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The new Fifth generation (5G) of wireless communications and beyond 5G (B5G) networks are required to provide connectivity for massive number of devices at high speed and low latency. Within this context, non-orthogonal multiple access (NOMA) has been involved and emerged in recent research since it is considered as an enabling technology for 5G and B5G networks. NOMA allows several users to share the same resources of time and frequency, making it an excellent candidate to provide impressively large connectivity with high spectral efficiency. In this paper, we study the performance of NOMA systems assuming independent but not necessarily to be identical $N$ -Nakagami-m multipath fading channels. This channel model subsumes the double Nakagami-m, which was investigated in the context of intervehicular communications and keyhole multiple input multiple output systems, as special cases. To this end, we derive exact analytical and asymptotic expressions for the probability density function of the overall signal to noise ratio, system capacity, and the pairwise error probability (PEP) for each user. Numerical results are also provided herein to show the effects of fading parameters and number of users on the capacity and the PEP of each user. [ABSTRACT FROM AUTHOR]

The efficiency of link adaptation in wireless communications relies greatly on the accuracy of channel knowledge and transmission mode selection. In this paper, a novel deep learning based link adaptation framework is proposed for the orthogonal frequency-division multiplexing (OFDM) systems with compressed-sensing-assisted index modulation, termed as OFDM-CSIM, communicating over millimeter-wave (mmWave) channels. To achieve link adaptation, a novel multi-layer sparse Bayesian learning (SBL) algorithm is proposed for accurately and instantaneously providing the required channel state information. Meanwhile, a deep neural networks (DNN)-assisted adaptive modulation algorithm is proposed to choose the best possible transmission mode to maximize the achievable throughput. Simulation results show that the proposed multi-layer SBL algorithm enables more accurate channel estimation than the conventional techniques. The DNN-based adaptive modulator is capable of achieving a higher throughput than the learning-assisted solution based on the $k$ nearest neighbor ($k$ -NN) algorithm, and also the classic average signal-to-noise ratio (SNR)-based solutions. Moreover, analysis shows that both the multi-layer SBL algorithm and the DNN-assisted adaptive modulator achieve better performance than their respective conventional counterparts while at a significantly lower computational complexity cost. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of vertical underwater wireless optical communication (UWOC) systems in the presence of air bubbles and temperature gradients. We consider a generalized UWOC channel model that contains $N$ layers, each having the same distribution but with different parameters to consider the vertically inhomogeneous nature of the underwater environment. To capture the effects of air bubbles and temperature gradients on channel statistics, we model each layer with a mixture exponential-generalized Gamma distribution. A closed-form probability density function (PDF) is presented for the end-to-end signal-to-noise ratio. Based on the PDF, we derive the average bit-error-rate (BER) and the ergodic capacity. Moreover, we provide asymptotic BER and ergodic capacity results in simple forms. The performance and behavior of vertical UWOC systems are thoroughly analyzed, and all the derived expressions are verified via Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

In this paper, we propose a cost-efficient beamforming optimization algorithm for multi-user wireless communication systems associated with the intelligent reflecting surface (IRS). From the baseline successive refinement algorithm, which gives a sub-optimal solution for the power minimization problem under the signal-to-interference-plus-noise-ratio (SINR) constraint at each user, several optimization techniques are proposed to reduce the computation complexity while maintaining the algorithm-level performance. To reduce the number of required multiply-accumulate (MAC) operations, we first simplify the complicated matrix inversion by utilizing the channel hardening effect. We also present the two-phase refinement process for the group-level optimization of phase-shift elements, further relaxing the computation complexity as well as the processing latency. Applying the proposed optimization techniques, as a result, numerical results show that the fully-optimized algorithm can reduce the computational costs by up to 89.4% while showing less than 1 dB power loss, leading to the practical solution for the next-generation IRS-aided communication. [ABSTRACT FROM AUTHOR]

Recent research on joint source channel coding (JSCC) for wireless communications has achieved great success owing to the employment of deep learning (DL). However, the existing work on DL based JSCC usually trains the designed network to operate under a specific signal-to-noise ratio (SNR) regime, without taking into account that the SNR level during the deployment stage may differ from that during the training stage. A number of networks are required to cover the scenario with a broad range of SNRs, which is computational inefficiency (in the training stage) and requires large storage. To overcome these drawbacks our paper proposes a novel method called Attention DL based JSCC (ADJSCC) that can successfully operate with different SNR levels during transmission. This design is inspired by the resource assignment strategy in traditional JSCC, which dynamically adjusts the compression ratio in source coding and the channel coding rate according to the channel SNR. This is achieved by resorting to attention mechanisms because these are able to allocate computing resources to more critical tasks. Instead of applying the resource allocation strategy in traditional JSCC, the ADJSCC uses the channel-wise soft attention to scaling features according to SNR conditions. We compare the ADJSCC method with the state-of-the-art DL based JSCC method through extensive experiments to demonstrate its adaptability, robustness and versatility. Compared with the existing methods, the proposed method takes less storage and is more robust in the presence of channel mismatch. [ABSTRACT FROM AUTHOR]

This paper studies the integration of the newly-emerged intelligent reflecting surface (IRS) technology into non-orthogonal multiple access (NOMA)-based wireless powered communication networks (WPCNs). We consider two WPCNs which communicate with a common hybrid access point (HAP), where there exists two types of devices in each WPCN, namely information receiving device (IRD) and harvest-then-transmit device (HTTD). Downlink communication from the HAP to IRDs, downlink energy transfer (ET) from the HAP to HTTDs, and uplink information transmission (IT) from the HTTDs to the HAP are assisted by two IRSs, one in each WPCN. Under this setup, we propose efficient algorithms to optimize reflection coefficients, beamforming vectors, and resource allocation for the sake of uplink sum-rate maximization, taking into account the minimum rate requirement at the IRDs. Numerical results show the considerable performance gain of the proposed NOMA-based scheme as compared to the conventional orthogonal multiple access (OMA)-based counterpart. [ABSTRACT FROM AUTHOR]

