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The explosive growth of Internet-of-Things (IoT) applications such as smart cities and Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating the rapid development of new techniques for enhancing spectrum utilization needed by new generation wireless communication technologies. Among others, dynamic spectrum access (DSA) is one of the most widely accepted approaches. In this paper, as an enhancement of existing works, we take into consideration of inter-node collaborations in a dynamic spectrum environment. Typically, in such distributed circumstances, intelligent dynamic spectrum access almost invariably relies on self-learning to achieve dynamic spectrum access improvement. Whereas, this paper proposes a DSA scheme based on deep reinforcement learning to enhance spectrum and access efficiency. Unlike traditional Q-learning-based DSA, we introduce the following to enhance the spectrum efficiency in dynamic IoT spectrum environments. First, deep double Q-learning is adopted to perform local self-spectrum-learning for IoT terminals in order to achieve better dynamic access accuracy. Second, to accelerate learning convergence, federated learning (FL) in edge nodes is used to improve the self-learning. Third, multiple secondary users, who do not interfere with each other and have similar operation condition, are clustered for federated learning to enhance the efficiency of deep reinforcement learning. Comparing with the traditional distributed DSA with deep learning, the proposed scheme has faster access convergence speed due to the characteristic of global optimization for federated learning. Based on this, a framework of federated deep reinforcement learning (FDRL) for DSA is proposed. Furthermore, this scheme preserves privacy of IoT users in that FDRL only requires model parameters to be uploaded to edge servers. Simulations are performed to show the effectiveness of theproposed FDRL-based DSA framework. [ABSTRACT FROM AUTHOR]

Recently, reconfigurable intelligent surface (RIS) has drawn much attention due to its capability of improving coverage and communication performance. The development of RIS-assisted communication technology relies on deep understanding of RIS channel characteristics. However, most of the existing investigations focus on the impact of RIS, ignoring the existence of local scatterers in the real propagation environment. The ideal propagation condition limits the accuracy and application of the developed channel model. In this paper, we aim to analyze the channel characteristics of RIS-assisted near-filed communication by considering different conditions of local scatterers. Specifically, we propose a three-dimensional (3D) RIS-assisted multiple-input multiple-output (MIMO) channel model based on a three-dimensional cylinder model, which considers line-of-sight, single-bounced at RIS (SBR) and double-bounced (DB) modes where radio waves reflect from RIS and scatterers near receiver. Based on the proposed channel model, we investigate some key statistical properties for SBR and DB propagation, including the time-frequency-space correlation function and Doppler power spectrum. From the simulation results, it is found that RIS element number, RIS horizontal and vertical locations, distribution of surrounding scatterers, and movement of Rx have significant impacts on channel characteristics. Finally, channel capacities of SBR and DB modes are calculated, where the large size and appropriate locations of RIS significantly improve the channel capacity of RIS-assisted communication. These numerical results and observations can be used for design of RIS-assisted near-field communication systems. [ABSTRACT FROM AUTHOR]

In this paper, the maximum signal-to-interference-plus-noise ratio (MSINR) beamforming problem in antenna-array CDMA systems is considered. In this paper, a modified MSINR criterion presented in a previous paper is interpreted as an unconstrained scalar cost function. By applying recursive least squares (RLS) to minimize the cost function, a novel blind adaptive beamforming algorithm to estimate the beamforming vector, which optimally combines the desired signal contributions from different antenna elements while suppressing noise and interference, is derived. Neither the knowledge of the channel conditions (fading coefficients, signature sequences and timing of interferers, statistics of other noises, etc.) nor training sequence is required. Compared with previously published adaptive beamforming algorithms based on the stochastic-gradient method, it has faster convergence and better tracking capability in the time-varying environment. Simulation results in various signal environments are presented to show the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of decoding in large-scale multiple-input–multiple-output (MIMO) systems. In this case, the optimal maximum-likelihood (ML) detector becomes impractical due to an exponential increase in the complexity with the signal and the constellation dimensions. This paper introduces an iterative decoding strategy with a tolerable complexity order. We consider a MIMO system with finite constellation and model it as a system with sparse signal sources. We propose an ML relaxed detector that minimizes the Euclidean distance with the received signal while preserving a constant \ell1 -norm of the decoded signal. We also show that the detection problem is equivalent to a convex optimization problem, which is solvable in polynomial time. Two applications are proposed, and simulation results illustrate the efficiency of the proposed detector. [ABSTRACT FROM PUBLISHER]

Cellular heterogeneous networks (HetNets), which are realized through shared carrier deployments of macrocells and small cells, are widely seen as a potential solution to serve growing data capacity demands. While these networks pose significant challenges in interference management, much of the focus in earlier efforts has been limited only to small-cell range expansion in the downlink. In this paper, we provide a comprehensive analysis of interference management techniques applicable to the uplink of cellular HetNets, with the goal of characterizing and improving edge user (e.g., 5th percentile) performance. In particular, we propose and study virtual soft-handoff (VSHO), which offers a low-complexity and low-overhead solution that exploits the link asymmetry observed in the uplink geometry of HetNets. VSHO exploits the fact that, in the uplink, an edge macro user who suffers from very low throughput may be closer to a nearby small cell than its own macrocell. The intuition is that such macro users should have better decoding opportunity when their signals are processed at the nearby small cell with better channel conditions. We also study how interference cancelation (IC) and interference avoidance through resource blanking can be incorporated into our VSHO proposal for further throughput gains. In addition to the VSHO techniques outlined in this paper, we also analyze other candidate techniques available in the Third Generation Partnership Project Long-Term Evolution (3GPP-LTE), such as cell-range expansion (CRE) and joint processing, to present a unified view of interference management options available in HetNets. [ABSTRACT FROM PUBLISHER]

