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This paper considers optimal joint time, frequency, and power allocation for energy-efficient device-to-device (D2D) communications in an overlay cellular network, where multiple D2D transmitters communicate with their corresponding D2D receivers while utilizing the energy harvested from a cellular base station (BS). Due to channel estimation error and feedback delays, the channel state information (CSI) available at the transmitters is usually imperfect, which can significantly deteriorate the energy efficiency (EE) of the considered system. To mitigate the impact of imperfect CSI, we formulate a non-convex robust optimization problem for the maximization of the EE (in bits/Joule) of the system while ensuring quality of service (QoS) requirements on the minimum data rata and the minimum amount of harvested energy for cellular and D2D users, respectively. We reveal that the optimal energy-efficient D2D transmission should exhaust all the harvested energy of each D2D transmitter. Exploiting this fact, we propose an efficient iterative algorithm for obtaining the optimal solution. To strike a balance between performance and computational complexity, we further propose a low-complexity suboptimal algorithm. Simulation results show that compared with several baseline schemes, both the proposed optimal and suboptimal algorithms can significantly improve the EE of wireless-powered D2D communications under imperfect CSI. Moreover, the proposed suboptimal algorithm is close-to-optimal when the number of cellular users are small or the channel estimation error is large. [ABSTRACT FROM AUTHOR]

The multi-UAV network is promising to extend conventional networks by providing broader coverage, and better reliability. Nevertheless, the broadcast nature of wireless signals, and the broader coverage expose multi-UAV communications to the threats of passive eavesdroppers. Recent studies mainly focus on securing a single legitimate link, or communications between a UAV, and multiple ground users in one/two-UAV-aided networks, while the physical layer secrecy analysis for hierarchical multi-UAV networks is underexplored. In this paper, we investigate a general two-tier UAV network consisting of multiple UAV transmitters (UTs), and multiple UAV receivers (URs) in the presence of multiple UAV eavesdroppers (UEs). To protect all legitimate UT-UR links against UEs at the physical layer, we design a two-stage framework consisting of a UT-UR association stage, and a cooperative transmission stage. Specifically, we formulate the secure transmission problem into a many-to-one matching game followed by an overlapping coalition formation (OCF) game, taking into account the limited capabilities, and the throughput requirements of URs, as well as the transmission power constraints of UTs. A matching algorithm, and an OCF algorithm are proposed to solve these two sequential games whose convergences, and stabilities are guaranteed theoretically. Simulation results show the superiority of our algorithms, and the effectiveness of our two-stage game framework in the terms of secrecy performance. [ABSTRACT FROM AUTHOR]

Sparse code multiple access (SCMA) is one type of non-orthogonal multiple access techniques for the fifth-generation wireless communication networks. Existing multiuser detection algorithms for SCMA uplink systems are based on the assumption that signals are in synchronization. However, asynchrony cannot be neglected due to the propagation delays in practical environments. In this paper, we present three detection algorithms for uplink asynchronous SCMA systems, namely belief propagation message passing algorithm, belief propagation with equal gain combining message passing algorithm, and partial phase-coherent algorithms. Simulation results show that our proposed asynchronous detection algorithms are able to offer descent bit error rate performances, with only a small performances loss compared to the synchronous case. Moreover, our proposed algorithms converge well in the uplink asynchronous SCMA systems. [ABSTRACT FROM AUTHOR]

As an important complement and enhancement technique for cellular communication systems, the device-to-device (D2D) technique has exhibited a number of benefits in terms of, for instance, offering an improved spectral efficiency, enabling a reduced transmit power and providing an enhanced channel capacity, etc. However, a severe interference may be imposed on the conventional cellular users by the activated D2D links, thus, substantially eroding the performance of the former. In this paper, we propose an interference limited area (ILA) based D2D-management scheme along with an appropriately designed power control algorithm for mitigating the above-mentioned interference. We first derive the closed-form expressions of the average coverage probability for both the cellular and D2D links under the proposed ILA scheme, followed by proposing a resource-allocation algorithm subject to a power control mechanism. Numerical results show that the proposed ILA scheme is capable of outperforming the conventional scheme in terms of both the coverage probability (i.e., for both cellular and D2D links) and the sum data rate, particularly in the scenarios with a high D2D density and a high signal-to-interference-plus-noise ratio. [ABSTRACT FROM AUTHOR]

