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This paper proposes a flexible pilot assignment method to jointly optimize the uplink and downlink data transmission in multi-cell Massive multiple input multiple output (MIMO) systems with correlated Rayleigh fading channels. By utilizing a closed-form expression of the ergodic spectral efficiency (SE) achieved with maximum ratio processing, we formulate an optimization problem for maximizing the minimum weighted sum of the uplink and downlink SEs subject to the transmit powers and pilot assignment sets. This combinatiorial optimization problem is solved by two sequential algorithms: a heuristic pilot assignment is first proposed to obtain a good pilot reuse set and the data power control is then implemented. Numerical results manifest that the proposed algorithm converges fast to a better minimum sum SE per user than the algorithms in previous works. [ABSTRACT FROM AUTHOR]

Multi-hop device-to-device (D2D) communications play an important role in expanding D2D coverage. In this paper, we study a relay-based and network-coding-assisted (in particular, XOR coding) multi-hop D2D communication system. In the system, toward jointly considering the impact of interference and network traffic conditions on the quality of D2D communications, various channel fading models and traffic models are investigated, and the packet loss probability of D2D links is meticulously computed using these models. With the packet loss probability of D2D links, the general closed-form expressions of end-to-end packet loss probability (E2EPLP) of the system with the presence (or absence) of XOR coding are subsequently derived. Our experiments reveal that both the number of relays and the mechanism of XOR coding can affect the system performance. Specifically, the increase in the number of relays will lower the overall system performance (e.g., an increase in the E2EPLP and end-to-end completion time, and a decrease of the end-to-end rate may follow as a result). On the other hand, although the presence of XOR coding unfortunately raises the system E2EPLP, it can effectively improve the end-to-end completion time and end-to-end rate. It is our belief that the analytical approach proposed in this paper and the results found in our work can be useful to peer studies in the context of applying network coding in multi-hop D2D networks. [ABSTRACT FROM AUTHOR]

The dynamic nature of vehicular networks imposes a lot of challenges in multihop data transmission as links are vulnerable in their existence due to associated mobility of vehicles. Thus, packets frequently find it difficult to get through to the destination due to the limited lifetimes of links. The conventional broadcasting based vehicular ad-hoc network (VANET) routing protocols struggle to accurately analyze the link dynamicity due to the unavailability of global information and inefficiencies in their route discovering schemes. However, with the recently emerged software defined vehicular network (SDVN) paradigm, link stability can be better scrutinized pertaining to the availability of global network information. Thus, in this paper, we introduce an optimization based novel packet routing scheme with a source routing based flow instantiation (FI) operation for SDVN. The routing framework closely analyzes the stability of links in selecting the routes and the problem is formulated as a minimum cost capacitated flow problem. Furthermore, an incremental packet allocation scheme is proposed to solve the routing problem in a less time complexity. The objective is to find multiple shortest paths which are collectively stable enough to deliver a given number of packets. The FI scheme efficiently delivers and caches flow information in the required nodes with a reduced extent of communication with the control plane. With the help of realistic simulation, we show that the proposed routing framework excels in terms of the performance over the existing routing schemes of both SDVN and conventional VANET. [ABSTRACT FROM AUTHOR]

Source location privacy is a major problem in wireless sensor networks (WSNs). WSNs are usually deployed in random areas with no protection. The source location reveals valuable information about targets. If an adversary locates the source node by analyzing the traffic mode, a target can be easily attacked. In this paper, a scheme based on the cloud using multi-sinks (CPSLP) is proposed to address the issue of source location privacy. The authors propose a scheme that changes packet destinations randomly in each transmission. In addition, multiple sinks are adopted to create many routing paths. The introduction of an intermediate node renders the routing path more random and flexible. Then, a cloud-shaped fake hotspot is created to add fake packets into the WSN to confuse the adversary and provide a comprehensive privacy location. Each valuable packet is routed through a path that is quite difficult for the hotspot-locating adversary to find directly. Simulation results illustrate that the CPSLP scheme can prevent adversarial capture and maintain a high level of privacy protection at the same time. The energy consumption in this scheme exerts limited influence on the network lifetime compared with a cloud-based scheme and an all-direction random routing algorithm scheme. [ABSTRACT FROM AUTHOR]