Orthogonal frequency-division multiplexing (OFDM) is a promising technology for communication systems. This paper investigates the impacts of unknown noise variance on the popular spectrum sensing scheme, i.e., energy detection, for OFDM cognitive radios over multipath fading channels. To study the effects of unknown parameters on the energy detector, a new maximum-likelihood estimation of noise and signal powers employing the cyclic prefix of OFDM is presented in this paper. The mean values and Cram $\acute{\text{e}}$ r–Rao lower bounds of the estimation are obtained. Furthermore, the performances of the energy detector for both hypotheses, i.e., false-alarm rate and detection probability, under the influence of unknown noise variance are validated by both simulation and analytical results. The assessment on the required number of samples for the proposed energy detector is conducted, which indicates that an amount of 40–50% samples can be saved compared to the conventional energy detector. [ABSTRACT FROM AUTHOR]

Mitigation of interference among adjacent radio systems is a topic of growing interest as the spectrum occupation increases. Site-shielding techniques appear as a method of improving millimeter-wave wireless communication system design, allowing frequency reuse and reducing cochannel interference. The viability of applying such techniques to systems operating in frequency bands around 40 GHz is the aim of this paper. Several propagation mechanisms are experimentally studied, including transmission across building obstacles, depolarization, reflection, and diffraction. The performance of some theoretical models of the different scattering mechanisms has been compared with measurement results. The measuring and processing procedures have also been improved. Values of the dielectric parameters of the materials in this frequency band have been obtained and are given in this paper. The attenuation results indicate that various materials, such as mortar, brick, and concrete walls, that present large values of attenuation in decibels per centimeter, can be used to shield base stations, reducing the frequency reuse distance in radio cellular networks. It can also be concluded that there is a significant diffracted field in the shadow region of brick corners. [ABSTRACT FROM AUTHOR]

In this paper, we consider decode-and-forward (DF) relaying of the data of a multiple-antenna-based source Earth station, via a single-antenna-based satellite, to a multiple-antenna-based destination Earth station. The source uses beamforming for transmission of the data, and the destination utilizes the maximal ratio combining for demodulating the transmitted signal. The uplink and downlink satellite channels are assumed to be shadowed-Rician (SR) fading. First, we consider independent and identically distributed SR fading and derive the closed-form expressions of the approximate bit error rate (BER) and probability of outage for the considered scheme. By using the BER expression, the analytical diversity order of the scheme is obtained. It is deduced on the basis of the diversity order analysis that the diversity of the considered DF scheme linearly depends upon the minimum number of antennas at the source and destination nodes. Next, we consider correlated SR fading links and derive power-series-based expression of the approximate BER of the DF satellite relay system. For the correlated SR fading, the diversity order is analytically obtained; it is shown by analysis and simulation that the diversity order of the scheme with correlated channels does not depend upon the antenna correlation matrices of the source and destination nodes. [ABSTRACT FROM PUBLISHER]

The objective of this paper is to design radio resource management policies for supporting the effective delivery of multicast service in Long-Term Evolution Advanced (LTE-A) systems. Specifically, we propose multicast subgrouping-based solutions to maximize the system efficiency in terms of throughput under the constraints that 1) all user equipment devices are served and that 2) fairness among the activated multicast subgroups is guaranteed to avoid users' dissatisfaction. These results are obtained by modeling the multicast subgroup formation problem through a bargaining game. Moreover, an algorithm, which achieves the optimal fairness–efficiency tradeoff, is proposed to support the system in selecting the most appropriate solution in terms of 1) subgroups activated over each system carrier and 2) resource allocated to them. [ABSTRACT FROM PUBLISHER]

Customer churn as a common but extremely harmful phenomenon haunts service operators in telecommunications industry for a long time. Discriminating customers prone to churning in the early stage and taking precaution measures can mitigate customer churn effectively. Unlike previous works which mainly considered the inter-operator customer churn, we focus on a new problem of intra-operator customer churn, that is, customers abandon their fourth generation (4G) mobile communication services and switch to third generation/second generation (3G/2G). Due to quite different mechanisms and causes, previous studies cannot tackle this new problem well. In this paper, we propose a novel profit maximizing framework to solve this special customer churn problem. Specifically, we first build a profit maximizing classifier to predict whether a customer is prone to churn or not, in which profitable customers have more probability to be classified correctly. Then, we describe and quantify the switching behaviors of 4G customers by introducing a notion of switching score. Finally, we investigate relations between operators and customers, finding that some features of 4G service plans provided by operators indeed affect switching behaviors of 4G customers remarkably. This provides insight into reasonable design of 4G service plans for operators in the future. Our framework uncovers the root causes of intra-operator customer churn and solve the problem well. Experimental results based on real data demonstrate the effectiveness of our framework. [ABSTRACT FROM AUTHOR]

In this paper, a novel nonlinear signal processing technology, which is denoted as the polarity-invariant square law (PISL) algorithm, is proposed to compensate nonlinear distortions caused by monobit digitization and to mitigate the performance degradation of impulse radio ultra wideband (IR-UWB) receivers employing monobit analog-to-digital converters (ADCs). An analytical framework based on characteristic functions has been developed to evaluate bit error rates of monobit transmitted-reference (TR) receivers and performance improvement offered by the PISL algorithm. Both theoretical analysis and simulations show that by employing the PISL algorithm, the monobit weighted TR (MWTR) receivers can achieve a bit-error-rate performance that is more than 10 dB over the direct-reference algorithm and is less than 1.5 dB away from the performance bound of the MWTR receivers in intravehicle UWB channels. Furthermore, the MWTR receiver employing the PISL algorithm is insensitive to a correlation interval; this feature not only reduces complexity of the receiver design but also ensures performance robustness over various multipath channels. Therefore, the PISL algorithm can be considered an enabling technology for the monobit IR-UWB receivers that demand high performance, lower power consumption, and low complexity. [ABSTRACT FROM PUBLISHER]

