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This paper investigates simultaneous wireless information and power transfer (SWIPT) for a multiple-input–single-output (MISO) secrecy channel. First, transmit beamforming without artificial noise (AN) is designed to achieve the secrecy rate maximization problem subject to the transmit power and the energy harvesting (EH) constraints. This problem is not convex, but this can be solved by applying a bisection search to a sequence of the associated power minimization problems, each of which can be solved by using a novel relaxation approach. Moreover, we extend our proposed algorithms to the robust case by incorporating channel uncertainties. Then, transmit beamforming with AN is investigated for the secrecy rate maximization problem, where two relaxation approaches are presented, i.e., a two-level optimization algorithm and a successive convex approximation (SCA), to solve the secrecy rate maximization problem. In addition, tightness analyses of rank relaxation are provided to show that the optimal transmit covariance matrix exactly returns rank one. Simulation results are provided to validate the performance of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

Recent advances in loop interference cancelation techniques enable full-duplex relaying (FDR) systems, which transmit and receive simultaneously in the same band with high spectrum efficiency. Meanwhile, wireless virtualization has attracted a lot of attention from both academia and industry because it can provide more flexibility, diversity, and other benefits in the process of wireless network design, construction, operation, and management. In this paper, we introduce the idea of wireless virtualization into FDR cellular networks. Then, the problem of energy-aware virtual resource management is formulated as a three-stage Stackelberg game. The subgame perfect equilibrium for each stage is analyzed. In addition, the interplays of the three-stage game are discussed, and an iterative algorithm is proposed to obtain the Stackelberg equilibrium solution. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we study energy-efficient power allocation in distributed antenna systems (DASs). Unlike previous works that assumed perfect channel-state information (CSI) at the transmitter, we investigate a more practical case, where only the slowly varying large-scale CSI is known, to reduce the system overhead for CSI acquisition. Under a generalized DAS model, the power allocation problem for energy-efficiency (EE) maximization is formulated as a nonconvex fractional programming problem. Using the random matrix theory, the nonlinear fractional programming theory, and the saddle-point theory, we propose an iterative algorithm that achieves the global optimal solution. We also show that deploying the antennas in a distributed manner may enlarge the region where the optimal EE and the optimal spectral efficiency (SE) can be simultaneously achieved. Accordingly, we suggest the DAS-like way to densify the future 5G and beyond cellular networks to achieve EE and SE simultaneously. [ABSTRACT FROM PUBLISHER]

We present in this paper a novel proactive interference avoidance scheme for mobile-to-mobile (M2M) communication as an underlay in Long-Term Evolution (LTE) downlink networks. The proposed scheme introduces an intelligent user-selective resource allocation algorithm that aims to proactively avoid interference between M2M pairs and LTE regular users while achieving a satisfactory link budget for both M2M and LTE regular links. The proposed resource allocation algorithm is based on a novel low-complexity interference estimation approach that requires only channel quality indicator (CQI) information (CSI). Since the CQI reporting mechanism has been already implemented in current LTE systems, the proposed algorithm is indeed practical and standard compatible, compared with the existing works that require perfect knowledge of the channel state information (CSI). In this research, achievable data throughput with LTE-compliant adaptive modulation and coding has been adopted as the optimization measurement, rather than the information-theoretic capacity. Therefore, the performance of the proposed scheme is practically realizable in LTE communication systems. Since the performance of the proposed scheme highly relies on the accuracy of CQI feedback, we also carry out performance analysis to evaluate the impact of CQI estimation error and delay. The simulation results show that the total achievable data throughput for LTE networks is dramatically enhanced by M2M communication with this proposed interference avoidance resource allocation scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we study the energy-efficient resource allocation problem for device-to-device (D2D) communication underlaying cellular networks, which aims to maximize the minimum weighted energy efficiency of D2D links while guaranteeing minimum data rates for cellular links. We first characterize the optimal power allocation of the cellular links to transform the original resource allocation problem into the joint subchannel and power allocation problem for D2D links. We then propose three resource allocation algorithms with different complexity levels, namely, dual-based, branch-and-bound (BnB), and relaxation-based rounding (RBR) algorithms. While the dual-based algorithm solves the problem by using the dual decomposition method, the BnB and RBR algorithms tackle the problem by employing the relaxation approach. We establish the strong performance guarantees for the proposed algorithms through theoretical analysis. Extensive numerical studies demonstrate that the proposed algorithms achieve superior performance and significantly outperform a conventional algorithm. [ABSTRACT FROM PUBLISHER]

Estimation of signal-to-noise ratio (SNR) plays an important role in many fields of communications. This paper addresses the SNR estimation of multiple phase-shift keying (MPSK) signals in Nakagami- $m$ fading channels. A family of SNR estimators with closed-form expressions is developed based on the relationship among different orders of moments. Compared with the existing algorithms, the estimator, which exploits the minimum order of moments, exhibits the best performance in general. We also propose a joint estimation algorithm for SNR and the fading factor when it is unknown. Simulation results verify the feasibility and superiority of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

The increasing densification of telecommunications mobile networks raises the compelling problem of exposure to electromagnetic fields (EMF). In this paper, we address the particular concept of heterogeneous networks, where small cells (SCs) are deployed to build up a second layer to the existing macrocell network. SC deployment is shown to be particularly effective in reducing EMF exposure, in addition to capacity enhancement. Previous studies on EMF have focused on the uplink (UL) and downlink (DL) components separately, although they are strongly correlated. Relying on the definition of the exposure index (EI) from the European FP7 Lexnet project, we evaluate the impact on EMF exposure due to SC deployment. Guidelines for EMF-efficient deployment of SCs are first presented and evaluated. Then, a new enhanced intercell interference coordination (eICIC) algorithm using UL and DL metrics to optimize capacity and exposure to EMF is proposed. Static and self-optimizing dynamic implementations of the solution are considered, using a utility function related to the sojourn time of the users. Time-domain and frequency-domain self-optimized eICIC are compared in terms of EMF exposure reduction and capacity enhancement. The eICIC algorithms are combined with a self-optimized coverage range expansion function leading to further reduction of the EI. The proposed solution for optimizing both capacity and exposure to EMF is compared with a capacity-driven solution based on the DL metrics only. Simulation results illustrate the performance gains obtained for the different SC deployment scenarios. [ABSTRACT FROM PUBLISHER]