With the rapid emergence of applications in Mobile Opportunistic Networks (MONs), understanding and characterizing their properties becomes extremely important. A fundamental model for MONs is time-varying graph, which currently remains poorly understood since many well-recognized properties of static graphs have no obvious counterpart in dynamic ones. In MONs, the dynamical links change opportunistically and usually the system energy is very limited, which results in unique and unknown properties about the network connectivity and reachability. In this paper, taking the communication energy into account, we introduce the concept of Energy-aware Temporal Reachability Graphs (ETRG), which characterizes the connectivity of MONs with the consideration of communication consumed energy, and consequently reveals the communication capabilities of MONs with the given of real-world system parameters of data size, tolerable delay, and energy budget. We come up with efficient algorithm to calculate ETRG from the corresponding time-varying graphs. By applying ETRG to several mobile networks recorded by real-life human and vehicular mobility traces, we characterize their network connectivity properties in terms of average reachability, communication asymmetry, and stability. Moreover, utilizing ETRG that places upper bounds of the communications capabilities, we reveal the fundamental relations and tradeoffs among large-scale variability of the system metrics of energy budget, tolerable delay, and data size on the system performance. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the energy efficiency of downlink transmissions in heterogeneous networks. Our objective is to satisfy the rate requirement of users while maximizing the energy efficiency of the network. We employ the fractional frequency reuse (FFR) scheme to increase the energy efficiency of downlink transmissions and to eliminate outages for the cell-edge users. We formulate the joint cell-center boundary selection for FFR, scheduling, and power allocation problems. This formulation gives us a mixed discrete (selection of the cell-center boundary selection for FFR and scheduling) and continuous (power allocation) optimization problem which is hard to solve jointly. In order to solve this problem, we propose a three-stage resource allocation algorithm. In the first stage, we propose a dynamic method to determine the cell-center region boundaries. In the second stage, we employ the Lagrangian-directed scheduler algorithm to incorporate the rate requirements of users. The third stage solves the power allocation subproblem using the Levenberg–Marquardt method combined with dual decomposition. In order to make the base stations further reduce intercell interference, interference pricing mechanism is applied. This scheme penalizes the utility of a base station with the interference it creates. The performance of the proposed algorithm is simulated in a long-term evolution (LTE) network simulation tool. Our numerical results reveal that significant gains in terms of energy efficiency can be achieved with the proposed algorithm. The outage probability is also significantly reduced. [ABSTRACT FROM AUTHOR]

In intelligent vehicular communication networks, a hybrid communication architecture is used which combines both centralized and ad hoc transmission schemes. In order to maximize the end-to-end delivery ratio while reducing the network overhead, one important problem is to efficiently design the data forwarding algorithm to guarantee the quality of data transmission. In this paper, by considering the traveling information and vehicular space-crossing community structure, two metrics, “space–time approachability” and “social approachability,” are defined to provide the absolute and relative geographical information of the forthcoming contacts, respectively. Then, a novel data-forwarding algorithm, called approachability-based algorithm, is proposed, which utilizes two metrics together for better routing quality. We evaluate the proposed approachability-based algorithm utilizing San Francisco Cabspotting and Shanghai Taxi Movement datasets. Simulation results show that the approachability-based data forwarding algorithm can achieve better performance than the popular data forwarding algorithms ZOOM and BUBBLE RAP in all the interested scenarios. [ABSTRACT FROM PUBLISHER]

In this paper, we model a vehicular multihop network as an evolving graph and formulate the problem of optimal data dissemination over the network in terms of minimum number of transmissions. We show that the problem belongs to the NP complexity class and provide an easy to implement polynomial-time \2 \tau H(\Delta)-approximation algorithm, where \tau is the number of different subgraphs that comprise the evolving graph, and H(\Delta) is the harmonic number of the degree of the evolving graph. By means of applying our heuristic over a vehicular scenario generated by a microscopic road-traffic simulator, we provide some insight into the data dissemination issue. In addition, the proposed algorithm is employed to benchmark a state-of-the-art communication protocol. We hope this paper will inspire more efficient heuristics and data dissemination solutions. [ABSTRACT FROM PUBLISHER]