Spectrum leasing via cooperation refers to the possibility of primary users to lease a portion of their spectral resources to secondary users in exchange for cooperation. This paper proposes a novel application of this concept, where in the presence of an eavesdropper, the secondary cooperation aims at improving the secrecy of the primary network. It does this by creating more interference to the eavesdropper than to the primary receiver. To generate the interference in a positive way, this paper studies an optimal design of a beamformer at the secondary transmitter with multiple antennas. The design maximizes the secrecy rate of the primary network while satisfying a required rate for the secondary network. Moreover, we investigate two scenarios that are contingent on how the eavesdropper operates: 1) The eavesdropper treats the interference by the secondary transmission as additive noise [single-user decoding (SD)]; and 2) the eavesdropper tries to decode and remove the secondary signal [joint decoding (JD)]. Numerical results confirm that, for a wide range of required secondary-rate constraints, the proposed spectrum-leasing strategy increases the secrecy rate of the primary network. [ABSTRACT FROM PUBLISHER]

Batched sparse (BATS) code is a class of temporal network code that achieves near-optimal tradeoff between network throughput and coding length for multi-hop erasure networks. However, the performance of the traditional BATS code degrades dramatically when the designed degree distribution does not match the actual channel condition. In this paper, we first prove that a universal degree distribution that asymptotically achieves the optimal rate for all channel rank distributions does not exist for BATS code with batch size greater than one. We then propose a quasi-universal BATS (QU-BATS) code that achieves near-optimalperformance for a range of channel conditions. This makes it suitable for use in scenarios where the end-to-end channel rank distribution is not fixed or not exactly known, e.g., in multicast or wireless transmission. In the proposed QU-BATS coding scheme, multiple degree distributions are designed, and the coded packets are generated according to different degree distributions at different transmission stages. Simulation results show that the proposed QU-BATS code strictly outperforms the fountain code and the traditional BATS codes for multihop data streaming over uncertain or time-varying network links, with lower decoding complexity. [ABSTRACT FROM PUBLISHER]

Ambient backscatter, an emerging green communication technology, has aroused great interest from both academia and industry. One open problem for ambient backscatter communication (AmBC) systems is channel estimation for a massive-antenna reader. In this paper, we focus on a channel estimation problem in AmBC systems with a uniform linear array at the reader consisting of large number of antennas. We first design a two-step method to jointly estimate channel gains and direction of arrivals (DoAs), and then refine the estimates through angular rotation. Additionally, Cramér–Rao lower bounds are derived for both the modulus of the channel gain and the DoA estimates. Simulations are then provided to validate the analysis, and to show the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

Location management plays a central role in guaranteeing the effective operation of personal communication service (PCS) networks. In current PCS networks, a two-tier system of home location register (HLR) and visitor location register (VLR) databases is commonly used for location management. To improve the performance of PCS networks, several dynamic location management schemes have been proposed. Among the existing dynamic schemes, the movement-based location management may be the most practical due to its effectiveness and easy implementation under the framework of current PCS networks. To implement location management in PCS networks, cost analysis is a crucial aspect. However, most of the existing cost analyses for the movement-based scheme are too simple and not available for PCS networks with the HLR/VLR architecture. One reason for this is the complexity and the difficulty associated with the problem. Li et al. and Rodríguez-Dagnino et al. challenged this task by considering the HLR/VLR architecture. However, the cost analysis developed by Li et a!. was carried out under the assumption that the cell and location area (LA) residence times are exponentially distributed. Rodríguez-Dagnino et al. furthered Li et al.'s work by assuming that the LA residence time follows a hyper- exponential distribution and that the cell residence time is generally distributed. However, Li et al. and Rodríguez-Dagnino et a!. failed to consider VLR location updates that are caused by terminal movements between LAs. In this paper, we relax the restrictions imposed on the distributions of the cell and LA residence times and propose an analytical model to study the movement- based scheme with HLR/VLR architecture. The issue of VLR location updates that are caused by movements between LAs is addressed carefully and successfully. Analytical formulas for the costs of HLR and VLR location updates are derived using a unified approach. Numerical study suggests that the total cost is a convex function of the movement threshold and is sensitive to the variances of the cell and LA residence times. The result presented in this paper can serve as a guideline for the system design and the implementation of the movement-based scheme for PCS networks. [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]

This paper describes several small printed circuit board planar antennas that can be integrated with amplifiers for short-range vehicle wireless communication. The antennas are designed for the 315-MHz frequency band, which is commonly used for control and security devices in the USA and Canada. Each antenna has dimensions of 50 × 70 mm (much less than the free-space wavelength λ = 0.95 m) and is implemented on FR-4 dielectric substrate. These investigated antennas were compared with respect to input impedance, radiation resistance, radiation efficiency, directivity, directionality, bandwidth, matching system complexity, and gain. This paper also includes experimental verification of the final antenna design in the vehicle. It is shown that the antenna diversity method can increase communication range for remote keyless entry systems. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) is a key enabler for future paradigm-shifting communication technologies. In a cellular network, an RIS can be used to simultaneously assist the communication of a cellular link and transmit additional data for various Internet of Things (IoT) applications. This coincides with the concept of symbiotic radio (SR). In this paper, we investigate this RIS-assisted SR system. We introduce the new idea of symbiotic modulation: the modulation constellation design allows a receiver to simultaneously detect the data transmitted in the RIS-assisted cellular link and the additional IoT data transmitted by the RIS. We propose three specific modulation schemes all having the feature of receive-antenna index modulation, and hence, called symbiotic spatial modulation (SSM). The first scheme is a coherent SSM scheme with a star-QAM (quadrature amplitude modulation) constellation. Its detection performance is analyzed using either an optimal maximum likelihood detector or a suboptimal successive greedy detector. We then extend the design to two noncoherent SSM schemes and analytically derive their detection performances as well. Simulation results corroborate the analysis and illustrate good detection performance of the proposed SSM schemes for both the cellular and IoT data transmissions in the considered SR system. [ABSTRACT FROM AUTHOR]