In heterogeneous networks (HetNets), the load between macrocell base stations (MBSs) and small-cell base stations (SBSs) is imbalanced due to their different transmission powers and locations. This load imbalance significantly impacts system performance and affects the experience of mobile users (MUs) with different priorities. In this paper, we aim to distributively optimize the user association in HetNets with various user priorities to solve the load balancing problem. Since the user association is a binary matching problem, which is NP-hard, we propose a distributed belief propagation (BP) algorithm to approach the optimal solution. We first develop a factor graph model, using the network topology, to represent this user association problem. With this factor graph, we propose a novel distributed BP algorithm by adopting the proportional fairness as the objective. Next, we theoretically prove the existence of the fixed point in our BP algorithm. To be more practical, we develop an approximation method to significantly reduce the computational and communication complexity of the BP algorithm. Furthermore, we analyze some properties of the factor graph relevant to the performance of the BP algorithm using the stochastic geometry. Simulation results show that 1) the proposed BP algorithm well approaches the optimal system performance and achieves a much better performance compared with other association schemes and that 2) the analytical results on the average degree distribution and sparsity of the factor graph match with those obtained from the Monte Carlo simulations. [ABSTRACT FROM PUBLISHER]

Software-defined networking (SDN) and network function virtualization (NFV) are a promising system architecture and control mechanism for future networks. Although some works have been done on wireless SDN and NFV, recent advancements in device-to-device (D2D) communications are largely ignored in this novel framework. In this paper, we study the integration of D2D communication in the framework of SDN and NFV. An inherent challenge in supporting software-defined D2D is the imperfectness of network state information, including channel state information (CSI) and queuing state information, in virtual wireless (QSI) networks. To address this challenge, we formulate the resource sharing problem in this framework as a discrete stochastic optimization problem and develop discrete stochastic approximation algorithms to solve this problem. Such algorithms can reduce the computational complexity compared with exhaustive search while achieving satisfactory performance. Both the static wireless channel and time-varying channels are considered. Extensive simulations show that users can benefit from both wireless network virtualization and software-defined D2D communications, and our proposed scheme can achieve considerable performance gains in both system throughput and user utility under practical network settings. [ABSTRACT FROM PUBLISHER]

Opportunistic routing has been extensively studied and utilized in delay/disruption-tolerant networks. The extensive use of nodes' local information, e.g., the distance to the destination or the contact frequency with the destination, in such routing schemes can cause severe security and privacy problems. Existing solutions of anonymous routing can introduce undesired overhead and fail to provide the confidentiality of the routing metric. In this paper, we propose an advanced framework for opportunistic routing schemes, providing the following properties: confidentiality of the nodes' routing metric, anonymous authentication, and efficient key agreement for pairwise communication. A comprehensive evaluation, including security analysis, efficiency analysis, and simulation evaluation, is presented to show the security and feasibility of the proposed framework. [ABSTRACT FROM PUBLISHER]

This paper proposes a scheme for constructing an Internet Protocol (IP) version 6 over low-power wireless personal area networks (6LoWPAN) wireless sensor network based on a cluster tree. In the cluster generation algorithm, a cluster tree is always an isolated node with the maximum number of neighbor isolated nodes that launches the cluster generation process; therefore, the total number of cluster heads is minimized. In the cluster-tree construction algorithm, the cluster-tree architecture is proposed, and the cluster-tree construction algorithm minimizes the total number of nodes included in a cluster tree; therefore, the routing cost is reduced. In the cluster-tree repair algorithm, when a cluster head or a cluster associate node fails or moves, a new cluster head or cluster associate node is elected to maintain the cluster-tree topology. This paper compares the performance parameters of Least Cluster Change algorithm with Lowest-ID, Root-based Lowest-ID cluster constructing mechanism, and the proposed scheme, including the cluster-tree topology stability, the routing memory cost, and the routing update cost. The analytical data show that the performance of the proposed scheme is better. [ABSTRACT FROM PUBLISHER]

Location estimation and tracking for mobile stations have attracted a significant amount of attention in recent years. Different types of signal sources are considered available to provide measurement inputs for location estimation and tracking in heterogeneous wireless networks. Various techniques have been studied and combined for location tracking, e.g., the least square methods for location estimation associated with the Kalman filters for location tracking. In this paper, the hybrid unified Kalman tracking (HUKT) technique is proposed to provide an integrated algorithm for precise location tracking based on both time of arrival (TOA) and time difference of arrival (TDOA) measurements. A new variable is incorporated as an additional state within the Kalman filtering formulation to consider the nonlinear behavior in the measurement update process. The relationship between this new variable and the desired location estimate is applied in the state update process of the Kalman filter. Three different designs of hybrid factor are proposed to adaptively adjust the weighting value between the TOA and TDOA measurements. Moreover, similar concepts are also utilized in the design of unified Kalman tracking schemes for pure TOA and TDOA measurement inputs in this paper. Compared with existing schemes, numerical results illustrate that the proposed HUKT algorithm can achieve enhanced accuracy for mobile location tracking, particularly under environments with an insufficient number of measurements in one of the signal paths. [ABSTRACT FROM PUBLISHER]