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]

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]

In this paper, we consider the coordinated multipoint (CoMP) transmission design for the downlink cloud radio access network (Cloud-RAN). Our design aims to optimize the set of remote radio heads (RRHs) serving each user and the precoding and transmission power to minimize the total transmission power while maintaining the fronthaul capacity and users' quality-of-service (QoS) constraints. The fronthaul capacity constraint involves a nonconvex and discontinuous function that renders the optimal exhaustive search method unaffordable for large networks. To address this challenge, we propose two low-complexity algorithms. The first pricing-based algorithm solves the underlying problem through iteratively tackling a related pricing problem while appropriately updating the pricing parameter. In the second iterative linear-relaxed algorithm, we directly address the fronthaul constraint function by iteratively approximating it with a suitable linear form using a conjugate function and solving the corresponding convex problem. For performance evaluation, we also compare our proposed algorithms with two existing algorithms in the literature. Finally, extensive numerical results are presented, which illustrate the convergence of our proposed algorithms and confirm that our algorithms significantly outperform the state-of-the-art existing algorithms. [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]

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]

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 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]

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]

As receiver performance will be degraded by carrier frequency offset (CFO), Doppler shift, and low signal-to-noise ratio (SNR), a novel estimator that jointly considers CFO, Doppler shift, and SNR is proposed in this paper. The proposed algorithm uses the Fourier transform (FT) to calculate the power spectral density of time-varying channels through channel estimates. Then, a new periodogram technique is utilized to estimate CFO, Doppler shift, and SNR together. Unlike conventional methods in sinusoid estimation, which rely on the peak-value search of a periodogram, this paper exploits the hypothesis test to address the random frequency modulation of time-varying channels. Furthermore, to optimize estimation performance, a theoretical analysis is also provided on the influences of some key parameters, e.g., the length of the signal processed with fast FT, the amplitude threshold value, the SNR dynamic range, and the velocity dynamic range. Correspondingly, the appropriate key parameters are chosen according to this analysis and are validated by simulations. The results are consistent with our analysis and present high accuracy over a wide range of velocities and SNRS. [ABSTRACT FROM AUTHOR]

The IEEE 802.16 Standard defines the mesh mode for media access control for external and internal packet transmission. In the IEEE 802.16 mesh mode, the allocation of minislots is handled by centralized scheduling and distributed scheduling, which are independently exercised. This paper proposes the Combined Distributed and Centralized (CDC) and Combined Distributed and Centralized with Queue capability (CDCQ) schemes to combine distributed scheduling and centralized scheduling so that the minislot allocation can be more flexible and the utilization is increased. Two scheduling algorithms, i.e., the Round-Robin (RR) and Greedy algorithms, are used as the baseline algorithms for centralized scheduling. This paper pro- poses an analytical model and conducts simulation experiments to investigate the performance of the CDC-series schemes with the RR and Greedy algorithms in terms of the acceptance rate of both external and internal packet data. Our study indicates that the CDC-series schemes outperform the scheme proposed in the IEEE standard. [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]

Orthogonal frequency division multiplexing (OFDM) suffers from a high peak-to-average power ratio (PAR). Tone reservation is a popular PAR reduction technique that uses a set of reserved tones to design a peak-canceling signal. In a previous paper by Krongold and Jones, an active-set approach was developed to efficiently compute the peak-canceling signal. In this paper, we consider the use of clipping noise, which is generated when the OFDM signal is clipped at a predefined threshold, to design the peak-canceling signal. To this end, the clipping noise is analyzed as a series of parabolic pulses under tone-reservation constraints. The single-pulse case and the multiple-pulse case are treated. The analysis explains peak regrowth and the constancy of the clipping noise power spectrum over the whole OFDM band. Moreover, the clipping noise at the end of several clipping and filtering iterations is shown to be approximately proportional to that generated in the first iteration. The constant of proportionality is estimated via the level-crossing theory for high clipping thresholds. Using this analysis, a constant-scaling algorithm and an adaptive-scaling algorithm are proposed for tone reservation. These algorithms scale the filtered first-iteration clipping noise to compensate for peaks that are above the threshold. The simulation results show that the proposed algorithms achieve a larger peak reduction and lower complexity than the active-set algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a method of determining electromotive force and battery internal resistance as time functions, which are depicted as functions of state of charge (SOC) because Soc = f(t). The model is based on battery discharge and charge characteristics under different constant currents that are tested by a laboratory experiment. This paper further presents the method of determining the battery soc according to a battery modeling result. The influence of temperature on battery performance is analyzed according to laboratory-tested data, and the theoretical background for calculating the SOC is obtained. The algorithm of battery SOC indication is depicted in detail. The algorithm of the battery SOC "online" indication considering the influence of temperature can be easily used in practice by a microprocessor. An NiMH battery is used in this paper to depict the modeling method. In fact, the method can also be used for different types of contemporary batteries, as well as Li-ion batteries, if the required test data are available. [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]