Short packet communications (SPC) will play an important role in future Internet-of-Things networks. Conventional pilot-assisted transmission (PAT) needs significant overhead to obtain accurate channel state information (CSI) for further symbol detection and bit recovery, thereby reducing the spectral efficiency of the transmission. In this paper, a machine learning framework called Label-Assisted Transmission is proposed, in which the received signals are grouped into clusters through clustering algorithms and known labels are transmitted for cluster-symbol/bits mapping. This novel framework supports bit recovery directly without requiring the bit-symbol mapping information. When such mapping information is available, modulation constrained (MC) clustering algorithms are proposed, which exploit the unique characteristics of digital communication signals. For frequency-flat channels, this novel design needs only one known label regardless of the modulation size and the missing labels can be reconstructed using a proposed label reconstruction scheme. For frequency-selective channels with $L$ -tap time domain channel responses, only $L$ known labels are needed to reconstruct the missing labels if orthogonal frequency division multiplexing technology is adopted. The proposed clustering receiver works well even when the number of clusters is much larger than the number of received samples. The performance of the proposed framework is analyzed empirically through extensive simulations, which verify that the proposed scheme approaches the maximum likelihood detector with perfect CSI. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) are anticipated to be widely deployed in future wireless communications, due to their advantages of high mobility and easy deployment. However, the broadcast nature of air-to-ground line-of-sight wireless channels brings a new challenge to the information security of UAV-ground communication. This paper tackles such a challenge in the physical layer by exploiting the mobility of UAV via its trajectory design. We consider a UAV-ground communication system with multiple potential eavesdroppers on the ground, where the information on the locations of the eavesdroppers is imperfect. We formulate an optimization problem, which maximizes the average worst case secrecy rate of the system by jointly designing the robust trajectory and transmit power of the UAV over a given flight duration. The nonconvexity of the optimization problem and the imperfect location information of the eavesdroppers make the problem difficult to be solved optimally. We propose an iterative suboptimal algorithm to solve this problem efficiently by applying the block coordinate descent method, $\mathcal {S}$ -procedure, and successive convex optimization method. Simulation results show that the proposed algorithm can improve the average worst case secrecy rate significantly, as compared to two other benchmark algorithms without robust design. [ABSTRACT FROM AUTHOR]

This paper aims at solving two classes of energy efficiency (EE) maximization problems in multiple channels wireless communication systems. First, the EE maximization problem with sum power constraint is solved based on the geometric water-filling approach; and second, the approach is extended into the EE maximization problem with additional least throughput requirement constraint. Our proposed algorithms make use of the water-filling structure of the optimal solution and provide exact and computation efficient solution to the energy-efficient power allocation problems. The proposed algorithms also have excellent scalability, which is applicable for large-scale wireless communication systems. Optimality of the proposed algorithms is strictly proved, and the proposed algorithms only require low-degree polynomial computational complexity. Numerical results are presented to demonstrate the efficiency of the proposed algorithms. To the best of our knowledge, no prior algorithms in the existing literature could provide such solutions to the EE maximization problems under the merit of exactness and the efficiency. [ABSTRACT FROM AUTHOR]

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]

In the air–ground propagation channel, multipath propagation severely affects the performance of the communication, navigation, and surveillance systems used in civil aviation. To gain a deeper understanding of the air–ground channel, we are interested in the locations of objects causing multipath propagation. Therefore, in this paper we propose and experimentally validate an algorithm to localize reflectors causing multipath components based on channel sounding data collected using omnidirectional antennas. The algorithm relies on superresolution parameter estimation and tracking as well as on a localization algorithm. Using both simulations and channel sounding data collected from flight trials, we demonstrate the ability to reliably localize the reflectors causing multipath components. [ABSTRACT FROM AUTHOR]