The cross-layer utility maximization problem, which is subject to stability constraints for a multicommodity wireless network where all links share the same number of orthogonal channels, is considered in this paper. We assume a time-slotted network, where the channel gains randomly change from one slot to another. The optimal cross-layer network control policy can be decomposed into the folloing three subproblems: 1) flow control; 2) next-hop routing and in -node scheduling; and 3) power and rate control, which is also known as resource allocation (RA). These subproblems span the layers from the physical layer to the transport layer. In every time slot, a network controller decides the amount of each commodity data admitted to the network layer, schedules different commodities over the network's links, and controls the power and rate allocated to every link in every channel. To fully exploit the available multichannel diversity, we consider the general case, where multiple links can be activated in the same channel during the same time slot, and the interference is controlled solely through power and rate control. Unfortunately, the RA subproblem is not yet amendable to a convex formulation, and in fact, it is NP-hard. The main contribution of this paper is to develop efficient RA algorithms for multicommodity multichannel wireless networks by applying complementary geometric programming and homotopy methods to analyze the quantitative impact of gains that can be achieved at the network layer in terms of end-to-end rates and network congestion by incorporating different RA algorithms. Although the global optimality of the solution cannot be guaranteed, the numerical results show that the proposed algorithms perform close to the (exponentially complex) optimal solution methods. Moreover, they efficiently exploit the available multichannel diversity, which provides significant gains at the network layer in terms of end-to-end rates and network congestion. In addition, the assessment of the improvement in performance due to the use of multiuser detectors at the receivers is provided. [ABSTRACT FROM PUBLISHER]

This paper considers the transmission of scheduling information in orthogonal frequency-division multiple-access (OFDMA)-based cellular communication systems such as the Third-Generation Partnership Project (3GPP) long-term evolution (LTE). These systems provide efficient usage of radio resources by allowing users to be dynamically scheduled in both frequency and time. This requires considerable amounts of scheduling information to be sent to the users. This paper compares two basic transmission strategies: transmitting a separate scheduling message to each user versus broadcasting a joint scheduling message to all users. Different scheduling granularities are considered, as are different scheduling algorithms. The schemes are evaluated in the context of the LTE downlink using multiuser system simulations, assuming a full-buffer situation. The results show that separate transmission of the scheduling information requires a slightly lower overhead than joint broadcasting when proportional fair scheduling is employed and the users are spread out over the cell area. The results also indicate that the scheduling granularity standardized for LTE provides a good tradeoff between scheduling granularity and overhead. [ABSTRACT FROM PUBLISHER]

The opportunities and flexibility in relay networks and orthogonal frequency-division multiple access (OFDMA) make the combination a suitable candidate network and air-interface technology for providing reliable and ubiquitous high-data-rate coverage in next-generation cellular networks. Advanced and intelligent radio resource management (RRM) schemes are known to be crucial toward harnessing these opportunities in future OFDMA-based relay-enhanced cellular networks. However, it is not very clear how to address the new RRM challenges (such as enabling distributed algorithms, intra-cell/inter-cell routing, intense and dynamic co-channel interference (CCI), and feedback overhead) in such complex environments comprising a plethora of relay stations (RSs) of different functionalities and characteristics. Employment of conventional RRM schemes in such networks will highly be inefficient if not infeasible. The next-generation networks are required to meet the expectations of all wireless users, irrespective of their locations. High-data-rate connectivity, mobility, and reliability, among other features, are examples of these expectations. Therefore, fairness is a critical performance aspect that has to be taken into account in the design of prospective RRM schemes. This paper reviews some of the prominent challenges involved in migrating from the conventional cellular architecture to the relay-based type and discusses how intelligent RRM schemes can exploit the opportunities in relay-enhanced OFDMA-based cellular networks. We identify the role of multiantenna systems and explore the current approaches in literature to extend the conventional schedulers to next-generation relay networks. This paper also highlights the fairness aspect in such networks in the light of the recent literature, provides some example fairness metrics, and compares the performances of some representative algorithms. [ABSTRACT FROM AUTHOR]

The IEEE 802.16j standard has been developed to provide performance enhancement to the existing IEEE 802.16e network by incorporating the multihop relay (MR) technology. However, frequent handoffs and low spectrum-utilization issues that were not encountered in IEEE 802.16e may be incurred in IEEE 802.16j. The relay station (RS) grouping is one optional mechanism in the IEEE 802.16j MR standard to overcome these problems. The concept of RS grouping is to group neighboring RSs together to form an RS group, which can be regarded as a logical RS with larger coverage. In this paper, we investigate RS grouping performance enhancement in terms of throughput and handoff frequency. This paper designs an RS grouping algorithm to minimize handoffs by utilizing a greedy grouping policy: RS pairs with higher handoff rates will have higher priority for selection. The simulation results show that the handoff frequency of the considered MR network can significantly be reduced, and suitable RS grouping patterns can be derived using our grouping algorithm. In addition, we propose two centralized scheduling policies, i.e., the throughput-first (TF) policy to maximize the system throughput and the delay-first (DF) policy to minimize the average packet delay. By integrating our RS grouping algorithm and centralized scheduling algorithms, the simulation results indicate that, for the case of fixed users, groupings with smaller group sizes can result in better throughput performance. However, when user mobility is considered, the throughput value increases as the group size increases. Furthermore, we also show that the DF policy can both minimize the average packet delay and provide the fairness property among users with different traffic loads. [ABSTRACT FROM AUTHOR]

We study power-allocation problems in wireless systems through a network utility maximization framework. In this framework, the type of utility function represents the characteristics of each service. Hence, to deal with multiclass services in the system, it is important to accommodate various types of utility functions. In this paper, we consider four types of utility functions that can represent most of the services in wireless networks. We first develop a simple algorithm that solves a general optimization problem with those four types of utility function. We show that, even though the proposed algorithm might not provide the optimal solution, it provides an asymptotically optimal solution, which could be a good approximation to the optimal solution. The proposed algorithm can be applied to various resource-allocation problems in wireless systems. Among them, in this paper, we show that the proposed algorithm can be applied to both uplink and downlink power-allocation problems. [ABSTRACT FROM AUTHOR]