The focus of this paper is to analyze the throughput performance of TCP Thhoe and Reno on a differentiated services network with correlated wireless losses. An analytical model of TCP on a wireless link with differentiated services (DiffServ) based on the packet train model is developed. The network model is based on the state dependent arrival process. A major contribution of this paper is an analytical model combining the performance of TCP throughput and DiffServ leading to a model that represents an almost complete network scenario. It is shown that DiflServ in a wireless channel with correlated error losses is possible if the prob' ability of the channel changing from a good state to a bad state is less than a particular value. It is also shown that TCP Reno has a higher sensitivity to DiffServ than Tahoe. Our analytical model is validated through a number of simulations. [ABSTRACT FROM AUTHOR]

This paper proposes two new data detection algorithms for decode-and-forward alternate-relaying cooperative communication systems. These algorithms are discussed in the context of bit-interleaved coded modulation transmission with a multiple-antenna destination. The interference signal, resulting from the concurrent transmission of the source and one of the relays, is exploited as a beneficial resource to develop an optimal data detection algorithm. We show that the optimal algorithm can be implemented by parallel demappers, each based on a family of Bahl, Cocke, Jelinek, and Raviv algorithms, connected to parallel decoders in an iterative way. Due to the need to buffer the entire frame before decoding, the optimal algorithm suffers from long processing time. A suboptimal algorithm is also proposed to avoid this problem, where each packet is decoded by using two consecutive received packets. The suboptimal algorithm reduces processing time, complexity, bandwidth loss, and memory size with a slight increase in the bit error rate (BER). The BER performance of the proposed algorithms is evaluated via Monte Carlo simulations, and the results indicate their effectiveness in improving the BER performance. [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]

Existing full-rate transmission schemes for two-path relay networks typically cannot achieve full diversity while demanding high decoding complexity. In this paper, we present a novel low-complexity full-rate transmission scheme for two-path relay networks to harvest maximum achievable diversity. The proposed scheme adopts block transmission with small block size of four symbols, which greatly reduces the decoding complexity at the receiver. Through the performance analysis of the resulting two-path relay network in terms of the symbol error rate (SER) and diversity order, we show the proposed scheme can achieve full diversity order of four and mimic a 2 $\times$ 2 multiple-input multiple-output system. Simulations results are provided to validate the mathematical formulation. [ABSTRACT FROM PUBLISHER]

In this paper, we dynamically select the transmission rate and design wireless network coding to improve the quality of services, such as delay for time-critical applications. In a network coded system, with a low transmission rate and, hence, a longer transmission range, more packets may be encoded, which increases the coding opportunity. However, a low transmission rate may incur extra transmission delay, which is intolerable for time-critical applications. We design a novel joint rate selection and wireless network coding (RSNC) scheme with a delay constraint to maximize the total benefit (where we can define the benefit based on the priority or importance of a packet for example) of the packets that are successfully received at the destinations without missing their deadlines. We prove that the proposed problem is NP-hard and propose a novel graph model to mathematically formulate the problem. For the general case, we propose a transmission metric and design an efficient algorithm to determine the transmission rate and coding strategy for each transmission. For a special case when all delay constraints are the same, we study pairwise coding and present a polynomial-time pairwise coding algorithm that achieves an approximation ratio of \1 -(\1/e) to the optimal pairwise coding solution, where $e$ is the base of the natural logarithm. Finally, simulation results demonstrate the superiority of the proposed RSNC scheme. [ABSTRACT FROM PUBLISHER]

