation, routing, and link rate scheduling. Different from traditional algorithms that assume infinite buffers, the proposed algorithms deterministically upper bound the flow-based packet queue length and thus can be employed in multihop networks with finite buffers. In addition, the algorithms achieve a power expenditure/throughput “\epsilon-close” to the optimal value, with a tradeoff of order O(\1/\epsilon) in buffer size. The average end-to-end delay upper bound can also be derived from the finite buffer property. Finally, numerical results are presented to show the performance of the two algorithms with different system parameters. [ABSTRACT FROM PUBLISHER]

In this paper, a novel low-complexity tree-search (TS) algorithm, which is referred to as a hierarchical tree search (HTS), is proposed for soft-output multiple-input–multiple-output (MIMO) detection to mitigate the performance loss caused by an early termination. The proposed HTS algorithm is realized by the following two components: the hierarchical set partitioning to find all hypotheses with reasonable quality as fast as possible and to fairly improve them and the new cost metric to determine the search order by considering the quality of the hypotheses found so far. Through simulation, it is shown that the performance–complexity tradeoff of the proposed HTS algorithm surpasses those of the existing algorithms in various MIMO configurations. [ABSTRACT FROM PUBLISHER]

In this paper, we study the multiple-input–multiple-output two-way relay channel (MIMO-TWRC) when the nodes and relay use analog beamforming. Following the amplify-and-forward (AF) strategy, the problem consists of finding the transmit and receive beamformers of the nodes and relay (as well as the power allocated to each one) that achieve the boundary of the optimal rate region. To solve it, we first express the optimal node beamformers in terms of relay beamformers and then show that the optimal rate region can efficiently be characterized using convex optimization techniques. We also extend our study to the multiple-relay scenario when the source nodes are single antenna and propose a distributed algorithm to compute the relay beamforming matrices. The proposed algorithm consists of solving two different subproblems. First, each individual TWRC is optimized independently. Next, a distributed beamforming is applied to make the signals from the relays add up coherently at the source nodes. Numerical examples are provided to illustrate the performance of the proposed techniques and to compare the performance of analog beamforming architectures against conventional MIMO schemes that operate at the baseband. [ABSTRACT FROM PUBLISHER]

Graphical models have been widely applied in solving distributed inference problems in wireless sensor networks (WSNs). In this paper, the factor graph (FG) is employed to model a distributed inference problem. Using particle filtering methods, a sequential particle-based sum-product algorithm (SPSPA) is proposed for distributed inference in FGs with continuous variables and nonlinear local functions. Importance sampling methods are used to sample from message products, and the computational complexity of SPSPA is thus linear in the number of particles. The SPSPA is applied to a distributed tracking problem, and its performance is evaluated based on the number of particles and the measurement noise. [ABSTRACT FROM PUBLISHER]

The intravehicular wireless sensor network (IVWSN) is a promising new research area that can provide part cost, assembly, maintenance savings, and fuel efficiency through the elimination of the wires and enables new sensor technologies to be integrated into vehicles, which would otherwise be impossible using wired means such as Intelligent Tire. The close interaction of communication with control systems, strict reliability, energy efficiency, and delay requirements in such a harsh environment that contains a large number of reflectors that operate at extreme temperatures are distinguishing properties of this network. In this paper, we investigate optimal power control, rate adaptation, and scheduling for an ultrawideband-based IVWSN for one-electronic-control-unit (ECU) and multiple-ECU cases. For the one-ECU case, we show that the optimal rate and power allocation is independent of the optimal scheduling algorithm. We prove the NP-hardness of the scheduling problem and formulate the optimal solution as a mixed-integer linear programming (MILP) problem. We then propose a 2-approximation algorithm, which is the smallest period into the shortest subframe first (SSF) algorithm. For the multiple-ECU case, where the concurrent transmission of links is possible, we formulate the optimal power control as a geometric-programming problem and optimal scheduling problem as an MILP problem where the number of variables is exponential in the number of links. We then propose a heuristic algorithm—the maximum-utility-based concurrency allowance algorithm—based on the idea of significantly improving the performance of the SSF algorithm in the existence of multiple ECUs by determining the sets of maximum utility. [ABSTRACT FROM PUBLISHER]