Tail-biting codes are efficient for short data packets by eliminating the rate loss in conventional known-tail codes. The existing maximum-likelihood (ML) decoding algorithms, such as the Viterbi heuristic ML decoder (VH ML decoder) and the trap detection-based ML decoder (TD-ML decoder), have to visit each state of the tail-biting trellis at least once. The decoding efficiency of these decoding algorithms can be improved further. In this paper, we propose an ML decoder for tail-biting trellises with bounded searches (BSs). We first perform a unidirectional bounded searching algorithm to estimate the lower bound of path metric of tail-biting paths on each sub-tail-biting trellis and exclude impossible candidates of starting states. In the second phase, a bidirectional searching algorithm is applied to find the ML tail-biting (MLTB) path on the survivor sub-tail-biting trellises. The proposed algorithm exhibits lower decoding complexity floor than other existing algorithms on tail-biting trellis. Simulation results for the (24, 12, 8) Golay codes and Eb/N0=\5\ \dB show that, for the proposed ML decoder, the average number of visited states per decoded bit is less than 2, whereas the average number of visited states per decoded bit is more than 12 for the VH ML decoder. [ABSTRACT FROM PUBLISHER]

It is expected that cognitive machine-to-machine (M2M) communications in smart grid networks will be indispensable in the near future. In this paper, after discussing the motivation of cognitive M2M communications in a smart grid network, we design a cognitive medium access control (MAC) protocol, keeping in view the unique features of M2M devices and smart grid communication requirements. We propose the use of packet reservation multiple access (PRMA), carry out its feasibility study, and adapt and significantly enhance it with modifications particularly tailored for M2M environments. The proposed protocol is centralized in nature and utilizes a specialized frame structure for supporting the coexistence of the cognitive M2M network with the primary network. This frame structure is further optimized, considering different tradeoffs pertaining to primary network protection and the utility of a secondary M2M network. Performance evaluation is carried out by analytical modeling and simulation studies. We also present a case study for application of the proposed protocol in advanced metering infrastructure (AMI) networks under the dynamics of power systems. [ABSTRACT FROM PUBLISHER]

In wireless sensor networks (WSNs), the network lifetime (NL) is a crucial metric since the sensor nodes usually rely on limited energy supply. In this paper, we consider the joint optimal design of the physical, medium access control (MAC), and network layers to maximize the NL of the energy-constrained WSN. The problem of NL maximization can be formulated as a nonlinear optimization problem encompassing the routing flow, link scheduling, transmission rate, and power allocation operations for all active time slots (TSs). The resultant nonconvex rate constraint is relaxed by employing an approximation of the signal-to-interference-plus-noise ratio (SINR), which transforms the problem to a convex one. Hence, the resultant dual problem may be solved to obtain the optimal solution to the relaxed problem with a zero duality gap. Therefore, the problem is formulated in its Lagrangian form, and the Karush–Kuhn–Tucker (KKT) optimality conditions are employed for deriving analytical expressions of the globally optimal transmission rate and power allocation variables for the network topology considered. The nonlinear Gauss–Seidel algorithm is adopted for iteratively updating the rate and power allocation variables using these expressions until convergence is attained. Furthermore, the gradient method is applied for updating the dual variables in each iteration. Using this approach, the maximum NL, the energy dissipation per node, the average transmission power per link, and the lifetime of all nodes in the network are evaluated for a given source rate and fixed link schedule under different channel conditions. [ABSTRACT FROM PUBLISHER]

Cooperative spectrum sensing (CSS) is considered as a powerful approach to improve the utilization of scarce spectrum resources. However, CSS assumes that all secondary users (SU) always are honest, thus offering opportunities for attackers to launch spectrum sensing data falsification (SSDF) attack. To combat such threat, recent efforts have been made to trust mechanism. In this paper, we argue that powering CSS with trust mechanism is not enough. A vulnerability for trust mechanism is found, that is, the feedback data from initiator SUs are generally unchecked. Such feedback data corresponding to the spectrum status of primary users can be exploited by attackers to disturb trust mechanism in a collusive manner. Especially, collusive false feedback (CFF) attackers would form a clique to help each other. One of CFF attackers can disguise as an initiator SU who sends the feedback in accordance with the sensing data of their conspirators who play the role of cooperating SUs, resulting in promoting their conspirators’ sensing trust quickly. With high sensing trust, attackers can avoid the detection of trust mechanism and, hence, launch SSDF attack (fake sensing data) more easily. We conduct an in-depth investigation on CFF attack and propose a two-level defense scheme called FeedGuard from the design ideas of feedback trust and I-C frequency correlation analysis. Simulation results show that the FeedGuard scheme can enhance the accuracy of sensing trust evaluation, thus successfully reducing the power of CFF attack against CSS. [ABSTRACT FROM AUTHOR]

Linear frequency modulated continuous wave (LFMCW) signals have been widely used in target detection and localization, thanks to their good detection sensitivity and high range resolution. However, estimation of the angle of arrival (AOA) of the LFMCW signal reflected from each target in a multitarget environment is still quite limited at present. In this paper, we propose a novel AOA estimation framework in which one transmitter antenna and two receiver antennas are employed to transmit a wideband LFMCW signal and receive the signals reflected from different targets, respectively. The signals received at two receiver antennas are processed in three steps. First, each of them is demodulated by mixing with the transmitted signal to transform the wideband nonstationary signal into superposition of a series of single-tone signals. Second, signals received at each receiver antenna from different targets are separated using bandpass filtering. Third, the corresponding AOA of each target is estimated using the phase difference between two receiver antennas. Different from the traditional subspace-based methods, the number of targets is not limited by the number of receiver antennas. The theoretical analysis and simulation results show that the proposed algorithm can achieve accurate AOA estimation for multiple targets even at a low signal to noise ratio. [ABSTRACT FROM AUTHOR]