This paper considers the problems of minimizing the completion time and reducing decoding complexity for relay-aided wireless broadcast. Both network coding and scheduling problems are considered. A deterministic network coding algorithm is designed to select innovative encoding vectors, which is applicable to both the base station and the relay. The proposed algorithm can reduce decoding complexity significantly by selecting sparse encoding vectors. Integrating with the proposed network coding algorithm, a scheduling scheme based on dynamic programming is proposed, which is proved to be optimal in terms of minimizing expected completion time. Considering the size of state space and computational complexity of dynamic programming, a greedy scheduling algorithm is also proposed for practical implementation. Simulation shows that the proposed network coding algorithm and scheduling schemes work very well both in reducing completion time and in decoding complexity. [ABSTRACT FROM PUBLISHER]

In this paper, we study a transmit beamforming technique for multiple-input–multiple-output (MIMO) downlink multicast systems. Assuming that channel state information (CSI) is available at a transmitter, we try to maximize the lowest transmit data rate among users for a given transmit power level. Since finding the optimal beamforming vector requires prohibitively high computational complexity, we propose a reduced complexity scheme by applying greedy vector search and a simple power-allocation (PA) algorithm. Simulation results show that the proposed scheme outperforms the conventional semidefinite relaxation (SDR) technique and provides a performance quite close to the optimal performance with much reduced complexity. [ABSTRACT FROM PUBLISHER]

This paper investigates the resource-sharing problem in vehicular networks, including both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication links. A novel underlaying resource-sharing communication mode for vehicular networks is proposed, in which different V2V and V2I communication links are permitted to access the same resources for their individual data transmission. To solve the resource-sharing problem in vehicular networks, we, for the first time, apply graph theory and propose the following two interference graph-based resource-sharing schemes: 1) the interference-aware graph-based resource-sharing scheme and 2) the interference-classified graph-based resource-sharing scheme. Compared with the traditional orthogonal communication mode in vehicular networks, the proposed two resource-sharing schemes express better network sum rate. The utility of the proposed V2V and V2I underlaying communication mode and the two proposed interference graph-based resource-sharing schemes are verified by simulations. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate a low-density parity-check (LDPC)-coded orthogonal frequency-division multiplexing (OFDM) system with a peak-to-average power ratio (PAPR) reduction using the partial transmit sequence (PTS), which does not transmit PTS side information about the phase factors. We view the PTS processing as a stage of coding and call the resulted code of LDPC coding and PTS processing a concatenated LDPC-PTS code. Then, we derive the parity-check matrix of the concatenated LDPC-PTS code. With the parity-check matrix, the LDPC code and phase factors can be jointly decoded using belief propagation algorithms. Neither transmission of PTS side information (phase factors) nor phase factor estimation before decoding is required by the proposed scheme. Simulation results show that the proposed joint decoding provides nearly perfect phase factor recovery and LDPC decoding for a small number of PTS partitions. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the problem of real-time transmission scheduling over time-varying channels. We first formulate this transmission scheduling problem as a Markov decision process and systematically unravel the structural properties (e.g., concavity in the state-value function and monotonicity in the optimal scheduling policy) exhibited by the optimal solutions. We then propose an online learning algorithm that preserves these structural properties and achieves \varepsilon-optimal solutions for an arbitrarily small \varepsilon. The advantages of the proposed online method are given as follows: 1) It does not require a priori knowledge of the traffic arrival and channel statistics, and 2) it adaptively approximates the state-value functions using piecewise linear functions and has low storage and computation complexity. We also extend the proposed low-complexity online learning solution to enable prioritized data transmission. The simulation results demonstrate that the proposed method achieves significantly better utility (or delay)–energy tradeoffs compared to existing state-of-the-art online optimization methods. [ABSTRACT FROM PUBLISHER]