Contour line estimation in a monitored physical phenomenon using wireless sensor networks (WSNs) with cross-layer considerations is investigated in this paper. Herein, we present a statistical approach to locate contour points for contour line construction in the presence of irregular sensor deployment with the assistant of Delaunay triangular meshes. The proposed contour-estimation algorithm has certain error-correction capability, and it is robust to the data degradation coming from sensing and/or communication noise. To ensure the success of the proposed algorithm, we further analyze three sources of signal distortion: sensing noise, data quantization error, and data communication noise. We find that choosing a proper data quantization level can balance the communication cost and the desired signal quality. Meanwhile, the impact of channel impairment can be mitigated by the appropriate data-fusion mechanism. In this paper, an adaptive data-fusion mechanism is proposed to avoid excessive packet retransmissions. The correctness of the proposed approach is verified through simulation, and the effects of different system parameters on the overall system performance are also given to show the robustness of the proposed algorithm. This paper also offers some guidelines on the design of the WSN system. [ABSTRACT FROM AUTHOR]

Maximum-likelihood (ML) detection for higher order multiple-input-multiple-output (MIMO) systems faces a major challenge in computational complexity. This limits the practicality of these systems from an implementation point of view, particularly for mobile battery-operated devices. In this paper, we propose a modified approach for MIMO detection, which takes advantage of the quadratic-amplitude modulation (QAM) constellation structure to accelerate the detection procedure. This approach achieves low-power operation by extending the minimum number of paths and reducing the number of required computations for each path extension, which results in an order-of-magnitude reduction in computations in comparison with existing algorithms. This paper also describes the very-large-scale integration (VLSI) design of the low-power path metric computation unit. The approach is applied to a 4 x 4, 64-QAM MIMO detector system. Results show negligible performance degradation compared with conventional algorithms while reducing the complexity by more than 50%. [ABSTRACT FROM AUTHOR]

Orthogonal frequency-division multiplexing (OFDM) can be used to support high-data-rate transmissions over time-dispersive fading channels. Many OFDM-based communication systems use packet-based transmission, where channel estimation is needed for the detection of information-carrying symbols. The finite impulse response (FIR) channel model is simple and effective for some simulations of channel estimation for the OFDM-based communication systems over the time-dispersive channels; yet, it is only an approximate channel model that cannot be used in the case of accurate channel estimation. Unfortunately, many researchers have overlooked this issue and have been devising channel-estimation algorithms squarely based on the FIR channel model. While the channel estimation results from these algorithms can be impressive for the FIR channels, the algorithms can hardly be applied in real-world applications. This paper explains in detail the reason the FIR channel model is only an approximate channel model for the OFDM-based communication systems, trying to discourage the inappropriate usage of this model, which can lead to fruitless efforts. This paper also presents a realistic channel model for OFDM-based communication systems, which can be used to realistically access the channel parameter-estimation algorithms. [ABSTRACT FROM AUTHOR]

This paper introduces a novel analytical model for analyzing the performance of handoff algorithms based on absolute and relative signal strength measurements. The performance is analyzed in multicell and multisector environments where cochannel interference (CCI) is present. The model presented in this paper accounts for the distinct features of intersector handoff compared with intercell handoff. Numerical results show that the performance metrics are affected by the CCI level. The occurrence condition of unnecessary handoffs in multisector systems is also presented. [ABSTRACT FROM AUTHOR]

This paper considers a scheduling problem for multi-user transmissions over the downlink of a time-slotted cellular data network. For such a network, opportunistic scheduling exploits the time-varying radio channel and improves network performance. This paper presents a new scheduling solution that maximizes the aggregate user performance subject to certain minimum and maximum performance constraints. By constraining the performance experienced by individual users, who share a common radio downlink, to some upper bounds, it is possible to provide the system operator with a better control of radio resource allocations and service differentiation among different classes of users. The proposed solution, which is referred to as Throughput Constrained Opportunistic Scheduling (TCOS), offers better service differentiation among different classes of users than the existing opportunistic scheduling algorithms with only minimum performance constraints. For ideal memoryless fading channels, TCOS provides performance comparable with an existing scheme with minimum and maximum performance constraints. For realistic fading channels with memory, TCOS significantly improves system performance due to its ability to trade off feasibility with throughput. Extensive simulation results demonstrate the improved system performance and effective service differentiation of the proposed solution under realistic channel conditions. [ABSTRACT FROM AUTHOR]

This paper presents an analysis framework for estimating spatio-temporal distortion associated with data-gathering algorithms in sensor networks. We assume that the underlying data field being sensed is spatially and temporally correlated and that the sink node performs real-time reconstruction of the field. Unlike existing work, the proposed analysis framework assumes realistic transmission schemes and network/routing parameters, such as congestion and limited transmission range. Our simulations show that, even for a simple collision-free transmission scheme and regular deployment patterns, the distortion analyses yield starkly different results, compared with the analyses performed in the absence of these assumptions. The analytical method presented in this paper could easily be extended to consider the real-time data-reconstruction problem under different transmission schemes, node distributions, and reconstruction methods. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a novel approach for computing the number, location, and transmission powers of wireless base stations in a 2-D urban setup. The new approach utilizes 2-D convolution to extract the supply-demand correlation. Available efficient methods for computing the convolution are then used to substantially reduce the complexity of the solution. The proposed approach enables network designers to choose arbitrary antenna propagation and radio demand patterns using a simple color-coding mechanism. Simulations of the proposed algorithm show its efficiency and flexibility in solving the placement problem. In this paper, we consider only the coverage planning. Consequently, the technique in this paper is useful in networks that operate with time-division multiple-access technology. However, the work can be extended to consider simultaneous coverage and frequency planning. [ABSTRACT FROM AUTHOR]

This paper proposes a blind equalizer that pursues the maximization of a novel objective function. It consists of the ratio between the square of the mean signal power and the variance of the signal power. In this paper, important prepositions are first mathematically stated. The devised equalizer is asymptotically equivalent to the well-known constant-modulus algorithm (CMA) and the Kurtosis maximization algorithm (KMA) because they pursue the same "Ricianity" criterion already employed in the "Rayleigh-ness" test for spread-spectrum code acquisition. The performance of the addressed equalizers is then investigated by focusing on direct-sequence code-division multiple~access (DS/CDMA) communication environments in a downlink scenario. In particular, we have evidenced the effectiveness of the presented equalizer in the numerical examples in terms of robustness against the effect of interference, as well as in~terms of convergence rate, in spite of a small amount of extra processing. [ABSTRACT FROM AUTHOR]