Deployment of unmanned aerial vehicles (UAVs) as flying base stations to provide specific geographical area with air-to-ground wireless communications is expected to increase dramatically in the coming decades, owing to its flexibility, mobility and autonomy. Moreover, mobile edge computing (MEC) promises significant reduction in latency by caching popular contents at the mobile edge. In this paper, we propose a method to apply mobile edge caching on UAVs in wireless communication systems. By investigating the user request preference with the aid of latent Dirichlet allocation (LDA), the caching strategy can be optimized. In the proposed system, we consider the design of intelligent caching strategies when a number of UAVs are deployed to serve ground users, where each UAV has a limited storage capacity for caching useful user contents. We use LDA to extract the user request preferences in order to intelligently cache data in the UAVs, while we utilize $k$ -means clustering to classify users and to help deploy UAVs. Besides, we consider three user-UAV association criteria, namely the user received signal to noise ratio (SNR), user preferences and the delay. Our simulation results show that, when compared to random caching, the average caching efficiency could be significantly improved from $\text{50}\%$ to $\text{70}\%$ , while the latency of our proposed system can also be greatly reduced. [ABSTRACT FROM AUTHOR]

Channel estimation is challenging for the reconfigurable intelligent surface (RIS)-aided wireless communications. Since the number of coefficients of the cascaded channel among the base station (BS), the RIS, and the user equipment (UE), is the product of the number of BS antennas, the number of RIS elements, and the number of UEs, the pilot overhead can be prohibitively high. In this paper, we propose a two-timescale channel estimation framework to exploit the property that the BS-RIS channel is high-dimensional but quasi-static, while the RIS-UE channel is mobile but low-dimensional. Specifically, to estimate the quasi-static BS-RIS channel, we propose a dual-link pilot transmission scheme, where the BS transmits downlink pilots and receives uplink pilots reflected by the RIS. Then, we propose a coordinate descent-based algorithm to recover the BS-RIS channel. Since the quasi-static BS-RIS channel is estimated less frequently than the mobile channel is, the average pilot overhead can be reduced from a long-term perspective. Although the mobile RIS-UE channel has to be frequently estimated in a small timescale, the associated pilot overhead is low thanks to its low dimension. Simulation results show that the proposed two-timescale channel estimation framework can achieve accurate channel estimation with low pilot overhead. [ABSTRACT FROM AUTHOR]

Cooperative beamforming is a potentially useful technique for enhancing link reliability in modern wireless relay communications. To aid the beamforming design, the signal-to-noise ratio (SNR) of the source-to-relay (S-R) channel links must be known at the destination node. Abdallah and Papadopoulos in IEEE Trans. Signal Processing, vol. 56, no. 10, 2008, proposed a beamforming system with relay-assisted SNR acquisition; that is, the S-R link SNR is first quantized at each relay and is then forwarded to the destination. An optimal quantizer design problem was proposed in that paper, aiming at reducing the system bit error rate; however, only the binary quantization case was considered therein, with the quantization threshold computed by a suggested rule of thumb. In this paper, we study the aforementioned quantizer design problem in the general multiple-bit setting. We show that the solutions to the first-order necessary condition for optimality can be obtained as a fixed point of a certain nonlinear map over the feasible threshold set. The existence and uniqueness of the fixed point are established by using, respectively, the Brouwer’s and Schauder’s fixed point theorems. Finally, we show that the fixed point thus obtained yields the globally optimal set of quantization thresholds. To the best of our knowledge, this paper is the first which leverages fixed point theories to rigorously solve SNR quantization problems in the context of wireless relay communication. [ABSTRACT FROM AUTHOR]

Multiple-input Multiple-output (MIMO) technologies play an important role in modern and future wireless communication systems as they can improve the capacity without increasing the bandwidth. MIMO detection is one of the key technologies for MIMO system designs. MIMO detection schemes based on Message Passing (MP) algorithms have attracted extensive attention in recent years. The MIMO detection scheme based on Expectation Propagation (EP), which is also a kind of MP algorithms, has been proved to achieve the Bayes-optimal performance under the conditions of large system limit and compression rate threshold. However, there is improvement space for the detection performance of the EP algorithm when the conditions are not satisfied, which are the common cases in the practical applications. In this paper, when the conditions of the large system limit and compression rate threshold are not satisfied, we analyze the influences of two factors, the initial parameters selection and the moment matching strategy, on the performance of EP based detection scheme. As a result, we propose an improved EP detection scheme based on optimizing the two factors. Simulation results show that the proposed scheme outperforms the original EP detection scheme in different MIMO scenarios. [ABSTRACT FROM AUTHOR]

It is very challenging to detect an unmanned-aerial-vehicle (UAV) when it is applied to launch an attack by the enemy’s country, due to its feature of mobility and flexibility. Against this background, in this paper, from wireless communication point of view, we study the detection probability of home country’s ground vehicle (GV) to enemy’s ground-station (GS)-to-UAV transmission system. We assume that the location of the GV is randomly distributed inside the space confined by the largest detection distance. Moreover, we assume the enemy’s UAV is randomly distributed in the coverage space of the GS-to-UAV (G2A) transmission link but also keep the security distance from the GS. To this end, we first characterize the statistical features of the signal-to-noise-ratio (SNR) over the G2V and G2A links. Then, we define detection outage probability (DOP) and average detection capacity (ADC), and show their approximations. Finally, Monte-Carlo simulations are conducted to verify the correctness of our proposed analytical models. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new construction of generalized root protograph (GRP) low-density parity-check (LDPC) codes which has a guaranteed diversity order. New hybrid-automatic request with incremental redundancy (H-ARQ-IR) is also proposed to ensure high diversity and rate-compatibility in wireless communication systems, where the GRP LDPC codes are employed along with a method called feedback encoding. The proposed H-ARQ-IR has advantages of low-complexity and near-optimal performance. In order to show its performance behavior, theoretical analysis for the proposed scheme is conducted for the block fading channel. Furthermore, numerical analysis shows that it achieves near maximum diversity order under the belief propagation (BP) decoding with binary phase shift keying (BPSK) modulation and high-order quadrature amplitude modulations (QAMs). [ABSTRACT FROM AUTHOR]

Terahertz (THz) band communication is envisioned as a key technology to satisfy the increasing demand for ultrabroadband wireless systems, thanks to its ultrabroad bandwidth. Tailored for the unique properties of pulse-based communications in the THz band, two timing acquisition algorithms are proposed and analyzed thoroughly in this paper. First, a low-sampling-rate (LSR) synchronization algorithm is proposed, by extending the theory of sampling signals with finite rate of innovation in the communication context and exploiting the properties of the annihilating filter. The simulation results show that the timing accuracy at an order of ten picoseconds is achievable. In particular, the LSR algorithm has high performance with uniform sampling at $1/20$ of the Nyquist rate when the signal-to-noise ratio (SNR) is high (i.e., greater than 18 dB). Complementary to this, a maximum likelihood (ML) approach for timing acquisition is developed, which searches for the timing offsets by adopting a two-step acquisition procedure based on the ML criterion. The simulation results show that the ML-based algorithm is well suitable in the low SNR case with a half-reduced search space. For further evaluation, the error performance and the resulting bit-error-rate sensitivity to the timing errors in the LSR and the ML algorithms are both analytically and numerically studied. This paper provides very different and promising angles to efficiently and reliably solve the timing acquisition problem for pulse-based THz band wireless systems. [ABSTRACT FROM PUBLISHER]