Anticipative driving of vehicles, considering the microscopic dynamics of the preceding traffic, can bring great improvement in the traffic flows in a connected vehicle environment (CVE), where 100% vehicles frequently share their states using vehicle-to-vehicle communication technology. This paper addresses a partially CVE, where unconnected (manually driven) vehicles are mixed in the traffic, and proposes a novel method of comprehending traffic conditions that can be used for realizing highly anticipative driving. More specifically, we refer to anticipative driving as the predictive control of a host vehicle considering its preceding traffic conditions in an extended view. For enhanced perception of the traffic conditions on the road, a road-speed profile is proposed that concisely describes the mean speed in each small segment or cell of the road by effectively extracting information from traffic big data, i.e., broadcasted data from all surrounding vehicles to the host vehicle. This process of dynamically approximating the road-speed profile is performed in two steps. First, a conditional persistence prediction model is proposed to estimate the future states of the connected vehicles. Such predicted states can sufficiently compensate missing data from any unconnected vehicles. Second, the predicted time, position, and speed of the vehicles are then mapped onto the road cells, and subsequently, the corresponding cell speed is tuned by employing the weighted-moving average technique. Accuracy of both the persistence prediction model and the road-speed profile are empirically evaluated for different penetration of the connected vehicles. Finally, an anticipative driving scheme in a model predictive control framework is developed by incorporating the proposed road-speed profile, and performance of the anticipative driving is compared with the existing scheme that needs the CVE. [ABSTRACT FROM AUTHOR]

In heterogeneous networks (HetNets), load balancing among different tiers can be effectively achieved by a biased user association scheme with which each user chooses to associate with one base station (BS) based on the biased received power. In contrast to previous studies, where a BS always has packets to transmit, we assume in this paper that incoming packets intended for all the associated users form a queue in the BS. In order to find the delay limit of the network to support real-time service, we focus on the delay optimization problem by properly tuning the biasing factor of each tier. By adopting a thinned Poisson point process model to characterize the locations of BSs in the busy state, an explicit expression of the average traffic intensity of each tier is obtained. On that basis, an optimization problem is formulated to minimize a lower bound of the network mean queuing delay. By showing that the optimization problem is convex, the optimal biasing factor of each tier can be obtained numerically. When the mean packet arrival rate of each user is small, a closed-form solution is derived. The simulation results demonstrate that the network queuing performance can be significantly improved by properly tuning the biasing factor. It is further shown that the network mean queuing delay might be improved at the cost of a deterioration of the network signal-to-interference ratio coverage, which indicates a performance tradeoff between real-time and non-real-time traffic in HetNets. [ABSTRACT FROM AUTHOR]

In this paper, energy-efficient power control for small cells underlaying a macrocellular network is investigated. We formulate the power control problem in self-organizing small-cell networks as a noncooperative game and propose a distributed energy-efficient power control scheme, which allows the small base stations (SBSs) to take individual decisions for attaining the Nash equilibrium (NE) with minimum information exchange. In particular, in the noncooperative power control game, a nonconvex optimization problem is formulated for each SBS to maximize their energy efficiency (EE). By exploiting the properties of parameter-free fractional programming and the concept of perspective function, the nonconvex optimization problem for each SBS is transformed into an equivalent constrained convex optimization problem. Then, the constrained convex optimization problem is converted into an unconstrained convex optimization problem by exploiting the mixed penalty function method. The inequality constraints are eliminated by introducing the logarithmic barrier functions, and the equality constraint is eliminated by introducing the quadratic penalty function. We also theoretically show the existence and the uniqueness of the NE in the noncooperative power control game. Simulation results show remarkable improvements in terms of EE by using the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, we consider a cooperative cognitive radio relay network (CCRRN), in which there is a pair of primary transmitter (PT) and primary receiver (PR) with each having a single antenna, a secondary transmitter (ST) equipped with two antennas and a secondary receiver (SR) having a single antenna. We assume that ST operates in a half-duplex mode with an amplify-and-forward cooperative transmission scheme adopted. For such a system, a novel transmission scheme for CCRRN based on uniquely-factorable constellation pair is proposed, which enables ST to transmit its own information to SR without knowing its channel links to PR and SR while assisting PT transmission. It is shown that one of the significant advantages of our proposed new scheme is that, in a noise-free case, PR and SR are able to decode their own signals uniquely and that, in a Gaussian noise case, they are still able to reliably decode their own signals with full diversity. In addition, a tight upper bound of average pairwise error probability for the maximum-likelihood detector is derived, showing that full diversity is achieved. With this, an optimal power allocation strategy is proposed that minimizes the worst-case upper bound. [ABSTRACT FROM AUTHOR]

In this paper, we study the impact of correlated fading on the secrecy performance of multiple decode-and-forward (DF) relaying with outdated relay selection. It is assumed that the information transmission, assisted by $N$ DF relays from the source to the destination, can be overheard by an eavesdropper. Particularly, we consider the realistic scenario where the eavesdropper's and the main channels are correlated. In order to enhance the network security, the best relay is selected among $N$ available DF relays to assist the secure transmission. Due to the time-varying channel environments, we note that the selected relay may be outdated. In order to study the impact of both channel correlation and outdated relay selection on the secrecy performance, we first derive an analytical expression for the secrecy outage probability (SOP). Also, we derive the asymptotic expression for the SOP in the high main-to-eavesdropper ratio regime. Numerical results are provided to demonstrate the correctness of our analytical expressions. [ABSTRACT FROM AUTHOR]