This paper tackles a power minimization problem of interleave-division multiple-access (IDMA) systems over a fading multiple-access channel. The problem is minimizing the total power received by the receiver while keeping the bit error rates (BERs) of all users below a predefined value. The original formulation of the problem has highly nonlinear and implicitly defined functions, which render most existing optimization methods incapable. A new formulation is proposed in this paper, whose solution can effectively be obtained by a branch-and-bound (B&B) technique. An algorithm is devised based on B&B, and its effectiveness is also demonstrated by numerical experiments of systems with a moderate numbers of users. [ABSTRACT FROM AUTHOR]

This paper introduces a space-time decision feedback equalizer whose coefficients are recursively renewed on the basis of the modified affine projection algorithm (APA). Despite its effectiveness against a rank-deficiency problem, the complexity of the conventional APA utilizing the sample matrix inversion is considerable. Furthermore, the shift invariance property could not be exploited in the case of a space-time decision-directed equalizer (STDE) application. To overcome such challenges, this paper introduces an APA employing a hyperplane projection scheme to reduce computational complexity without any degradation in its convergence characteristic and tracking capability. The performance of the proposed equalization methodology is verified by showing its superior bit error rate behaviors, fast convergence property, and reduced computational complexity by performing adaptive STDE under the single-input-multiple-output wireless multipath fading channel. [ABSTRACT FROM AUTHOR]

In this paper, we consider a time-division code- division multiple-access (CDMA) system operating in downlink mode in a multiuser multipath channel scenario. In order to implement RAKE reception, the delays, phases, and magnitudes of the different paths need to be estimated and the estimates updated. In the context of burst transmissions, delays do not vary during a burst, and only phases and magnitudes need to be tracked. In this paper, we investigate the issue of phase tracking over rapidly time-varying multipath channels. We propose a new version of the conventional phase loop that mitigates the interpath interference effect. The optimization is based on the concept of prefiltering. The analysis shows improved tracking performance in comparison with the standard phase recovery algorithm. [ABSTRACT FROM AUTHOR]

We consider a wireless ad hoc network where each node employs a single-beam directional antenna and is provisioned with limited energy. We are interested in an online routing algorithm for successive multicast communication requests with the aim of maximizing the network lifetime. The beam-forming property, which is associated with single-beam directional antennas, introduces some unique problems that do not exist for omnidirectional antennas and, therefore, significantly increases the design space for routing algorithms. The contributions of this paper are twofold. First, we provide some important theoretical understanding on various multicast problems and deduce that even an offline version of this problem is NP-hard. Second, we develop a highly competitive online routing algorithm that takes the network lifetime consideration directly into iterative calculations and show that an algorithm that is designed under this methodology provides consistently better performance than the current state-of-the-art algorithm that only considers remaining energy. The theoretical results and routing algorithm in this paper offer some important insights on algorithm design for energy-constrained wireless ad hoc networks with directional antennas. [ABSTRACT FROM AUTHOR]

In wireless location, nonline-of-sight (NLOS) errors are a major error source. To improve positional performance, these errors should be identified and mitigated before measurements are used in position computations. A novel NLOS mitigation algorithm is proposed in this paper. Employing system redundancy, the algorithm derives from the distribution function of hyperbolic intersections, which is an intermediate mobile location. Cost functions based on the intermediate position are then created for each time-of-arrival measurement. NLOS errors are detected and mitigated via hypothesis tests performed on the cost functions. Simulation tests are presented in this paper, and the results verify the effectiveness of this NLOS-error-mitigation method. This paper also demonstrates that algorithm performance depends closely on receiver noise. Reducing receiver noise or providing the intermediate mobile location via external aiding can improve performance. [ABSTRACT FROM AUTHOR]

Wireless systems have evolved into supporting non- real-time data services. However, as the data rates for the services increase, the number of base stations per service area needs to expand, which leads to a high degree of base-station density. On the other hand, the so-called best effort resource management has been extensively studied for nonreal-time data services. One example of such efforts can be found in packet scheduling. The purpose of this paper is to investigate the economic impact of the down-link scheduling in terms of the base-station density. To this end, equations that can calculate the base-station density for the given quality of service (QoS) requirements such as outage probabilities, average data rates, and target Eb /Io were derived. Under specific QoS requirements on Rayleigh-fading channel environments, it is found that the one-by-one downlink scheduling (round-robin) requires about 50%-60% of the base stations required by the conventional simultaneous transmission. It was also found that this impact is almost the same as simply doubling the spectrum bandwidth for the simultaneous transmission. The base-station density is directly related to the infrastructure cost and thus may be translated into service prices. Therefore, the analysis in this paper provides a new insight into an economic aspect; how much the service prices for downloading the nonreal-time data would decrease with the introduction of packet scheduling in the code division multiple access downlink. [ABSTRACT FROM AUTHOR]

In this paper, the authors study the performance of scheduling algorithms exploiting the multiuser selection diversity. Schedulers with affordable-rate transmission and adaptive transmission based on the absolute signal-to-noise ratio (SNR) and the normalized SNR are considered. In contrast to previous studies on the multiuser-diversity systems, the channel dynamics is taken into consideration in this paper by a novel formulation based on the level crossing analysis of stochastic processes. Then, the authors make the connection between the Doppler frequency shift, which indicates the channel temporal correlation, and the average (channel) access time, the average waiting time (AWT) between accesses, and the average access rate (AAR) of active users. These properties are important for the scheduler design, especially for applications where delay is a concern. In addition, analytical expressions for the system throughput and the degree of fairness (DOF) when users have nonidentical average channel conditions are presented. These expressions quantify the effect of disparateness in users' average channel conditions on the system performance. [ABSTRACT FROM AUTHOR]