The level crossing rate (LCR) is an important second-order statistical quantity that characterizes the rate of occurrence of fading time intervals. In this paper, we investigate the LCR of multiantenna flat-fading channels in the presence of additive white Gaussian noise and cochannel interferers with unequal received powers and Doppler shifts. We first present a unified approach to derive the exact LCR of the signal-to-interference-noise ratio at a receiver, where maximum ratio combining is deployed over spatially correlated or uncorrelated systems. Through the exact LCR derivation, we identify an accurate approach to obtain a simplified approximate LCR expression in the spatially uncorrelated system case. Benefits of the LCR expressions derived in the paper are demonstrated in two important applications: 1) the packet error rate is evaluated through the finite-state Markov channel model; and 2) the optimum packet length to maximize the throughput of the system with the stop-and-wait automatic repeat request protocol is derived. The analytical results are validated by simulations. [ABSTRACT FROM PUBLISHER]

Millimeter wave (mmWave) has been widely considered as a promising technology in the next generation wireless communication systems. Various beam-based directional transmission techniques have been proposed to compensate high pathloss caused by mmWave properties. However, mobility effect of users potentially causes severe inter-beam interferences, which has not been fully-investigated in existing studies. In this paper, we have analyzed different types of mobility-aware beam interference models. Additionally, the theoretical SINR is derived based on channel statistics and the trajectories of users. We propose a mobility-aware subband and beam resource allocation (MSBA) scheme for the mmWave subband-beam massive multi-input multi-output (SB-MMIMO) systems. The proposed MSBA benefits from reduced computation complexity for maximizing system throughput constrained by quality-of-service (QoS) demands of users. The first phase of MSBA scheme is responsible for resource block assignment; while the second phase allocates beamwidth and beam directions according to the analytical derivations. Numerical results show that the proposed MSBA scheme can effectively achieve the highest system throughput and the lowest complexity compared to existing schemes in open literatures. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) that enables the control of wireless propagation environment has recently emerged as a promising cost-effective technology for boosting the spectral and energy efficiency of future wireless communication systems. Prior works on IRS are mainly based on the ideal phase shift model assuming full signal reflection by each of its elements regardless of the phase shift, which, however, is practically difficult to realize. In contrast, we propose in this paper a practical phase shift model that captures the phase-dependent amplitude variation in the element-wise reflection design. Based on the proposed model and considering an IRS-aided multiuser system with one IRS deployed to assist in the downlink communications from a multi-antenna access point (AP) to multiple single-antenna users, we formulate an optimization problem to minimize the total transmit power at the AP by jointly designing the AP transmit beamforming and the IRS reflect beamforming, subject to the users’ individual signal-to-interference-plus-noise ratio (SINR) constraints. Iterative algorithms are proposed to find suboptimal solutions to this problem efficiently by utilizing the alternating optimization (AO) as well as penalty-based optimization techniques. Moreover, to draw essential insight, we analyze the asymptotic performance loss of the IRS-aided system that employs practical phase shifters but assumes the ideal phase shift model for beamforming optimization, as the number of IRS elements goes to infinity. Simulation results unveil substantial performance gains achieved by the proposed beamforming optimization based on the practical phase shift model as compared to the conventional ideal model. [ABSTRACT FROM AUTHOR]

In this paper, the effective rate (ER) of wireless communication systems and the performance of energy detection (ED) based spectrum sensing over $\alpha -\eta -\kappa -\mu$ fading channels are analysed. To this end, novel mathematically tractable exact expressions of the ER, the average detection probability (ADP) and the average area under the receiver characteristics curve (AUC) are derived. The asymptotic expressions at high average signal-to-noise ratio (SNR) values are also provided. A comparison between the numerical results and Monte Carlo simulations is presented to verify the validation of our analysis. The mathematical relationship between the ER and the performance metrics of the ED which is based on the time-bandwidth product, is explained. The provided results show that the increase in the time-bandwidth product from 1 to 4 reduces the ER, the ADP, and the average AUC by nearly $\text{21}\%$ , $\text{8}\%$ , and $\text{3}\%$ , respectively, for constant average SNR at 15 dB and delay exponent at 0.1. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) and non-orthogonal multiple access (NOMA) are deemed two promising technologies in the next generation wireless communication systems in achieving high capacity and massive connectivity. In this paper we study the performance of a NOMA-enabled VLC system using different modulation schemes. In particular system level bit error rate (BER) is derived for different modulation schemes. Conventional methods used for analyzing the BER under orthogonal multiple access cannot be directly applied to NOMA. In order to obtain the closed-form BER expressions for the NOMA-enabled VLC systems, an analytical framework based on bitwise-decision axis and signal space is proposed.Moreover, the analysis method can be extended to the any wireless communication networks with NOMA. Simulation results demonstrate the accuracy of the theoretical analysis. The study shows that the BER gap among users decreases with the increase of the modulation order but at the cost of a higher power consumption in order to achieve a better signal to noise ratio. It is observed that 8-PSK modulation in NOMA-enabled VLC systems strikes a good tradeoff between the power cost and the achievable BER. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed energy-harvesting random access protocol called harvest-or-access by applying slotted ALOHA to wireless powered communication networks (WPCNs). From the fact that there are a considerable number of idle slots during which any nodes do not attempt transmission in slotted ALOHA, the idle slots are made available for wireless energy transfer (WET). If any random access (RA) slot is recognized as an idle slot, the hybrid access point (HAP) opportunistically performs the WET in this slot. The wireless devices (WDs) can harvest energy for every idle slot and attempt random access by using this harvested energy. An asymptotic throughput analysis in a high signal-to-noise ratio (SNR) environment with a sufficient number of accessing WDs shows that there is an optimal number of RA slots allocated to maximize throughput and this optimal number of RA slots depends only on the average of the minimum SNRs of the WDs without knowledge of full channel state information. Monte Carlo simulation results further show that the proposed harvest-or-access protocol outperforms the conventional harvest-then-transmit-based random access protocols especially when the number of WDs is large. [ABSTRACT FROM AUTHOR]