While underwater communications have been investigated for decades, existing solutions still have difficulties in establishing reliable and low-delay links among small-size devices. The magnetic induction (MI) communication is a promising solution due to its advantages in low propagation delay and less susceptibility to surrounding environments. To date, existing MI models cannot characterize broadband and complex underwater MI channels, especially in shallow and lossy water, which significantly underestimates the underwater MI's performance. Moreover, the unpredictable polarization loss of coil antenna that makes MI unreliable has not been modeled and addressed. To this end, this paper presents a broadband channel model for underwater MI communication in complex environments. Compared with existing underwater MI models, the developed model can characterize 1) the underwater magnetic field propagation at any point in the 3-D space between the water surface and water floor, 2) both the near and far fields of all feasible underwater signal bands, 3) the impacts of lossy underwater medium on not only the propagation path but on the MI antenna itself as well, and 4) the arbitrarily orientated tri-directional coil antenna that can eliminate the MI antenna's susceptibility to orientation changes. The developed model is validated through COMSOL-multiphysics simulations and in-lab experiments. [ABSTRACT FROM AUTHOR]

In existing channel estimators for amplify-and-forward relaying, pilots are often sent from the relay to the destination which consumes the relay's own energy. This limits the relay's participation in the network. In this paper, several moment-based channel estimators for amplify-and-forward relaying are proposed that harvest energy from the source and using the harvested energy to send pilots to the destination for channel estimation. Both time-switching and power-splitting strategies are considered. Numerical results show that the two schemes that perform channel estimation only at the destination have worst performances than the two schemes that perform channel estimation at both the relay and the destination. They also show that the bit error rate performances of all schemes are close to the perfect case when exact knowledge of the channel state information is available such that there is no channel estimation error in the demodulation. The assumption that the two schemes only perform channel estimation at the destination makes them simpler, as they do not require channel estimation at the relay or feed the channel estimate back to the destination. [ABSTRACT FROM AUTHOR]

To achieve the potential in providing high throughput for cellular networks by device-to-device (D2D) communications, the interference among D2D links should be carefully managed. In this paper, we propose an opportunistic cooperation strategy for D2D transmission by exploiting the caching capability at the users to control the interference among D2D links. We consider overlay inband D2D, divide the D2D users into clusters, and assign different frequency bands to cooperative and nonco operative D2D links. To provide high opportunity for cooperative transmission, we introduce a caching policy. To maximize the network throughput, we jointly optimize the cluster size and bandwidth allocation, where the closed-form expression of the bandwidth allocation factor is obtained. Simulation results demonstrate that the proposed strategy can provide 400%–500% throughput gain over traditional D2D communications when the content popularity distribution is skewed and can provide 60%–80% gain even when the content popularity distribution is uniform. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communications has gradually become a promising technique to support wireless peer-to-peer services and enhance the overall spectrum utilization. In the meantime, the full-duplex communication technique has also attracted significant research interest recently. In this paper, for the first time, we employ the D2D communication concept in a full-duplex cellular network. In such a scenario, the user equipments (UEs) are allowed to communicate between each other by reusing the spectrum resources of cellular uplinks and downlinks. However, this D2D underlaying full-duplex cellular scenario poses a new challenge for interference management. The complicated UE-to-UE interference among cellular links and D2D links self-interference at the base station can critically affect network performance. Therefore, we investigate the joint resource block assignment and transmit power allocation problem, in order to optimize the network performance and spectrum utilization. Furthermore, we use graph theory to model the investigated scenario and propose a novel graph coloring based resource sharing scheme to solve the joint optimization problem effectively with acceptable complexity. The performance of our scheme is evaluated through Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

Recently, a new mutual information preserving quantize-and-forward (MIP-QF) is proposed for the half-duplex relay channel, where the relay node does not need to decode the source signal correctly. In this paper, a new MIP-QF upper bound on the achievable rate of the half-duplex relay channel is proposed, which is shown to be lying between the compress-and-forward (CF) bound and the cut-set bound. For the half-duplex additive white Gaussian noise (AWGN) relay channel, the specific MIP-QF bound and the optimal duplex ratios of the MIP-QF upper bound and the MMSE-CF bound are also derived. In addition, we also show that the decode-and-forward (DF) bound can exceed the MIP-QF bound in some special cases that the relay is close to the source and far away from the destination. The validity and accuracy of the proposed theoretical results are verified by numerical results under the half-duplex AWGN relay channel. [ABSTRACT FROM AUTHOR]

In interference channels, channel state information (CSI) can be exploited to reduce the interference signal dimensions, and thus, achieve the optimal capacity scaling, i.e., degrees of freedom, promised by the interference alignment technique. However, imperfect CSI, due to channel estimation error, imperfect CSI feedback and time selectivity of the channel, lead to a performance loss. In this paper, we propose a novel limited feedback algorithm for single-input single-output interference alignment in time-variant channels. The feedback algorithm encodes the channel evolution in a small number of subspace coefficients, which allow for reduced-rank channel prediction to compensate for the channel estimation error due to time selectivity of the fading process and feedback delay. An upper bound for the rate loss caused by feedback quantization and channel prediction is derived. Based on this bound, we develop a dimension switching algorithm for the reduced-rank predictor to find the best tradeoff between quantization and prediction error. Besides, we characterize the scaling of the required number of feedback bits in order to decouple the rate loss due to channel quantization from the transmit power. Simulation results show that a rate gain over the traditional nonpredictive feedback strategy can be secured and a $60\%$ higher rate is achieved at 20-dB signal-to-noise ratio with moderatesxst mobility. [ABSTRACT FROM PUBLISHER]

In this paper, we study the uplink in a single-cell massive multiple-input–multiple-output system. The base station (BS) is equipped with three antenna arrays, each covering one third of the cell area. Each antenna array comprises a large yet finite number of antennas. The single-antenna users are randomly and uniformly distributed in the cell, transmitting to the BS utilizing full channel inversion power control. All users experience Rician fading. Receiver maximum-ratio-combining is performed at the BS. Under such a setting, we focus on one cell sector and analyze the intrasector interference in a realistic situation where the number of BS antennas is not extremely large compared with the user number. In particular, we show that, due to the line-of-sight (LoS) component of the channel, the interference is partially determined by the angles of arrival of the signals. We approximate the LoS component interference by a Beta mixture. The interference in Rician fading is then modeled as a noncentral chi-square distribution with a random noncentrality parameter, corresponding to the LoS component. The approximate interference distribution can be used to compute signal-to-interference-ratio-dependent metrics such as outage probability and average throughput. [ABSTRACT FROM AUTHOR]