Reverse link capacity of a direct-sequence code-division multiple-access (DS-CDMA) system in a multicell environment has been studied recently, and significant capacity improvements due to the use of beamforming have been observed. However, system performance with beamforming will be affected by several impairments, such as direction of arrival estimation errors, array perturbations, mutual coupling, and signal spatial spreads. In this paper, reverse link performance of CDMA systems with beamforming under these impairments (imperfect beamforming) is investigated. A simplified beamforming model is developed to evaluate the system performance in terms of user capacity, bit-error rates (BER), and outage probabilities. Both signal-to-interference-ratio-based power control and strength-based power control are considered in this paper. The capacity and BER degradations due to different impairments are shown, and outage probabilities under different power control schemes are examined. [ABSTRACT FROM AUTHOR]

This paper investigates the features of a cellular geometry in code-division multiple-access (CDMA) systems with soft handoff and distinguishes controlling area of a cell from coverage area of a cell. Some important characteristics of the cellular configuration in soft handoff systems are used to propose a new design of efficient call admission control (CAC) in CDMA systems. Then, the paper constructs a continuous-time Markov chain (CTMC) model for CAC in CDMA with a soft handoff queue, obtains closed-form solutions, and thus develops loss formulas as performance indices such as the new blocking probability and the handoff dropping probability. In order to determine handoff traffic arrival rate, a fixed-point strategy is developed. Algorithms are also provided to stably compute loss probabilities and to determine the optimal number of guard channels. A new soft handoff scheme—eliminating pseudo handoff calls (EPHC)—is proposed to improve channel utilization efficiency based on mobility information. As an application of the loss formulas, the proposed modeling techniques are used to evaluate and compare the performance of conventional and proposed EPHC soft handoff schemes. Numerical results show the effectiveness of the proposed Markov chain models and the benefits of the new soft handoff scheme. [ABSTRACT FROM AUTHOR]

Tactical communications networks are multihop wireless networks in which switches and endpoints are mobile nodes. In a tactical environment, system performance degrades when switching nodes and/or communication links fail to operate. Fast algorithms for performance analysis are desirable for optimizing the network in a timely fashion. Further, tactical networks commonly use preemptive priorities to achieve low blocking probabilities for high-priority calls when the loss of equipment in the battlefield is not trivial. This paper discusses three measures and analytical algorithms for the performability evaluation of a two-tier tactical communications network where preemptive priority service discipline is employed and traffic is divided into multiple classes to provide multiple grades of service. Each class of traffic has its distinct characteristics, such as average call-arrival rate, average call-holding time, and service priority. The three performability measures are devised to evaluate the impact of nodes/links failures on system performance. Experiments show that the preemption does provide robust service for higher priority traffic. The techniques for performability evaluation presented in this paper may also be useful in other rapidly deployable networks, where mobility, communication efficiency, and computational complexity for adapting the network to unpredictable environments are of significant concern. [ABSTRACT FROM AUTHOR]

The major issue in the wireless multimedia system design is the selection of a suitable channel sharing media access control (MAC) protocol. The design challenge is to identify a wireless "multimedia capable" MAC protocol that provides a sufficient degree of transparency for many different kinds of services. This protocol should guarantee different quality of service (QoS) parameters for different types of traffic while in the same time achieving high throughput. In this paper a MAC protocol to serve different kinds of traffic, namely voice, data, and, real time variable bit rate (rt-VBR) video is proposed. The transmission time scale is divided into frames. Each frame is subdivided into N time slots. In this protocol, a fixed number of slots M out of 150 time slots are reserved at the beginning of every frame to transmit some of the video packets arriving during the frame interval. The rest of the video packets contend with the voice and data packets for the remaining time slots of this frame as in normal packet reservation multiple access (PRMA). One objective of this paper is to find the optimum value of M allowing the maximum number of voice and data users to share the HF channel with one video user. Another objective is to find the optimum permission probabilities of sending contending voice, data, and video packets allowing the maximum number of users sharing the RF channel. The dropping probability requirement for video is examined. [ABSTRACT FROM AUTHOR]

In this paper, we study the power allocation problem in a multiuser cooperative network, where users help each other's transmissions to an access point. We use iterative double auction (IDA) game to model the interaction among the users and the access point. In each iteration of this game, the users first submit bids for buying other users' power and asks for selling its own power, and then, the access point determines the power allocation based on users' bids and asks. We propose a distributed algorithm for the implementation of the IDA-based power allocation. We also show that the proposed algorithm achieves a weighted sum signal-to-noise ratio (sum-SNR)-optimal solution. Simulation results are conducted to verify the performance of the proposed algorithm. [ABSTRACT FROM PUBLISHER]

In-band spectrum sensing (SS) requires that secondary users (SUs) periodically interrupt their communication to detect the emergence of the primary users (PUs) in the channel. A new approach referred to as spectrum monitoring (SM) was proposed by Boyd et al., which allows the SU to employ its receiver statistics to detect the emergence of the PU during its own communication periods. In this paper, we construct a decision statistic for SM based on the SU's receiver error count. We then evaluate the detection probability of SM in the presence of interference from the PU signal. Next, we derive closed-form formulas for channel utilization and detection delay using two Markov chain models. Upper and lower bounds on channel utilization and detection delay are derived, and an optimization problem is formulated and solved to maximize channel utilization with a constraint on detection delay. Numerical results from analysis are compared with simulation results obtained for a BCH code and a convolutional code, which show the accuracy of the analysis and the significant improvement of a hybrid SM/SS over SS alone. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a cellular/infostation integrated network that supports on-demand data service delivery over a wireless link to users in a high-speed train. For the requests with different lifetimes and prices that they are willing to pay, we develop the optimal packet schedule that aims at earning the maximum revenue. To this end, we formulate the problem as an integer linear program (ILP). The problem cannot be solved efficiently by existing ILP solvers with guaranteed polynomial-time complexity in the worst case. By exploring the special structure of the formulated ILP, we propose a novel Checker algorithm and prove that this algorithm is guaranteed to find the offline optimal schedule in polynomial time. Based on the relevant insights, we further develop a class of online Checker algorithms that require only causal knowledge of service demands and wireless channel capacities. It is established that these online algorithms have a worst-case competitive ratio of 1/2, i.e., total revenue earned by them is at least half as much as the revenue earned by an offline optimal schedule that knows the complete a priori knowledge of future requests and channel conditions. Simulation results are provided to demonstrate the merit of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