This paper investigates the secrecy performance of multiple-input multiple-output systems under generalized $\alpha -\mu $ fading conditions. To this end, we focus on two distinct scenarios: 1) the transmitter has knowledge of the channel state information (CSI) of the eavesdropper channel and 2) the transmitter is not aware of the CSI of the wiretap link. By considering transmit antenna selection in the underlying system, we develop closed-form analytical expressions for the lower bound of the secrecy outage probability (SOP) and the probability of the strictly positive secrecy capacity. Furthermore, two novel approaches are proposed to derive an analytical expression of the average secrecy capacity (ASC). First, the ASC is expressed as a function of the average capacity of the desired link and an interaction term regarded as the ASC loss. Second, the ASC is expressed in terms of the average capacities of the desired and eavesdropper links, plus an interaction term that can be regarded as some sort of ASC gain due to the statistical independence between the desired and eavesdropper links. In addition, asymptotic studies of the SOP and the ASC at high signal-to-noise ratio are carried out, which precisely reveal the secrecy diversity and array gains. [ABSTRACT FROM AUTHOR]

Full-duplex (FD) jamming transceivers recently have been shown to enhance the information security of wireless communication systems by simultaneously transmitting artificial noise (AN) while receiving information. In this paper, we investigate whether FD jamming can also improve the system’s secrecy energy efficiency (SEE) in terms of securely communicated bits per Joule when considering the additional power used for jamming and self-interference (SI) cancellation. Moreover, the degrading effect of the residual SI is also taken into account. In this regard, we formulate a set of SEE maximization problems for a FD multiple-input-multiple-output multiple-antenna eavesdropper (MIMOME) wiretap channel, considering both cases where exact or statistical channel state information (CSI) is available. Due to the intractable problem structure, we propose iterative solutions in each case with a proven convergence to a stationary point. Numerical simulations indicate only a marginal SEE gain, through the utilization of FD jamming, for a wide range of system conditions. However, when SI can efficiently be mitigated, the observed gain is considerable for scenarios with a small distance between the FD node and the eavesdropper, a high signal-to-noise ratio (SNR), or for a bidirectional FD communication setup. [ABSTRACT FROM AUTHOR]

Multi-channel (MC) optical wireless communication (OWC) systems employing wave-division multiplexing for outdoors free-space optical communications, or multi-user time-division multiple access for indoors visible-light communications, e.g., can be modeled as parallel channels. Multi-input multi-output OWC systems can also be transformed, possibly with some performance loss, to parallel channels using pre-/post-coding. Studying the performance of such MC-OWC systems requires characterizing the capacity of the underlying parallel channels. In this paper, upper and lower bounds on the capacity of constant parallel OWC channels with a total average intensity constraint are derived. Then, this paper focuses on finding intensity allocations that maximize the lower bounds given channel-state information at the transmitter (CSIT). Due to its nonconvexity, the Karush–Kuhn–Tucker conditions are used to describe a list of candidate allocations. Instead searching exhaustively for the best solution, low-complexity near-optimal algorithms are proposed. The resulting optimized lower bound nearly coincides with capacity at high signal-to-noise ratio (SNR). Under a quasi-static channel model and in the absence of CSIT, outage probability upper and lower bounds are derived. Those bounds also meet at high SNR, thus characterizing the outage capacity in this regime. Finally, the results are extended to a system with both average and peak intensity constraints. [ABSTRACT FROM PUBLISHER]

In this paper, a system-level design is presented for an integrated receive circuit for a wireless ultrasound probe, which includes analog front ends and beamformation modules. This paper focuses on the investigation of the effects of architectural design choices on the image quality. The point spread function is simulated in Field II from 10 to 160 mm using a convex array transducer. A noise analysis is performed, and the minimum signal-to-noise ratio (SNR) requirements are derived for the low-noise amplifiers (LNAs) and A/D converters (ADCs) to fulfill the design specifications of a dynamic range of 60 dB and a penetration depth of 160 mm in the B-mode image. Six front-end implementations are compared using Nyquist-rate and $\Sigma \Delta $ modulator ADCs. The image quality is evaluated as a function of the depth in terms of lateral full-width at half-maximum (FWHM) and −12-dB cystic resolution (CR). The designs that minimally satisfy the specifications are based on an 8-b 30-MSPS Nyquist converter and a single-bit third-order 240-MSPS $\Sigma \Delta $ modulator, with an SNR for the LNA in both cases equal to 64 dB. The mean lateral FWHM and CR are 2.4% and 7.1% lower for the $\Sigma \Delta $ architecture compared with the Nyquist-rate one. However, the results generally show minimal differences between equivalent architectures. Advantages and drawbacks are finally discussed for the two families of converters. [ABSTRACT FROM AUTHOR]

G-Cast is a wireless visual communication scheme that conveys visual information via image gradient. It is inspired by the characteristics of human vision systems and can provide improved perceptual quality. G-Cast is power efficient but bandwidth demanding, because gradient data have double the size of the original image. This paper presents a scheme named CG-Cast for scalable image transmission in bandwidth-limited wireless scenarios. It employs a compressive-gradient-based image representation to describe perceptually sensitive image details and reduce the bandwidth requirement at the same time, combining gradient-based visual representation with compressive sensing techniques. The compressive gradient data are transmitted in a pseudo-analog way so that it achieves elegant quality transition in a wide channel signal-to-noise ratio (CSNR) range. CG-Cast also sends a small set of low-frequency data in digital a way to provide the global and local luminance of the image. We developed an effective optimization algorithm for the decoder to reconstruct the original image from the received noisy compressive gradient and the low-frequency part of the image. Experimental results demonstrate that the proposed scheme improves the quality of received images remarkably under different CSNR and channel bandwidth conditions. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the secrecy performance of a dual-hop cooperative relaying network, where a source node communicates with a destination node via an amplify-and-forward relay node and via direct link in the presence of a passive eavesdropper. In this network, the eavesdropper exploits the advantages of both direct and relay links. We assume that the source, relay, and eavesdropper nodes are mobile, and the destination node is stationary. Moreover, we consider that the source-relay, relay-destination, and source-destination links experience Rayleigh fading, whereas source-eavesdropper and relay-eavesdropper links undergo double-Rayleigh fading. Examples of such scenario are encountered in vehicle-to-vehicle communication and/or vehicle-to-infrastructure communication under cooperative vehicular networks. In particular, we derive new tight closed-form expressions for the secrecy outage probability and ergodic secrecy capacity of the considered system under mixed fading environments. In addition, we present an effective secrecy diversity order within the main-to-eavesdropper ratio ranges of practical interest, and demonstrate that the secrecy diversity order of 2 can be achieved. Finally, the numerical and simulation results corroborate our analytical findings, and show the occurrence conditions for secrecy outage probability and ergodic secrecy capacity floors, and impacts of channel conditions and relay and eavesdropper positions on the system secrecy performance. [ABSTRACT FROM AUTHOR]