With the advent of the Internet of things, massive machine-type communications (mMTC) have become one of the most important requirements for next generation communication systems. In the mMTC scenarios, grant-free nonorthogonal multiple access on the transmission side and compressive sensing-based multi-user detection (CS-MUD) on the reception side are a promising solution because many users sporadically transmit small data packets at low rates. In this paper, we propose a novel CS-MUD algorithm for the active user and data detection in the mMTC systems. The proposed scheme consists of the maximum a posteriori probability (MAP) based active user detector (MAP-AUD) and the MAP-based data detector (MAP-DD). By exchanging the extrinsic information between MAP-AUD and MAP-DD, the proposed algorithm improves the active user detection performance and the reliability of the data detection. In addition, we extend the proposed algorithm to exploit group sparsity. By jointly processing the multiple received data with common activity, the proposed algorithm dramatically enhances the active user detection performance. We show by numerical experiments that the proposed algorithm achieves a substantial performance gain over existing algorithms. [ABSTRACT FROM AUTHOR]

The employment of social similarity (SS) aware device-to-device (D2D) user equipment (UE)-to-network (UE-NW) relay helps to improve system capacity and UEs’ accessability to the evolved Node B (eNB), where a crucial aspect is the design of the relay helper UE (HUE) selection process. However, few existing studies jointly consider the diverse impacts from various design criteria on the performance of HUE selection. In this paper, we formulate the SS-aware D2D UE-NW relay selection (RS) issue as a multiobjective binary integer linear programming (MOBILP) problem under the constraints of several criteria. Then, we propose a new two-stage D2D UE-NW selection scheme. Specifically, a joint algorithm exploiting the intuitionistic fuzzy analytic hierarchy process and the entropy weight generation method is designed for stage one, which provides both subjective and objective preferences for assisting decision making. In stage two, with the constructed decision weights, the MOBILP can be transformed to a simpler binary integer linear programming problem and thus be solved distributively through an efficient message passing method. Based on realistic social data traces, our simulation results validate the benefits of the proposed two-stage scheme, which ensures high system performances in terms of throughput, fairness and energy efficiency. [ABSTRACT FROM AUTHOR]

Ultradense heterogeneous networks (HetNets) are emerging as an inevitable approach to tackle the capacity crunch in cellular networks. However, imbalanced load among small and macrocells and poor resource utilization as a consequence in HetNets remains a long-standing problem. This paper addresses this problem by presenting a solution for maximization of coverage and capacity while minimizing load imbalance among macro and small cells. Most recent studies on the topic focus on either optimization of coverage, capacity or load, or a combination of two of these three intertwined objectives. We formulate the optimization problem as a function of two hard parameters namely antenna tilt and transmit power, and a soft parameter, cell individual offset, that affect the coverage, capacity, and load directly. The resulting solution is a combination of the otherwise conflicting coverage and capacity optimization (CCO) and load balancing (LB) self-organizing network (SON) functions. In the presented joint CCO-LB solution, a conflict free operation of CCO and LB is ensured by designing a novel load aware user association methodology and resolving the effects of shadowing on coverage probability using stochastic approximation. The problem is proven to be nonconvex and is solved using genetic algorithm, sequential quadratic programming, and pattern search algorithms. The proposed CCO-LB solution is compared against two recently proposed CCO and CCO-LB solutions in the literature. Results show that the proposed solution can yield significant gain in terms of throughput, spectral efficiency, and load distribution. [ABSTRACT FROM AUTHOR]

This paper considers a heavy loaded full-duplex (FD) small cell consisting of one FD base station and multiple half-duplex users where the number of subchannels is less than the number of uplink and downlink users. With the objective of maximizing the total sum-rate, a joint power allocation, and user pairing problem is formulated. To solve this problem, a novel decomposition method is proposed, which decouples the power allocation and user pairing problem into two subproblems. It is proven that the optimal solution of subproblems is the optimal solution of the original problem. Then, optimal algorithms are developed for the two subproblems. Numerical results show that the proposed algorithm achieves better performance compared with the baselines of the greedy algorithm and random pairing algorithm. [ABSTRACT FROM AUTHOR]