It is known that in addition to spectrum sparsity, spatial sparsity can also be used to further enhance spectral utilization in cognitive radio systems. To achieve that, secondary users (SUs) must know the locations and signal strength distributions (SSDs) of primary users' base stations (PUBSs). Recently, a group sparse total least squares method was developed to cooperatively sense the PUBSs' signal strength and estimate their locations. It approximates PUBSs' power decay with a path loss model (PLM), assumes PUBSs' locations on some grid points, and then accomplishes the estimation tasks. However, the parameters of the PLM have to be known in advance, and the accuracy of the location estimation is bounded by the resolution of the grid points, which limit its practical applications. In this paper, we propose a sparse Bayesian learning method to solve the problems. We use a Laplacian function to model the power decay of a PUBS and then derive learning rules to estimate corresponding parameters. The distinct features of the proposed method are that most parameters are adaptively estimated, and little prior information is needed. To further enhance the performance, we incorporate source number detection methods in the proposed algorithm such that the number of the PUBSs can be precisely detected, facilitating the estimation of PUBSs' locations and SSDs. Moreover, the proposed algorithm is modified into a recursive mode to adapt to SUs' mobility and time-variant observations. Simulations show that the proposed algorithm has good performance, even when the spatial measurement rate is low. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the problem of power control for sum-rate maximization on multiple interfering links [transmitter–receiver pairs (Tx–RX)] under a sum power constraint. We consider a single-frequency network, where all pairs are operating in the same frequency band, thereby creating interference with each other. We study the power-allocation problem for sum-rate maximization with and without quality-of-service (QoS) requirements on individual links. When the objective is only sum-rate maximization without QoS guarantees, we develop an analytic solution to decide optimal power allocation for a two-TX–RX-pair problem. We also develop a low-complexity iterative algorithm for a three-TX–RX-pair problem. For a generic N>\3 TX–RX pair problem, we develop two low-complexity suboptimal power-allocation algorithms. The first algorithm is based on the idea of making clusters of two or three TX–RX pairs and then leveraging the power-allocation results obtained for the two- and three-TX–RX-pair problems. The second algorithm is developed by using a high signal-to-interference-plus-noise ratio (SINR) approximation, and this algorithm can be also implemented in a distributed manner by individual TXs. We then consider the same problem but with additional QoS guarantees for individual links. We again develop an analytic solution for the two-TX–RX-pair problem and a distributed algorithm for N>\2 TX–RX pairs. [ABSTRACT FROM PUBLISHER]

Due to signal fading and user mobility in wireless networks, quality-of-service provisioning for wireless services has become more challenging. As a promising technique, cooperative communications make use of the broadcasting nature of the wireless medium to facilitate data transmission and, thereby, reduce energy consumption. However, in many studies on wireless cooperative diversity, it is often assumed that the number of relays or the relay distribution intensity is known a priori. In this paper, we relax this assumption and propose an algorithm to estimate the relay intensity for a backoff-based cooperative scheme, where the relays are distributed as a homogeneous Poisson point process. It is proved that the algorithm can converge to an optimal solution with the minimum estimation error. Based on the estimated relay intensity, we further investigate a distributed energy saving strategy, which selectively turns off some relays to reduce energy consumption while maintaining the required transmission success probability. The performance of the proposed cooperative scheme is analytically evaluated with respect to the collision probability. The numerical and simulation results demonstrate the high accuracy and efficiency of the intensity estimation algorithm and validate the theoretical analysis. Moreover, the proposed cooperative scheme exhibits significant energy savings and satisfactory transmission performance, which offers a good match to accommodate green communications in wireless networks. [ABSTRACT FROM PUBLISHER]

Network coding achieves multicast network capacity by allowing intermediate nodes to mix information in packets. However, due to the mixing operation, network coding is vulnerable to pollution attacks. Different from conventional cryptographic solutions, watchdog-based solutions, which have been recently proposed for network coding, rely on trusted nodes to monitor and verify behaviors of transmission nodes. However, the impact of lossy wireless communications has not been considered. Since false alarm and misdetection depend on the loss rate, these false results can happen with high probability when packet loss happens. In this paper, we propose VANDER, which is a novel cooperative watchdog scheme in heterogeneous wireless networks, where multiple watchdogs collaborate and efficiently detect pollution attacks in a lossy wireless environment. The novelty of our approach is that, when lossy overhearing happens, watchdogs work cooperatively to share the packet information, where no extra overhead is introduced to normal transmission nodes, and rather than retransmitting all lost packets among watchdogs, watchdogs use randomly generated Vandermonde hashes to detect corrupted packets. Moreover, VANDER is capable of detecting successive colluded adversaries. In addition to the low false alarm and misdetection probabilities, VANDER also achieves low computational complexity and communication overhead. Numerical experiments are provided to support the theoretical analysis of VANDER. [ABSTRACT FROM PUBLISHER]

In the current architecture of dynamic spectrum access, secondary users (SUs) only opportunistically access the spectrum of primary users (PUs). The resurgence of PUs disrupts secondary communications, which can result in poor performance for SUs. In this paper, we propose a novel architecture for dynamic spectrum access, termed dynamic spectrum co-access (DSCA), to enable the PU and the SU to simultaneously access the licensed spectrum. With DSCA, SUs transparently incentivize PUs through increasing the PU performance so that SUs can access the spectrum simultaneously with PUs; hence, there is no disruption to secondary communications due to the resurgence of PUs. We derive a mathematical model to formulate the minimum incentives for the spectrum co-access between the PU and the SU and to compute the region of co-access to determine the SUs that can co-access with a given PU. An algorithm is also developed to select the co-access primary and secondary links to maximize network performance. Numerical results indicate that DSCA significantly improves performance compared with the current architecture of dynamic spectrum access. [ABSTRACT FROM PUBLISHER]