This paper analyzes statistical properties of the Poisson line Cox point process useful in the modeling of vehicular networks. The point process is created by a two-stage construction: a Poisson line process to model road infrastructure and independent Poisson point processes, conditionally on the Poisson lines, to model vehicles on the roads. We derive basic properties of the point process, including the general quadratic position of the points, the nearest distance distribution, the Laplace functional, the densities of facets of the Cox–Voronoi tessellation, and the asymptotic behavior of the typical Voronoi cell under vehicular densification. These properties are closely linked to features that are important in vehicular networks. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new architecture and performance analysis for beam index modulation (BIM) wireless communication implemented with the aid of analog beamforming. The BIM concept is presented in order to extend and adapt the spatial modulation concept to sparse wireless communication channel environments. It is shown that when compared with the conventional beamforming and SM strategies, the BIM system can achieve higher spectrum efficiency in high signal-to-noise ratio and non-line-of-sight (nLoS) sparse channel scenarios. Furthermore, different to the previous spatial scattering modulation (SSM) work the proposed BIM architectures have reduced hardware complexity, and, importantly, in some nLoS sparse channel conditions the BIM can also outperform the SSM. The above findings were further validated by some demonstrative experiments that were conducted at 10 GHz. [ABSTRACT FROM AUTHOR]

Channel state information (CSI) is critical for the performance of cooperative multicell transmission. In this paper, the performances of cooperative multicell precoding under global CSI and local individual CSI are analyzed and compared in the large dimensional regime. Using theoretical results from large random matrix theory, we derive large dimensional approximations of signal-to-interference-plus-noise ratio for both precoding cases. Such approximations depend only on the slow fading channel statistics instead of the fast fading channel realizations. It is easy to quantify the performance loss caused by local individual CSI in the large dimensional regime. Two different massive MIMO scenarios are considered. When the number of antennas and that of users go large at the same rate, there is a constant gap between the two CSI cases. When the number of antennas goes large, while the number of users is fixed, the performances of both CSI cases are the same. This means that the impact of limited local individual CSI vanishes. Numerical results validate the theoretical analysis and show that there is constant performance loss due to the price of limited CSI. Also, the performance of precoding with local individual CSI almost decreases linearly with the increased number of BSs for the first scenario. [ABSTRACT FROM PUBLISHER]

The medium access probability (MAP) of a random access protocol can severely impact network throughput especially for delay-sensitive applications, since it determines whether a node should transmit packets in a given slot or not. This paper focuses on network throughput maximization through optimizing the MAPs of all users under delay quality-of-service constraints in wireless interference-limited networks. Specifically, first, the total delay for transmitting one packet for a user is analyzed and derived based on an M/G/1 model. Then, the stochastic property of the aggregated interference is analyzed and its distribution is modeled as a log-normal distribution. Based on the delay and interference models, an optimization problem is formulated to derive the optimal MAPs so that the network throughput is maximized under the delay constraints. Two network traffic scenarios, homogeneous and heterogeneous user traffic, are discussed, respectively. For the case of homogeneous traffic, a closed-form expression of the optimal MAP is derived; for the case of heterogeneous traffic, a global $\epsilon $ -optimal algorithm based on the branch-and-bound framework and convex relaxation technology is proposed with relatively low complexity. Simulations results show that the proposed algorithms can achieve superior network throughput performance over existing schemes. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an imperfect quantized feedback-based diagonal precoding scheme for generalized orthogonal space-time block codes in an $N \times 1$ multiple-input single-output (MISO) wireless communication system employing $M$ -QAM constellation. It is well known that a feedback-based precoding scheme aids channel adaptive signaling in wireless communication system and capitulates large improvements in almost all performance metrics. However, a practical feedback link is susceptible to error due to wireless channel fading and leads to wrong precoder selection. Therefore, a signal-to-noise ratio (SNR) adaptive error-tolerant weighting scheme is introduced which provides significant gain in comparison with another proposed arbitrarily fixed SNR error-tolerant weighting scheme. At first, a tight approximate closed-form expression of average symbol-error-rate (SER) and an exact analytical expression of outage probability are derived under imperfect feedback information with the help of order statistics. By minimizing the derived average SER, optimized transmit weights for the diagonal precoding matrix (based on feedback bits) are obtained. Later, a closed-form expression of the ergodic capacity with erroneous feedback bits for arbitrary MISO system is also provided by using the moment generating function approach. Further, numerical results show that the considered error-tolerant schemes outperform the uniform power allocation scheme in term of all the investigated performance metrics. [ABSTRACT FROM AUTHOR]

The capacity region of the $K$ -user Gaussian interference channel (GIC) is a long-standing open problem and even capacity outer bounds are little known in general. A significant progress on degrees-of-freedom (DoF) analysis, a first-order capacity approximation, for the $K$ -user GIC has provided new important insights into the problem of interest in the high signal-to-noise ratio (SNR) limit. However, such capacity approximation has been observed to have some limitations in predicting the capacity at finite SNR. In this paper, we develop a new upper-bounding technique that utilizes a new type of genie signal and applies time sharing to genie signals at $K$ receivers. Based on this technique, we derive new upper bounds on the sum capacity of the three-user GIC with constant, complex channel coefficients and then generalize to the $K$ -user case to better understand sum-rate behavior at finite SNR. We also provide closed-form expressions of our upper bounds on the capacity of the $K$ -user symmetric GIC easily computable for any $K$ . From the perspectives of our results, some sum-rate behavior at finite SNR is in line with the insights given by the known DoF results, while some others are not. In particular, the well-known $K/2$ DoF achievable for almost all constant real channel coefficients turns out to be not embodied as a substantial performance gain over a certain range of the cross-channel coefficient in the $K$ -user symmetric real case especially for large $K$ . We further investigate the impact of phase offset between the direct-channel coefficient and the cross-channel coefficients on the sum-rate upper bound for the three-user complex GIC. As a consequence, we aim to provide new findings that could not be predicted by the prior works on DoF of GICs. [ABSTRACT FROM PUBLISHER]