Traffic offloading via device-to-device communications is expected to play a major role to meet the exponential data traffic growth in wireless networks. In this paper, we focus on the problem of user capacity maximization in ultra-dense heterogeneous networks with device-to-device cooperation, where a large number of users in a given geographical area request common data content, such as video on demand streaming, with strict quality of service guarantees. We aim at finding the best strategy for delivering the content either over long range connectivity from the access points or short range connectivity from peer mobile terminals while meeting a target rate per served user. We formulate the multiuser resource management problem as an optimization problem including traffic offloading and channel allocation considering a very high user density reaching up to 1.75 users per square meter. We extend the system model to include mobile terminals acting as content owners by having the content cached locally, in order to further enhance the network capacity and coverage. We then propose an iterative resource management solution, which first solves the optimization subproblem of traffic offloading with orthogonal channels, and then optimally allocates channels to the transmitters with minimized interference due to channel reuse. We also propose efficient suboptimal hierarchical tree-based algorithms that operate in real time with dynamic and fast solutions for ultra-dense networks. For performance evaluation, we consider a realistic scenario consisting of a stadium topology with thousands of mobile terminals active simultaneously. We generate results as a function of a wide range of system parameters, and demonstrate that the proposed algorithms achieve near-optimal performance with notably low time complexity. [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]

In this paper, we investigate the cross-layer resource optimization for wireless relay networks with dynamic node-selfishness information. The degree of intrinsic selfishness (DeIS) and the degree of extrinsic selfishness (DeES) of the relay node (RN) are defined as the effects of its own residual energy resource and the incentive in an incentive mechanism, respectively. A model of two-timescale node-selfishness dynamics is constructed to describe the time-varying characteristics of the RN's DeIS and DeES. Based on the two-timescale node-selfishness dynamics of the RNs, a two-timescale resource-optimization dynamical algorithm (TRODA) is employed to control the transmit powers of both RNs and end users (EU), as well as the flow rates of the data packets injected by all EUs. Meanwhile, the stability and the tracking error of the TRODA under the two-timescale node-selfishness dynamics are analyzed by Lyapunov theory. Our simulation results demonstrate that the two-timescale optimization algorithm is stable and has trivial tracking error. [ABSTRACT FROM AUTHOR]

The ability of mobile devices to be connected to more than one radio node at the same time enables mobile devices to transmit and receive traffic to and from multiple paths. This ability helps to increase the average mobile device data rate and to improve the network reliability. Load balancing among multiple paths become a key factor to avoid network congestion, nevertheless it requires efficient techniques to split traffic without adding more delay or generating too much packet reordering for delay-sensitive traffic. In this paper, we address two key issues in the context of uplink wireless mobile networks: 1) how to accurately split traffic among multiple paths and 2) how to minimize the end-to-end delay without increasing packet reordering. We propose delay-aware load balancing algorithm (DALBA), a novel strategy that splits traffic at the granularity of the packet. DALBA aims to minimize the splitting error (SE) and the end-to-end delay difference by effectively using all of the available paths. We analyze DALBA's performance through extensive simulations using H.264 video traffic. Numerical results demonstrate that DALBA outperforms previous algorithms in terms of SE, end-to-end delay and peak signal-to-noise ratio while keeping packet reordering to a suitable low value. [ABSTRACT FROM AUTHOR]

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]

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]

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]

Recently, ultra wide-band (UWB) wireless communication technology, which provides high data transmission rates and is capable of linearly trading off between throughput and signal-to-noise ratio (SNR), has drawn much attention for short-range wireless networks. To fully exploit its desirable features and to minimize its interference with coexisting other systems requires knowledge of the SNRs at the receivers. In this paper, we propose an algorithm for estimating the pulse energy-to-noise ratio of an UWB signal through utilization of output samples from a correlator in the receiver and evaluate the performance of the proposed algorithm through computer simulation. A notable feature of the proposed algorithm is that it does not affect the effective throughput because the estimation process does not require any additional specific training signals. [ABSTRACT FROM AUTHOR]