Accurate integer frequency offset (IFO) estimation is crucial for orthogonal frequency-division multiplexing (OFDM) systems, particularly in the presence of frequency-selective fading and residual timing offset (RTO). For existing algorithms, however, it is still a challenge to obtain a good tradeoff among the estimation performance, complexity, and spectrum overhead. In this paper, we propose a novel cross ambiguity function (CAF)-based IFO estimator using only one training sequence. By designing the training sequence, which has only a single sharp peak on its ambiguity function surface, a highly accurate and full acquisition range estimation of the IFO can be obtained in the presence of frequency-selective fading and RTO. Moreover, the adoption of the CAF expression in terms of time-domain signals ensures that the complexity of the proposed algorithm is relatively low. Simulation results verify its superior accuracy in frequency-selective fading channels and in the presence of RTO. [ABSTRACT FROM PUBLISHER]

In this paper, blind symbol synchronization for orthogonal frequency-division multiplexing (OFDM) systems based on the cyclic prefix (CP), considering time-variant long-echo fading channels, is introduced. The basic idea of our contribution is to obtain an estimate of channel-tap powers using the correlation characteristics of the CP. The maximum-likelihood (ML) estimation of the correlation characteristics is derived and employed for channel-tap power estimation. An intersymbol-interference (ISI) metric is minimized using the estimate of channel-tap powers. The metric, which is based on the statistical properties of received samples, turns the mobility factor into a coefficient, which can be simply compensated. The metric is suitable for both short- and long-echo channels. The performance is analyzed. The proposed algorithm has moderate complexity. Simulations confirm the advantages of the proposed estimator. [ABSTRACT FROM PUBLISHER]

This paper proposes the full interference cancellation (FIC) algorithm to cancel the interrelay interference (IRI) in the two-path cooperative system. Arising from simultaneous data transmission from the source and relay nodes, IRI may significantly decrease performance if it is not carefully handled. Compared with the existing partial interference cancellation scheme, the FIC approach is more robust yet is not as complex. Numerical results are also given to verify the proposed scheme. [ABSTRACT FROM PUBLISHER]

This paper investigates subcarrier and powerallocation schemes considering fairness issues in a cooperative orthogonal frequency-division multiple-access (OFDMA) uplink system. A pseudochannel gain is introduced to convert cooperative transmissions to virtual direct transmissions. By utilizing pseudochannel gains, we can simplify a cooperative OFDMA resource-allocation problem to a traditional one. Furthermore, minimum rate requirements are considered to include fairness issues. An algorithm that provides an efficient solution with low computational complexity is proposed. Experimental results show that the fairness with minimum rate requirements is achieved outstandingly, and cooperative transmissions prevail over direct transmissions in the aspect of the total system throughput. [ABSTRACT FROM AUTHOR]

This paper addresses resource allocation for weighted sum throughput maximization (WSTM) in multicell orthogonal frequency-division multiple-access (OFDMA) networks. Two suboptimal algorithms with polynomial-time complexity are provided. First, we determine a graph-based subcarrier allocation algorithm allowing joint transmission of two interfering links whenever such a transmission fulfills the pairwise WSTM objective. An analytical expression of the optimal power allocation with two interfering cells in single-carrier transmission is obtained, and the capacity region study serves as the basis to build the interference graph. Second, we present a distributed power-control algorithm suitable for any signal-to-interferenceplus-noise ratio (SINR) regime. It rejects users and subcarriers with weighted SINR that is too low before operating in the high SINR regime for the remaining users and subcarriers. Both algorithms and their combination are assessed via dynamic simulations, where the weight of each user is proportional to its queue length. They are shown to significantly decrease resource consumption and efficiently balance users' queue lengths. [ABSTRACT FROM AUTHOR]

In wireless mobile peer-to-peer (P2P) networks, multiple sources can provide multimedia file sharing at the same time. The selection of multiple sources is one of the key issues in the design of a multisource-transmission system in wireless mobile P2P networks. In this paper, we propose a distributed multisource sender-selection scheme to maximize the receiving data rate and minimize the energy consumption. Our scheme is based on recent advances in restless-bandit algorithms. The proposed sender-selection scheme has an indexability property that dramatically simplifies the computation and implementation of the policy. In addition, there is no need for a centralized control point, and senders can freely join and leave from the wireless mobile P2P network. Simulation results show that the proposed scheme significantly improves the receiving data rate and energy-consumption performance compared with the existing scheme. [ABSTRACT FROM AUTHOR]