The Beckmann distribution is a general multipath fading model for the received radio signal in the presence of a large number of scatterers, which can thence be modeled as a complex Gaussian random variable where both the in-phase and quadrature components have arbitrary mean and variance. However, the complicated nature of this distribution has prevented its widespread use and relatively few analytical results have been reported for this otherwise useful fading model. In this paper, we derive a closed-form expression for the generalized moment-generating function (MGF) of the signal-to-noise ratio (SNR) of Beckmann fading, which permits to circumvent the inherent analytical complexity of this model. This is a new and useful result, as it is a key for evaluating several important performance metrics of different wireless communication systems and also permits to readily compute the moments of the output SNR. Thus, we obtain simple exact expressions for the energy detection performance in Beckmann fading channels, both in terms of the receiver operating characteristic (ROC) curve and of the area under ROC curve. We also analyze the outage probability in interference limited systems affected by Beckmann fading, as well as the outage probability of secrecy capacity in wiretap Beckmann fading channels. Monte Carlo simulations have been performed to validate the derived expressions. [ABSTRACT FROM AUTHOR]

In this paper, the fundamental limits of simultaneous information and energy transmission in the two-user Gaussian multiple access channel with feedback (G-MAC-F) and without feedback (G-MAC) are fully characterized. More specifically, all the achievable information and energy transmission rates (in bits per channel use and energy-units per channel use, respectively) are identified. Furthermore, the fundamental limits on the individual and sum- rates given a minimum-energy rate ensured at an energy harvester are also characterized. In the case without feedback, an achievability scheme based on power-splitting and successive interference cancellation is shown to be optimal. Alternatively, in the G-MAC-F case, a simple yet optimal achievability scheme based on power-splitting and Ozarow’s capacity achieving scheme is presented. Finally, the energy transmission enhancement induced by the use of feedback is quantified. Feedback can at most double the energy transmission rate at high SNRs when the information transmission sum-rate is kept fixed at the sum-capacity of the G-MAC, but it has no effect at very low SNRs. [ABSTRACT FROM AUTHOR]

Considering a dual-hop energy-harvesting (EH) relaying system, this paper advocates novel relaying protocols based on adaptive time-switching (TS) for amplify-and-forward and decode-and-forward modes, respectively. The optimal TS factor is first studied, which is adaptively adjusted based on the dual-hop channel state information (CSI), accumulated energy, and threshold signal-to-noise ratio (SNR), to achieve the maximum throughput efficiency per block. To reduce the CSI overhead at the EH relay, a low-complexity TS factor design is presented, which only needs single-hop CSI to determine the TS factor. Theoretical results show that, in comparison with the conventional solutions, the proposed optimal/low-complexity TS factor can achieve higher limiting throughput efficiency for sufficiently small threshold SNR. As the threshold SNR approaches infinity, the throughput efficiency of the proposed optimal/low-complexity TS factor tends to zero in a much slower pace than that of the conventional solutions. Simulation results are presented to corroborate the proposed methodology. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the power–delay tradeoff for the newly emerging wireless powered communication networks, in which wireless powered devices (WPDs) harvest energy from a power station via wireless energy transfer in the downlink and then communicate with an information receiving station in the uplink. Each WPD is equipped with an energy buffer and a data buffer to store the random harvested energy and the bursty data arrivals, respectively. To minimize the time-averaged power consumption, a stochastic optimization problem is formulated subject to both constraints of data queue stability and harvested energy availability. By employing Lyapunov optimization theory, we transform the stochastic optimization problem into a series of deterministic problems, where each is further proved to become the standard convex optimization problem and, hence, can be effectively and optimally solved by standard convex optimization techniques. Correspondingly, we propose an Online Power and TIMe Allocation (Optima) algorithm, which requires no a priori distribution knowledge of channel states and data arrivals. Most importantly, the proposed algorithm achieves the power–delay tradeoff as [\mathcalO(\text1/V),\mathcalO(V)], with $V$ being a system control parameter, and provides a significant method to control the power–delay performance on demand in system design. Simulation results verify the theoretical analysis and validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a cooperative wireless system with unreliable wireless backhaul connections is investigated. To increase the throughput and maximize the receiver signal-to-noise ratio (SNR), a selection combining (SC) protocol is employed. Cooperative transmitters are connected to the control unit (CU) via independent but unreliable wireless backhaul connections. Simultaneously taking into account the reliability of each backhaul and different fading conditions of Nakagami-$m$ fading channels, the statistical properties of the effective SNR (e-SNR) at the receiver are investigated. Closed-form expressions are derived for several performance metrics, including the outage probability, average spectral efficiency (ASE), and average symbol error rate (ASER). The effects of backhaul reliability on these performance metrics are also investigated. The scaling relationship between the convergence behavior of these performance metrics and the conventional diversity gain is also analytically investigated in the asymptotic high-SNR regime. Monte Carlo simulations are conducted to verify the derived impact of backhaul reliability on the performance. [ABSTRACT FROM PUBLISHER]

This paper analyzes the impact of statistical delay constraints on the achievable rate of a two-hop wireless communication link in which the communication between a source and a destination is accomplished via a buffer-aided relay node. It is assumed that there is no direct link between the source and the destination, and the buffer-aided relay forwards the information to the destination by employing the decode-and-forward scheme. Given statistical delay constraints specified via maximum delay and delay violation probability, the tradeoff between the statistical delay constraints imposed on any two concatenated queues is identified. With this characterization, the maximum constant arrival rates that can be supported by this two-hop link are obtained by determining the effective capacity of such links as a function of the statistical delay constraints, signal-to-noise ratios at the source and relay, and the fading distributions of the links. It is shown that asymmetric statistical delay constraints at the buffers of the source and relay node can improve the achievable rate. Overall, the impact of the statistical delay tradeoff on the achievable throughput is provided. [ABSTRACT FROM PUBLISHER]

This paper analyzes the performance of energy-constrained dual-hop amplify-and-forward relaying systems with multi-antenna nodes in the presence of multiple co-channel interferers at the destination. To maximize the overall signal-to-interference-plus-noise ratio, as well as the harvested energy so as to mitigate the severe effects of fading and enable long-distance wireless power transfer, hop-by-hop information and energy beamforming is proposed where the transmitted signal is steered along the strongest eigenmode of each hop. The wirelessly powered relay scavenges energy from the source information radio frequency signal through energy beamforming, where both the time-switching receiver and power-splitting receiver are considered, and then uses the harvested energy to forward the source message to the destination. To this end, tight lower and upper bound expressions for the outage probability and ergodic capacity are presented in closed form. These are employed to investigate the throughput of the delay-constrained and delay-tolerant transmission modes. In addition, the asymptotic high signal-to-noise ratio outage probability and ergodic capacity approximations are derived, where the achievable diversity order is also presented. Numerical results sustained by Monte Carlo simulations show the tightness of the proposed analytical expressions. The impact of various parameters, such as energy harvesting time, power-splitting ratio, source transmit power, and the number of antennas on the system throughput, is also considered. [ABSTRACT FROM PUBLISHER]