The high-speed railway wireless communication network architecture is gradually transforming from a traditional GSM-Railway (GSM-R) cellular network to a 5G heterogeneous ultra-dense communication network. How to effectively deal with the interference while obtaining the capacity gain has become an inevitable problem. This article proposes a power allocation interference alignment algorithm based on game equilibrium with the goal of joint optimization about throughput and energy efficiency for imperfect channels in high-speed railway communication. Firstly, the imperfect Channel State Information including delay and fading is calculated. Then, in order to improve system throughput and energy efficiency, we establish a game model and prove the existence of Nash equilibrium in the model. At the same time, a power allocation iterative algorithm based on Recurrent Neural Network is proposed. Finally, combined with the interference alignment algorithm based on a maximal signal-to-noise ratio, the optimal power matrix is calculated by iteration to achieve interference management optimization. The simulation results prove that our algorithm has superior performance in improving the system throughput, energy efficiency and transmission reliability in high-speed railway wireless communication with imperfect channels. [ABSTRACT FROM AUTHOR]

Femto base stations (FBSs) are cost-effective choices for wireless service providers (WSPs) to provide better indoor coverage and capacity in cellular networks. With the introduction of femtocells, spectrum allocation among macro base stations (MBSs) and numerous FBSs becomes challenging. WSPs will allocate resources among hierarchical infrastructures to mitigate mutual interference and maximize WSPs' revenue from service provisioning. In this paper, we propose a channel allocation and service provision framework to help WSPs allocate resources and increase revenue. The spectrum allocation and revenue maximization problem is formulated as a convex problem, and a centralized method is proposed to efficiently solve it. We also propose a distributed algorithm called LD (based on Lagrangian decomposition) to achieve a near-optimal solution with low computational and communication complexity, which can be used when the system is on a large scale. The simulation results show that our scheme can significantly improve the system's revenue. [ABSTRACT FROM PUBLISHER]

Cooperative communication (CC) offers an efficient and low-cost way to achieve spatial diversity by forming a virtual antenna array among single-antenna nodes that cooperatively share their antennas. It has been well recognized that the selection of relay nodes plays a critical role in the performance of CC. Most existing relay selection strategies focus on optimizing the outage probability or energy consumption. To fill in the vacancy of research on throughput improvement via CC, we study the relay selection problem with the objective of optimizing the throughput in this paper. For unicast, it is a P problem, and an optimal relay selection algorithm is provided with a correctness proof. For broadcast, we show the challenge of relay selection by proving it nonprobabilistic hard (NP-hard). A greedy heuristic algorithm is proposed to effectively choose a set of relay nodes that maximize the broadcast throughput. Simulation results show that the proposed algorithms can achieve high throughput under various network settings. [ABSTRACT FROM PUBLISHER]

Collaborative spectrum sensing (CSS) between secondary users (SUs) in cognitive networks exhibits an inherent tradeoff between minimizing the probability of missing the detection of the primary user (PU) and maintaining a reasonable false alarm probability (e.g., for maintaining good spectrum utilization). In this paper, we study the impact of this tradeoff on the network structure and the cooperative incentives of the SUs that seek to cooperate to improve their detection performance. We model the CSS problem as a nontransferable coalitional game, and we propose distributed algorithms for coalition formation (CF). First, we construct a distributed CF algorithm that allows the SUs to self-organize into disjoint coalitions while accounting for the CSS tradeoff. Then, the CF algorithm is complemented with a coalitional voting game to enable distributed CF with detection probability (CF-PD) guarantees when required by the PU. The CF-PD algorithm allows the SUs to form minimal winning coalitions (MWCs), i.e., coalitions that achieve the target detection probability with minimal costs. For both algorithms, we study and prove various properties pertaining to network structure, adaptation to mobility, and stability. Simulation results show that CF reduces the average probability of miss per SU up to 88.45%, relative to the noncooperative case, while maintaining a desired false alarm. For CF-PD, the results show that up to 87.25% of the SUs achieve the required detection probability through MWCs. [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]