In this paper, three clock-synchronization algorithms for wireless sensor networks (WSNs) under unknown delay are derived. They include the maximum-likelihood estimator (MLE), a generalization of the estimator of Noh et al., and a novel low-complexity estimator. Their corresponding performance bounds are derived and compared, and complexities are also analyzed. It is found that the MLE achieves the best performance with the price of high complexity. For the generalized version of the estimator of Noh et al., although it has low complexity, its performance is degraded with respect to the MLE. On the other hand, the newly proposed estimator achieves the same performance as the MLE, and the complexity is at the same level as that of the generalized version of the estimator of Noh et al. [ABSTRACT FROM AUTHOR]

In this paper, we propose a low-complexity decision-directed channel-estimation scheme, which offers improved performance for space-frequency-block-coded orthogonal frequency-division multiplexing (SFBC-OFDM) systems under doubly selective (i.e., frequency selective and fast fading) channels. First, we propose a square-root-free inverse-QR-decomposition-based groupwise recursive (SIQR-GR) channel-estimation algorithm employing sequences of scaled Givens rotations. The proposed SIQR-GR scheme recursively processes data decisions corresponding to the SFBC groups within each OFDM block to improve system performance under doubly selective channels. Furthermore, the avoidance of square roots and the utilization of scaled Givens rotations ensure that the proposed SIQR-GR scheme is computationally efficient. Second, we derive semi-analytical expressions for the normalized mean square error (NMSE) performance of SIQR-GR and verify the accuracy of the NMSE analysis via numerical simulations. Finally, we provide performance and complexity comparisons between SIQR-GR and previously proposed schemes. These comparisons show an excellent performance-complexity tradeoff achieved by SIQR-GR over the previous solutions under various channel conditions. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of designing channel-aware access control (CAAC) algorithms for cognitive radio networks. To protect the primary transmission, the access probabilities of secondary users are adjusted based on the channel-state information and the measured interference temperature. It is shown that the proposed CAAC algorithm always converges to a fixed point. Furthermore, the CAAC algorithm can be interpreted as a noncooperative game. Then, the game model is extended to include general access utilities, unsuccessful transmission discount, and interference constraints. Sufficient conditions are established to guarantee the uniqueness of the Nash equilibrium (NE) of the proposed general game model, and a distributed iteration algorithm is proposed to find the unique NE. The convergence properties of this algorithm in continuous-time iteration, as well as in the discrete-time version, are proved under some sufficient conditions. Simulation results demonstrate the convergence and effectiveness of the distributed channel-access algorithms. [ABSTRACT FROM AUTHOR]

Seamless wireless local area network (WLAN)-to-cellular handover can often be very difficult to achieve. A particularly bad scenario may occur when mobile users exit from indoor WLAN coverage to outdoors during active voice connections. In this paper, we report on a measurement-based study of this type of vertical handover (VHO) situation. The presented results come from measurements taken by traversing many indoor-to-outdoor paths for a large number of building exits while measuring multi-access-point (AP) WLAN coverage. The collected data was then processed to determine handover characteristics when optimal threshold-based handover triggering is used. Our results show that it is very difficult to successfully complete the handover unless the WLAN deployment has carefully been engineered. For WLAN deployments which restrict the use of lower data rates, we propose a limited data rate usage (LDU) algorithm that improves VHO performance without adversely affecting the WLAN capacity. Analytic models and simulations using the experimental data are presented, which show the improvements in call blocking when the LDU algorithm is used. [ABSTRACT FROM AUTHOR]

An iterative receiver for a multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system is considered to jointly decode the transmitted bits and estimate the channel state. The receiver consists of a list detector, a turbo decoder, and a channel estimator that is based on the space-alternating generalized expectation-maximization (SAGE) algorithm. This paper proposes a way to improve the convergence of the iterative detection and decoding by using a priori information to also recalculate the candidate list, aside from the log-likelihood ratios (LLRs) of the coded bits. A new list parallel interference cancellation (PlC) detector is derived to approximate an a posteriori probability (APP) algorithm with reduced complexity and minimal losses of performance. Further- more, the organization of spectrally efficient decision-directed (DD) SAGE channel estimation under a constrained number of detector-decoder iterations is optimized by computer simulations, and the SAGE algorithm itself is modified for nonconstant envelope constellations. The list recalculation is shown to improve convergence. It is also shown that the list PlC detector with good initialization outperforms the K-best list sphere detector (LSD) in the case of small list sizes, whereas the complexities of the algorithms are of the same order. Despite the low preamble density and fast-fading channel, the proposed iterative receiver shows robust performance. [ABSTRACT FROM AUTHOR]