Information and power transfer in mobile relay networks have recently emerged simultaneously, where the relay can harvest the radio frequency (RF) energy and then use this energy for data forwarding and system operation. Most of the previous works do not consider that the relay may have its own objectives, such as using the harvested energy for its own transmission instead of maximizing transmission of the network. Therefore, in this paper, we propose a Nash bargaining approach to balance the information transmission efficiency of source–destination pairs and the harvested energy of the relay in a wireless powered relay network with multiple source–destination pairs and one relay. We analyze and prove that the Nash bargaining problem has several desirable properties such as the discreteness and quasi-concavity, when it is decomposed into three subproblems: the energy transmission power optimization, the power control for data transmission, and the time division between energy transmission and data transmission. Based on the theoretical analysis, we propose an alternating power control and time-division algorithm to find a suboptimal solution. Simulation results clearly show and demonstrate the properties of the problem and the convergence of our algorithm. [ABSTRACT FROM AUTHOR]

We consider the point-to-point adaptive transmission of scalable video coding streams over a fading channel in energy harvesting (EH) aided communication systems, where the transmitter is equipped with an EH device and a rechargeable battery. The aim of this paper is to enable the transmitter having the ability of adaptively adjusting the number of video layers to be transmitted according to the available energy. Since the depletion of the energy in the battery acts as a trigger for the interruption of the video transmission, we define the energy starvation probability for equivalently characterizing a quality-of-experience (QoE) metric. We formulate the problem of EH-aided video transmission as a constrained optimization problem, maximizing the number of video layers for transmission while keeping the energy starvation probability below a threshold. Classic large deviation theory is invoked for estimating the energy starvation probability from online measurements. Consequently, our dynamic layer switch algorithm operates with no prior statistical knowledge of both the EH process and of the channel quality. Furthermore, the technique of perturbation analysis that constructs a perturbed sample path from an original sample path is invoked for improving the performance of the proposed method. Our experimental results verify that the algorithms proposed have the adaptation capability to accommodate both the energy-dynamics and the channel-dynamics for improving the video quality subject to an unobjectionable level of transmission interruption rate. [ABSTRACT FROM AUTHOR]

This paper investigates the energy-efficient traffic splitting for time-varying wireless networks, which have been configured with multiple radio access technologies (multi-RATs). A single stream of the media content is split into multiple segments, which could be transmitted over multiple RATs simultaneously so that the complementary advantages of different RATs can be exploited. To address this problem, we formulate the traffic splitting as a long-term energy efficiency (EE) maximization problem with respect to the time-varying channel state information (CSI). An equivalent transformation method is proposed to convert the long-term nonconvex EE maximization problem into a concave optimization. To reduce the computational complexity, we develop a dynamic traffic splitting (DTS) algorithm, which iterates only one time when the network state changes. Then, we use the definition of tracking error to describe the difference between the DTS and the target optimal traffic splitting solution. After that, an adaptive-compensation traffic splitting (ACTS) algorithm is proposed to offset the tracking error so as to enhance the EE performance. More specifically, we give a sufficient condition for significantly eliminating the tracking errors of the ACTS algorithm. Simulation results show that the proposed ACTS algorithm obtains the EE performance comparable with the optimal solution at the overhead of only a single iteration at each timeslot of the network state acquisition. [ABSTRACT FROM AUTHOR]

As the cellular networks continue to progress between generations, the expectations of 5G systems are planned toward high-capacity communication links that can provide users access to numerous types of applications (e.g., augmented reality and holographic multimedia streaming). The demand for higher bandwidth has led the research community to investigate unexplored frequency spectrums, such as the terahertz band for 5G. However, this particular spectrum is strived with numerous challenges, which includes the need for line-of-sight (LoS) links as reflections will deflect the waves as well as molecular absorption that can affect the signal strength. This is further amplified when a high quality of service has to be maintained over infrastructure that supports mobility, as users (or groups of users) migrate between locations, requiring frequent handover for roaming. In this paper, the concept of mirror-assisted wireless coverage is introduced, where smart antennas are utilized with dielectric mirrors that act as reflectors for the terahertz waves. The objective is to utilize information such as the user's location and to direct the reflective beam toward the highest concentration of users. A multiray model is presented in order to develop the propagation models for both indoor and outdoor scenarios in order to validate the proposed use of the reflectors. An office and a pedestrian-walking scenarios are used for indoor and outdoor scenarios, respectively. The results from the simulation work show an improvement with the usage of mirror-assisted wireless coverage, improving the overall capacity, the received power, the path loss, and the probability of LoS. [ABSTRACT FROM PUBLISHER]

Machine-to-machine (M2M) communications have attracted great attention from both academia and industry. In this paper, with recent advances in wireless network virtualization and software-defined networking (SDN), we propose a novel framework for M2M communications in software-defined cellular networks with wireless network virtualization. In the proposed framework, according to different functions and quality-of-service (QoS) requirements of machine-type communication devices, a hypervisor enables the virtualization of the physical M2M network, which is abstracted and sliced into multiple virtual M2M networks. In addition, we develop a decision-theoretic approach to optimize the random access process of M2M communications. Furthermore, we develop a feedback and control loop to dynamically adjust the number of resource blocks that are used in the random access phase in a virtual M2M network by the SDN controller. Extensive simulation results with different system parameters are presented to show the performance of the proposed scheme. [ABSTRACT FROM PUBLISHER]