In this paper, we model the various users in a wireless network (e.g., cognitive radio network) as a collection of selfish autonomous agents that strategically interact to acquire dynamically available spectrum opportunities. Our main focus is on developing solutions for wireless users to successfully compete with each other for the limited and time-varying spectrum opportunities, given experienced dynamics in the wireless network. To analyze the interactions among users given the environment disturbance, we propose a stochastic game framework for modeling how the competition among users for spectrum opportunities evolves over time. At each stage of the stochastic game, a central spectrum moderator (CSM) auctions the available resources, and the users strategically bid for the required resources. The joint bid actions affect the resource allocation and, hence, the rewards and future strategies of all users. Based on the observed resource allocations and corresponding rewards, we propose a best-response learning algorithm that can be deployed by wireless users to improve their bidding policy at each stage. The simulation results show that by deploying the proposed best-response learning algorithm, the wireless users can significantly improve their own bidding strategies and, hence, their performance in terms of both the application quality and the incurred cost for the used resources. [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]

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

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

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

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

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

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

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

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

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

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

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

New sphere decoding and synchronization algorithms for multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems are proposed in this paper. In particular, an iterative list branch-and-bound (BB) algorithm based on the basic BB algorithm is described to obtain a candidate list to compute soft information that is used in the iterative detector. Furthermore, an improved algorithm that uses prior information from the preceding iteration to calculate the lower bound is proposed, and the candidate list is updated every iteration. To obtain a complete modem architecture, we propose an efficient expectation-maximization (EM)-based iterative algorithm for synchronization and channel estimation to interface with the proposed list-sphere-decoding detector, and we investigate the performance of the designed MIMO-OFDM modem on a realistic fading channel. The obtained performance results show that it is possible to practically design a performing MIMO-OFDM modem with high spectral efficiency, i.e., 8 bit/s/Hz with a 4 x 4 16-QAM MIMO-OFDM system. [ABSTRACT FROM AUTHOR]

In this paper, we propose an adaptive linear-receiver structure based on interpolated finite-impulse response (FIR) filters with adaptive interpolators for direct-sequence code-division multiple-access (DS-CDMA) systems in multipath channels. The interpolated minimum mean-squared error (MMSE) and the interpolated constrained minimum-variance (CMV) solutions are described for a novel scheme, where the interpolator is rendered time-varying in order to mitigate multiple-access interference and multiple-path propagation effects. Based upon the interpolated MMSE and CMV solutions, we present computationally efficient stochastic gradient and exponentially weighted recursive least squares type algorithms for both receiver and interpolator filters in the supervised and blind modes of operation. A convergence analysis of the algorithms and a discussion of the convergence properties of the method are carried out for both modes of operation. Simulation experiments for a downlink scenario show that the proposed structures achieve a superior bit-error-rate convergence and steady-state performance to previously reported reduced-rank receivers at lower complexity. [ABSTRACT FROM AUTHOR]

Call admission control (CAC) strongly influences the performance of 3G/4G spread spectrum systems because it determines the number of active users that are admitted to the network, i.e., influences spectral efficiency. A novel air interface CAC algorithm is introduced in this paper. It optimizes the utilization of radio resources and provides real-time adaptation to the radio channel with generalized multiplicative fading. Users are handled as memory-less traffic sources. The suggested CAC method was evaluated for lognormal fading and ON/OFF traffic. [ABSTRACT FROM AUTHOR]

In this paper, we consider blind channel estimation for cyclic-prefixed single-carrier (CP-SC) systems via second-order statistics only. By exploiting the existence of real symbols in the transmitted data block, we develop a simple technique for blind channel estimation that does not need redundant precoding or virtual carriers. Hence, the proposed algorithm provides band-width efficiency. A side benefit of the proposed algorithm is that the phase ambiguity, which is an inherent problem in traditional blind channel estimation, is reduced to sign ambiguity only. This side benefit facilitates signal detection in digital communications where symbols are usually taken from a finite alphabet. Although the proposed method is mainly developed for channel estimation in single-input-single-output CP-SC systems, it can also be applied straightforwardly to single-input-multiple-output systems (either with CP-SC or other kinds) and multiple-input-multiple-output systems whenever real symbols exist or are deliberately inserted in the transmission. [ABSTRACT FROM AUTHOR]