We study the optimal resource allocation in the wireless powered underground sensor network (WPUSN) for throughput maximization. The WPUSN is a new networking paradigm where underground sensors can be replenished by a radio frequency energy harvesting technique and transmit geological data to the nearby aboveground access point in real time. In this paradigm, the underground portion of the wireless communication link suffers from severe path loss. Moreover, different underground sensors may have diverse data traffic demands. In this paper, we formulate an optimization problem to maximize the throughput in WPUSNs with the quality of service (QoS) consideration in terms of communication reliability and diverse data traffic demands. Specifically, we map the QoS requirements to signal-to-noise ratio thresholds and transform our problem into a convex optimization problem with linear constraints. We then present a closed-form solution for the transformed problem through a problem decomposition of the Karush–Kuhn–Tucker conditions. Our closed-form solution uncovers the insights that how the wireless channel states, reliability requirements, and data traffic demands affect the optimal resource allocation in the WPUSN. Finally, we demonstrate the effectiveness of the proposed scheme by running simulations. [ABSTRACT FROM PUBLISHER]

For high-speed railway (HSR), an essential characteristic of the propagation channels is the specific spatial–temporal correlation caused by a dominant strong line-of-sight (LOS) component. Multiple-antenna gain is therefore far from being achieved due to this strong channel correlation. However, it is interesting to note that if the resulted intercarrier interference (ICI) is elaborately controlled, high mobility may decrease the channel correlation. Spatial modulation (SM) is one of the promising multiple-antenna technologies for wireless communication systems, which needs only the activation of one transmit antenna to convey information bits implicitly through the index of the active transmit antenna, in addition to conveying information bits through modulation symbols during transmission. In SM, ICI is avoided, which therefore helps in the implementation of the idea of decreasing channel correlation by increasing the velocity in an HSR scenario. In this paper, the performance of massive SM multiple-input multiple-output (MIMO) over a spatial–temporal correlated Rician fading channel is investigated under an HSR scenario. The impacts of velocity, Rician factor K, and signal-to-noise ratio (SNR) are discussed. In addition, the correlation factor and the correlation comparison function are defined as metrics of channel correlation. We theoretically find out that higher velocity makes the impact of temporal correlation more dominant, which weakens the influence of spatial correlation. In other words, spatial correlation can be weakened by high mobility. Our theoretical analysis and simulations further demonstrate that, with an appropriate scheme, massive SM MIMO outperforms Vertical Bell Laboratories Layered Space–Time (VBLAST), except at a lower SNR region with high velocity (usually more than 360 km/h). Consequently, massive SM MIMO is a promising solution within an appropriate range of velocity for HSR wireless communication systems. [ABSTRACT FROM PUBLISHER]

In this paper, we explore some of the fundamentals of synchronous Code Division Multiple Access (CDMA) as applied to wireless and optical communication systems under very general settings (of any size) for the user symbols and the signature matrix entries. The channel is modeled by real/complex additive noise of arbitrary distribution. Two problems are addressed. The first problem concerns whether uniquely detectable overloaded matrices exist in the absence of additive noise under these general settings, and if so, whether there are any practical optimum detection algorithms. The second one is about the bounds for the sum channel capacity when user data and signature matrices employ any real or complex alphabets (finite or infinite). In response to the first problem, we have developed practical maximum likelihood detection algorithms for overloaded CDMA systems for a large class of alphabets. In response to the second problem, a general theorem has been developed in which the sum capacity lower bounds with respect to the number of users, spreading gain, and signal-to-noise ratio can be derived. To show the power and utility of the main theorem, a number of sum capacity bounds for special cases are evaluated. An important conclusion of this paper is that the lower and upper bounds of the sum capacity for small/medium-size CDMA systems depend on both the input and the signature symbols; this is contrary to the asymptotic results for large-scale systems reported in the literature (also confirmed in this paper) where the signature symbols and statistics disappear for signature matrices and input vectors with i.i.d. entries. Furthermore, upper and asymptotic bounds are derived and compared to other derivations. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical analysis and computer simulation experiments to determine the effect of amplitude modulation (AM) on a fractal model of electromagnetic noise. The experiments found that the desired fractal character of a baseband monofractal noise signal was altered and became a multifractal signal over its upper sideband spectral frequencies, yet approximately monofractal when considering a small frequency range within this sideband. However, the magnitude of the spectral exponent of the power law that describes the modulated signal in this small frequency range differed significantly from that of the modulating signal. Therefore, due to first, the character-altering behavior, second, the nonspecificity of the spectral exponent, and third, the limited narrowband range for observing monofractality, this paper concluded that AM was not considered ideal for synthesizing a broadband signal from a baseband model. [ABSTRACT FROM AUTHOR]

Although there has been a growing interest on the study of diversity-multiplexing tradeoff (DMT), the existing works are mostly restricted to the outcomes reported for Rayleigh, Rician, and Nakagami fading channels. In this paper, we investigate the optimal tradeoff in the presence of log-normal fading, which provides an accurate model for indoor wireless, optical wireless, and ultra-wideband channels. We consider a multiple-input multiple-output (MIMO) log-normal channel, derive the outage probability expression, and then present the asymptotical DMT expression. It is shown that the asymptotical maximum diversity gain tends to infinity with logarithm of signal-to-noise ratio (SNR). To have further insight, we normalize the DMT with that of single-input single-output case and express the relative asymptotical DMT of the MIMO log-normal channel as a function of the number of transmit and receive antennas. We further study DMT for finite SNRs and demonstrate convergence to the asymptotical case. Extensive numerical results are provided to corroborate the analytical derivation. [ABSTRACT FROM AUTHOR]