In this paper, a blind symbol synchronization algorithm is presented for orthogonal frequency-division multiplexing (OFDM) systems, and a new timing function based on the redundancy of the cyclic prefix (CP) is introduced. It proves that the maximum of this function necessarily points to the correct timing offset, irrespective of channel conditions when the signal-to-noise ratio is high. Using the timing function, the timing offset is estimated through a searching algorithm. Channel power profile and channel length information are unnecessary. Simulation results show that the proposed algorithm is robust and outperforms the existing CP-based algorithms, particularly in frequency-selective fading channels. [ABSTRACT FROM AUTHOR]

The location information of sensor nodes in wireless sensor networks is crucial for various applications such as emergency rescue operations, environmental monitoring, home automation, and traffic control. In this paper, a new method to improve the anchor location accuracy in wireless sensor networks is proposed based on fusion of Global Positioning System (GPS) measurements and anchor-to-anchor parameter estimates. Novel algorithms are derived to increase the accuracy of anchor locations using both anchor-to-anchor distance and angle-of-arrival (AOA) estimates for both line-of-sight (LOS) and non-LOS (NLOS) scenarios. When using anchor-to-anchor distance estimates in LOS conditions, an optimization-based algorithm is developed. The Cramer-Rao lower bound (CRLB) is derived to benchmark positioning accuracy in 3-D environments with both GPS measurements and anchor-to-anchor parameter estimates, which has not been studied in the literature. Simulation results demonstrate that the proposed algorithms can substantially improve anchor position accuracy, and the performance of the proposed algorithms approaches the CRLB. [ABSTRACT FROM AUTHOR]

In wireless sensor networks (WSNs), the field information (e.g., temperature, humidity, airflow) is acquired via several battery-equipped wireless sensors and is relayed toward a sink node. As the size of the WSNs increases, it becomes inefficient (in terms of power consumption) when gathering all information in a. single sink. To tackle this problem, one can increase the number of sinks. The set of sensor nodes that are sending data to sink k is called commodity k. In this paper, we formulate the lexicographically optimal commodity lifetime (LOCL) routing problem. A stepwise centralized algorithm called the LOCL algorithm is proposed, which can obtain the optimal routing solution and lead to lexicographical fairness among commodity lifetimes. We then show that, under certain assumptions, the lexicographical optimality among commodity lifetimes can be achieved by providing lexicographical optimality among node lifetimes. This motivates us to propose our second algorithm, which is called the lexicographically optimal node lifetime (LONL) algorithm, which is suitable for practical implementation. Simulation results show that our proposed LOCL and LONL algorithms increase the normalized commodity and node lifetimes compared with the maximum lifetime with multiple sinks (MLMS) and lexicographical max-min fair (LMM) routing algorithms. [ABSTRACT FROM AUTHOR]

In this paper, a channel-driven rate and power adaptation (CDRPA) algorithm is proposed for wireless local area networks (WLANs) in generalized Nakagami fading channels. Through the channel information of the first packet, the CDRPA algorithm can lower the complexity of comparing various rates and power levels. In the case of the IEEE 802.11 WLAN, the computation complexity of the CDRPA algorithms is reduced by more than 94% compared with the complete-search link adaptation. A physical and/or medium access control (MAC) cross-layer analytical model is also developed to evaluate the goodput and energy efficiency of the carrier sense multiple access with a collision avoidance MAC protocol in Nakagami fading channels. Our numerical results show that the CDRPA algorithm is not only more energy efficient in the Nakagami fading channel but can also achieve comparable and even higher throughput compared with the complete-search link adaptation approach. [ABSTRACT FROM AUTHOR]

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]