Design of efficient dynamic channel allocation (DCA) algorithms has an important impact on performance optimization of wireless mobile networks. The previously proposed DCA algorithms are shown to have good performance but only for certain services and under certain load conditions. Within this paper, we propose a new cost-function-based DCA algorithm, which is fully adaptive to service and load conditions and includes some well-known DCA algorithms such as Random, Minimum Interference, and Autonomous Reuse Partitioning DCA as special cases. By using dynamic system-level simulations, we show that the algorithm provides the same or substantially better performance than these DCA algorithms, with low signalization and computation overhead. We also show the general limits of DCA algorithms in the presence of other interference reduction techniques such as power control and smart antennas. [ABSTRACT FROM AUTHOR]

In this paper, we propose a wireless system that realizes theoretical benefits of space-time cooperation. Specifically, we design a space-time cooperative system based on orthogonal frequency division multiplexing (OFDM), which we refer to as a cooperative (CO)-OFDM system. Our design includes a two-phase space-time cooperation protocol, as well as a transmitter and receiver architecture that facilitates cooperation. Furthermore, we devise a frame structure, on which we build practical timing and frequency synchronization algorithms and a channel estimation algorithm. In particular, the proposed frequency synchronization algorithm utilizes the underlying structure of the cooperation protocol, and the proposed channel estimation algorithm is based on a pairwise orthogonal construction of two sequences. We validate the performance of the proposed synchronization and channel estimation algorithms through simulations. We then present simulation results that demonstrate the overall performance advantage of the CO-OFDM system over an OFDM system without cooperation, not only under idealistic assumptions but also under realistic situations where the proposed algorithms are employed. [ABSTRACT FROM AUTHOR]

Device-free identification (DFI) is a promising technique, which could recognize human identity using his/her unique influence on surrounding wireless signals in a device-free and contact-free manner. It could maintain the privacy of a user and enable smart applications to provide customized service for a specific user. Despite its advantages over other person's identification systems, one fundamental problem to solve is that the accuracy of the DFI system is a little bit low due to the extremely noisy wireless measurements. The goal of this work is to explore and exploit a method to extract intrinsic features from the noisy channel state information (CSI) so as to realize high-performance DFI. To this end, we propose a novel empirical-mode-decomposition-based general DFI framework, which decomposes raw noisy CSI measurements into intrinsic mode functions (IMF) and extracts intrinsic features from the IMF components accordingly. Under the proposed framework, we also develop two DFI systems based on the respiration and gait biometric features. Extensive experiments carried out on commodity WiFi reveal that the developed systems could identify a person with an accuracy of over 90% from a group of ten persons. [ABSTRACT FROM AUTHOR]

Many emerging applications, such as security surveillance and smart healthcare, have incubated the device-free localization (DFL) technique, which could estimate the location of a target without equipping any device. However, current DFL system needs labor-intensive training to learn the influence of the target on surrounding wireless signals, so as to provide model parameters or radio maps for the location estimation algorithm. To address this issue, we develop a novel robust training-free DFL system, named DeFi, which could directly estimate the target location by refining the angle-of-arrival (AOA) of the target reflection path based on WiFi channel state information. We analyze the characteristics of the static paths and the motion paths, eliminate the static paths using a background elimination algorithm, and separate out the target reflection path from the motion paths according to the AOA and equivalent time-of-flight measurements. With the AOA of the target reflection path as observation information, we robustly estimate the target location based on a particle filter algorithm. We implement the proposed DeFi system on commodity off-the-shelf WiFi devices and validate its performance in two indoor scenarios. Experimental results show that DeFi achieves a median error of less than 0.6 m. [ABSTRACT FROM AUTHOR]

Fifth generation new radio aims to facilitate new use cases in wireless communications. Some of these new use cases have highly demanding latency requirements; many of the powerful forward error correction codes deployed in current systems, such as the turbo and low-density parity-check codes, do not perform well when the low-latency requirement does not allow iterative decoding. As such, there is a rejuvenated interest in noniterative/one-shot decoding algorithms. Motivated by this, we propose a signal-to-noise ratio-adaptive convolutionally coded system with optimized constellations designed specifically for a particular set of convolutional code parameters. Numerical results show that significant performance improvements in terms of bit-error-rate and spectral efficiency can be obtained compared to the traditional adaptive modulation and coding systems in low-latency communications. [ABSTRACT FROM AUTHOR]