In this paper, a bivariate \kappa- \mu model is presented. Exact expressions for the 1) joint probability density function, the 2) joint cumulative distribution function, 3) joint arbitrary moments, and the 4) normalized envelope correlation coefficient are derived. The joint statistics are given in terms of their respective parameters (\kappa1,\mu1) and (\kappa2,\mu2), with \mu1=\mu2=\mu>\mbox{0} and arbitrary \kappa1>\mbox{0} and \kappa2>\mbox{0}. The parameter describing the correlation between $\kappa$- $\mu$ fading channels is then written in terms of the physical instances known to affect it in a wireless medium, namely, Doppler shift, the separation distance between two reception points, frequency, and delay spread. As an application example, the outage probability of a dual-branch selection-combining scheme is presented. The effect of correlation in the various aspects of system performance is then investigated. The validity of the analytical results is supported by reducing them to particular cases, for which results are available in the literature, and by means of simulation for the general cases. [ABSTRACT FROM AUTHOR]

Compute-and-forward (C&F) is a promising new approach to interference management, enjoying several advantages over other information-theoretic schemes. C&F usually requires channel state information (CSI) at the receivers so that an “optimal” scaling factor can be computed for the purposes of decoding. In this paper, a blind C&F scheme—i.e., one not requiring CSI—is developed. Rather than attempting to compute the optimal scaling factor, this new scheme seeks one or more “good” scalars, i.e., scalars that allow correct decoding despite possibly being suboptimal. The region of all such good scalars is characterized. To find a good scalar, a computationally efficient scheme is proposed which involves error-detection, a hierarchically organized list, as well as a use of the smoothing lemma from lattice theory. Simulation results show that our blind C&F scheme achieves—for a class of nested lattice codes—the same throughput as its CSI-enabled counterpart at the expense of, approximately, a two-fold increase in computational complexity in the high-throughput region. Moreover, our blind C&F scheme can be applied to multisource multirelay networks with a good performance/complexity tradeoff. [ABSTRACT FROM AUTHOR]

This paper tackles the problem of minimum-energy cooperative transmission in wireless networks under the assumption of limited channel state information at the transmitters. It is assumed that only the average statistics of the fading channels are known to the transmitters. The objective here is to jointly optimize the set of relays and the transmission powers for both the broadcasting and cooperative transmission phases while satisfying probabilistic signal-to-noise ratio (SNR) constraints at the relays and at the destination node. Increasing the broadcasting power expands the set of potential relays and decreases the required power for cooperative transmission. Hence, there is a compromise in the selection of the power values, which is addressed in this work using a chance-constrained optimization framework. A closed-form approximate solution is also presented, which provides a low-complexity transmission scheme for energy-harvesting wireless networks. Simulations are presented to demonstrate the efficacy of the proposed approach and the approximate solution. [ABSTRACT FROM AUTHOR]

This paper presents the concept and demonstration of harmonic diversity for wireless communication, which makes use of multiple harmonic radio frequency (RF) channels with respect to the carrier frequency. Rather than frequency and space diversities widely used today to improve multipath fading, signal quality and spectral efficiency, the proposed scheme does not require multiple RF transceiver front-ends. The advantages of inherent RF device nonlinear characteristics are harnessed to produce and process harmonics within single transceiver. Even though distinct harmonic channels will exhibit different order of phase shifts, the analysis shows that such phase offsets can be compensated by adjusting the phase of local oscillator (LO) at receiver end. Extending the framework of the Shannon theorem, an M-channel harmonic communication system is shown to reduce the minimum required signal-to-noise ratio (SNR) at the input of receiver by M-times. In addition, this work indicates that the power consumption of transmitter can be significantly reduced up to 66% than the conventional ones. Through the analysis of channel capacity, the harmonic system is proved to outperform the single channel counterpart especially when SNR is low. To validate the correctness of the proposed concept, a series of experiments are carried out to emulate the developed theoretical models. For instance, a three-channel harmonic communication system is prototyped, involving certain RF harmonic components designed for demonstration. The retrieved signal strengths are examined with different phase setting of receiving LO, and various modulation techniques are applied for estimating the system performances. All measured results are in agreement with their simulated counterparts, thereby demonstrating the correctness and usefulness of the proposed theories and techniques for nonlinear communication systems of harmonic diversity. [ABSTRACT FROM PUBLISHER]

Wireless resource virtualization is a potential solution for meeting the increasing demand for mobile data services. Virtualization allows for more efficient utilization of the spectrum, reduces capital expenditures and operating expenditures, and can support higher peak rates. Device-to-device (D2D) communication as an underlay to cellular networks is also a potential solution to satisfy the data demand. Due to the proximity of devices and thus the higher signal-to-interference and noise ratio, higher data rates can be achieved using D2D communication. This is beneficial in cases of multimedia sharing where data can be broadcast to several nearby users. However, the interference that D2D pairs introduce to cellular users should be below a target threshold so as not to reduce their performance. In this paper, the problem of wireless resource virtualization with D2D communication underlaying the LTE network is formulated. Since the problem is an integer non-linear programming problem, it is divided into two smaller linear integer programs that are solved to optimality. Two lower complexity heuristic algorithms, each solving one of the subproblems are introduced. Results show that the heuristic achieves close to optimal results while having a much lower computational complexity. [ABSTRACT FROM PUBLISHER]

Wireless-powered cellular networks (WPCNs) are currently being investigated to ensure the reliability as well as improved battery lifetime of wireless devices. A WPCN leverages on a centralized base station (BS) that takes care of both wireless information and energy transfer. However, the harvested energy and, in turn, the spectral efficiency of uplink transmission of the users may significantly vary depending on the locations of the users and the channels used for energy and information transfer purposes. To this end, this paper theoretically characterizes the signal-to-noise ratio (SNR) outage zones in a WPCN and comparatively analyzes the performance of three useful configurations of dedicated energy sources that can potentially minimize the SNR outage zones. These configurations are: (i) harvesting energy from and information transfer to a full-duplex BS. This is considered as a baseline configuration; (ii) harvesting energy from symmetrically deployed power beacons (PBs) and information transfer to a conventional half-duplex BS; and (iii) harvesting energy from symmetrically deployed PBs that are colocated with the distributed antenna elements (DAEs) of a conventional half-duplex BS. For all the listed cases, we characterize the SNR outage probability and spectral efficiency of an arbitrarily located user within the cellular region. Based on the derived expressions, we also optimize the distance of the PBs from the BS to minimize the SNR outage probability and provide closed-form solutions for special cases. The optimum distance of the PBs is shown to be a function of the number of PBs and the coverage area of the BS. Numerical results validate the accuracy of the derived expressions, provide design insights related to WPCNs, and reveal the significance of the limited number of optimally placed PBs over a large number of randomly deployed PBs. [ABSTRACT FROM AUTHOR]