Traditional approaches in the analysis of downlink systems decouple the precoding and the channel estimation problems. However, in cellular systems with mobile users, these two problems are, in fact, tightly coupled. In this paper, this coupling is explicitly studied by accounting for the channel training overhead and estimation error while determining the overall system throughput. This paper studies the problem of utilizing imperfect channel estimates for efficient linear precoding and user selection. It presents precoding methods that take into account the degree of channel estimation error. Information-theoretic lower and upper bounds are derived to evaluate the performance of these precoding methods. In typical scenarios, these bounds are close. [ABSTRACT FROM PUBLISHER]

This paper reexamines the problem of frequency offset estimation and signal detection of the Bell Laboratories Layered Space-Time (BLAST) scheme. Today, typical multiple-input-multiple-output (MIMO) receivers separately execute these two steps, but in succession. In this paper, we propose a joint frequency offset estimator and signal detector (JFESD). In our scheme, the frequency offset can be well compensated by utilizing the intermediate detector results. Our detector is evolved from conventional zero-forcing BLAST detectors. It is extendable to situations where the receive dimension is lower than the transmit dimension with a marginal increase of computational complexity. We evaluate the bit error probability and mean square error performance of the JFESD and compare them with other schemes. - [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 considers a scheduling problem for multi-user transmissions over the downlink of a time-slotted cellular data network. For such a network, opportunistic scheduling exploits the time-varying radio channel and improves network performance. This paper presents a new scheduling solution that maximizes the aggregate user performance subject to certain minimum and maximum performance constraints. By constraining the performance experienced by individual users, who share a common radio downlink, to some upper bounds, it is possible to provide the system operator with a better control of radio resource allocations and service differentiation among different classes of users. The proposed solution, which is referred to as Throughput Constrained Opportunistic Scheduling (TCOS), offers better service differentiation among different classes of users than the existing opportunistic scheduling algorithms with only minimum performance constraints. For ideal memoryless fading channels, TCOS provides performance comparable with an existing scheme with minimum and maximum performance constraints. For realistic fading channels with memory, TCOS significantly improves system performance due to its ability to trade off feasibility with throughput. Extensive simulation results demonstrate the improved system performance and effective service differentiation of the proposed solution under realistic channel conditions. [ABSTRACT FROM AUTHOR]

This paper 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]

On the multiantenna broadcast channel, the spatial degrees of freedom support simultaneous transmission to multiple users. The optimal multiuser transmission, which is known as dirty paper coding, is not directly realizable. Moreover, close-to-optimal solutions such as Tomlinson-Harashima precoding are sensitive to channel state information (CSI) inaccuracy. This paper considers a more practical design called per user unitary and rate control (PU2RC), which has been proposed for emerging cellular standards. PU2RC supports multiuser simultaneous transmission, enables limited feedback, and is capable of exploiting multiuser diversity. Its key feature is an orthogonal beamforming (or precoding) constraint, where each user selects a beamformer (or precoder) from a codebook of multiple orthonormal bases. In this paper, the asymptotic throughput scaling laws for PU2RC with a large user pool are derived for different regimes of the signal-to-noise ratio (SNR). In the multiuser interference-limited regime, the throughput of PU2RC is shown to logarithmically scale with the number of users. In the normal SNR and noise-limited regimes, the throughput is found to scale double logarithmically with the number of users and linearly with the number of antennas at the base station. In addition, numerical results show that PU2RC achieves higher throughput and is more robust against CSI quantization errors than the popular alternative of zeroforcing beamforming if the number of users is sufficiently large. [ABSTRACT FROM AUTHOR]

Targeting mobile vehicle communications, Dedicated Short Range Communications (DSRC) wireless technology has been widely used in Vehicular Ad-hoc Networks (VANETs). Though DSRC can provide reliable and low-latency communications for various VANET applications, the multi-channel operations standardized by IEEE 802.11p suffer from high contention on control channel, especially in dense traffic scenarios. Meanwhile, as a conventional wireless technology for VANET communications, WiFi is often underutilized when a vehicle is on road. In this paper, we propose an innovative approach that can effectively offload control frames from DSRC to WiFi when the control traffic is dense, resulting in significantly improved throughput of control traffic (about 28.7% under moderate traffic density in simulation). [ABSTRACT FROM AUTHOR]

The minimum mean square error combining (MMSEC) scheme performs best among various equalization and combining schemes for downlink multicarrier code-division multiple access (MC-CDMA) However, it is also the most computationally complex to realize as it involves the complex matrix inversion operation of a large matrix. In this paper, a new method is proposed to calculate the equalizer coefficient for MMSEC based on reduced-size matrices. It is shown that as long as the number of users is even, the matrix inversion size is reduced to at least Nc/2, where Nc is the number of subcarriers. [ABSTRACT FROM AUTHOR]

In this paper, we analyze transmission techniques for multiple-input-multiple-output (MIMO) systems from a link-layer perspective using frame error rate (FER), frame loss rate, and link throughput metrics. We introduce two new layered space-time coding variants adapted for transmission at the frame level in MIMO systems with no channel state information (CSI) at the transmitter. We analytically demonstrate that for moderate to high signal-to-noise ratios (SNRs), the average FER is lower when the frames are segmented into subframes sent from different antennas rather than transmitting each frame on separate antennas. When the CSI is available at the transmitter, we investigate a new transmission technique, which uses a diagonal precoder and a subchannel selection strategy to trade off the multiplexing gain with the FER to increase the link-level throughput. [ABSTRACT FROM AUTHOR]

This paper proposes to encode pilot bits together with information bits by using a systematic encoder and applying them to an iterative receiver, where channel estimation and decoding are iteratively performed. This paper then shows why and how the encoded pilot bits can give a positive gain over a conventional uncoded pilot system. Specifically, this paper considers an orthogonal frequency-division multiplexing system that is encoded by a low-density parity-check code under a frequency-selective fading channel and shows theoretical analysis as well as simulation results. [ABSTRACT FROM AUTHOR]