We consider the uplink transmission in multiuser wireless systems with multiple single-antenna transmitting users and a multiantenna receiver. We address two problems in this paper. The first problem is user admission, i.e., given a large number of users, how to admit the maximum number of users that can simultaneously satisfy quality of service (QoS) and power constraints. The second problem is how to distribute the data among the users when they are allowed to share data before transmission. The aim is to minimize the total data exchange cost. Such a problem is called user clustering. We formulate those problems into sparsity-maximization problems, which are NP-hard. Inspired by compressive sensing techniques, we propose a common framework to tackle those problems by first applying the \ell1 -norm relaxation and then solving them with convex optimization methods. Simulations show that the proposed algorithms achieve excellent performance. For user admission, the numbers of admitted users by the proposed algorithms are close to the optimum numbers of admitted users obtained by exhaustive search (ES) . For user clustering, the total data exchange cost is reduced by more than 10% after only a few iterations. When the QoS requirement is low, the user data exchange can be avoided using the proposed method, which achieves the optimum result obtained by ES. [ABSTRACT FROM PUBLISHER]

Cognitive radio (CR) is currently one of the most promising solutions for designing spectrum-efficient wireless communication systems. In this paper, we present a greedy cognitive access policy that handles spectrum sensing with the tools of image processing. By means of the Wigner–Ville transform (WVT), we are able to analyze the time and frequency features of the received interference, and represent them on a time–frequency grid as an image in which brightness reveals the spectrum occupancy. According to sensed interference, each secondary user autonomously tries to access the grid following a multiple-division principle, i.e., by properly shaping the signal in the code, time, and frequency domains. In detail, this is realized by processing the WVT to derive the shaping mask (and the matching algorithm) that allows the filling up of the “time spectrum holes.” Numerical simulations and a test-bed implementation show how the proposed scheme outperforms selected state-of-the-art approaches while still presenting an affordable computational cost. [ABSTRACT FROM AUTHOR]

Broadcasting is a key function in mobile ad hoc networks. Topology-dependent scheduling algorithms depend on the detailed network connectivity information and cannot adapt to dynamic topological changes in mobile networks. To overcome this limitation, topology-transparent broadcast scheduling algorithms have been proposed. Due to the large overhead of implementing the acknowledgement mechanism in broadcast communications and to guarantee that there is at least one collision-free transmission in each frame, most existing topology-transparent broadcast scheduling algorithms require a node to transmit the same packet repeatedly at multiple slots during one frame. This is very inefficient. In this paper, we propose an efficient topology-transparent broadcast scheduling algorithm. First, instead of transmitting the same packet repeatedly during one frame, each node collects transmission codes of its two-hop neighbors and transmits several different packets during one frame. Second, noting that many unassigned slots are not utilized, we propose several methods to utilize the unassigned slots efficiently in a collision-free and traffic-adaptive manner. Thus, our algorithm provides a guaranteed throughput and achieves a much better average throughput. The analytical and simulation results show that our proposed algorithm outperforms other existing topology-transparent broadcast algorithms dramatically. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the problem of distributed channel selection for interference mitigation in a canonical communication network. The channel is assumed time-varying, and the active user set is considered dynamically variable due to the specific service requirement. This problem is formulated as an exact potential game, and the optimality property of the solution to this problem is first analyzed. Then, we design a low-complexity fully distributed no-regret learning algorithm for channel adaptation in a dynamic environment, where each active player can independently and automatically update its action with no information exchange. The proposed algorithm is proven to converge to a set of correlated equilibria with a probability of 1. Finally, we conduct simulations to demonstrate that the proposed algorithm achieves near-optimal performance for interference mitigation in dynamic environments. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communications bring significant benefits to mobile multimedia services in local areas. However, these potential advantages hinge on intelligent resource sharing between potential D2D pairs and cellular users. In this paper, we study the problem of energy-efficient uplink resource sharing over mobile D2D multimedia communications underlaying cellular networks with multiple potential D2D pairs and cellular users. We first construct a novel analytical model of energy efficiency for different sharing modes, which takes into account quality-of-service (QoS) requirements and the spectrum utilization of each user. Then, we formulate the energy-efficient resource sharing problem as a nontransferable coalition formation game, with the characteristic function that accounts for the gains in terms of energy efficiency and the costs in terms of mutual interference. Moreover, we develop a distributed coalition formation algorithm based on the merge-and-split rule and the Pareto order. The distributed solution is characterized through novel stability notions and can be adapted to user mobility. From it, we obtain the energy-efficient sharing strategy on joint mode selection, uplink reusing allocation, and power management. Extensive simulation results are provided to demonstrate the effectiveness of our proposed game model and algorithm. [ABSTRACT FROM PUBLISHER]

One of the key challenges in wireless networking is allocating the available radio resources to maximize key service delivery parameters such as the aggregate throughput and the multimedia quality of experience (QoE). We propose a novel and effective scheduling policy that allocates resource blocks, such that interference power is shifted toward capacity-saturated users, while improving the throughput of unsaturated users. The highlight of this paper is that the proposed scheme can dramatically improve the performance of cells that have a high discrepancy in its signal-to-noise ratio (SNR) distribution, which is typical in urban areas. The results show that a free-lunch (FL) solution is possible, whereby for negligible performance degradation in the saturated users, a large improvement in the nonsaturated users can be obtained. However, on average, the number of FL user pairings is low. By relaxing the degradation constraints, the non-FL (NFL) solution can yield a greater multiuser throughput gain. Motivated by a surge in mobile multimedia traffic, we further demonstrate that the proposed scheduling may have a profound impact on both energy efficiency and QoE of multimedia service delivery. [ABSTRACT FROM PUBLISHER]