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The propagation loss of RF signals is a significant issue in simultaneous wireless information and power transfer (SWIPT) systems. Additionally, ensuring information security is crucial due to the broadcasting nature of wireless channels. To address these challenges, we exploit the potential of active intelligent reflecting surface (IRS) in a multiple-input and multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) SWIPT system. The active IRS provides better beamforming gain than the passive IRS, reducing the "double-fading" effect. Moreover, the noise introduced at the active IRS can be used as artificial noise (AN) to jam eavesdroppers. This paper formulates a secrecy sum-rate maximization problem related to precoding matrices, power splitting (PS) ratios, and the IRS matrix. Since the problem is highly non-convex, we propose a block coordinate descent (BCD)-based algorithm to find a sub-optimal solution. Moreover, we develop a heuristic algorithm based on the zero-forcing precoding scheme to reduce computational complexity. Simulation results show that the active IRS achieves a higher secrecy sum rate than the passive and non-IRS systems, especially when the transmit power is low or the direct link is blocked. Moreover, increasing the power budget at the active IRS can significantly improve the secrecy sum rate., Comment: 15 pages, 6 figures, 3 tables

Air-to-ground (A2G) networks, using unmanned aerial vehicles (UAVs) as base stations to serve terrestrial user equipments (UEs), are promising for extending the spatial coverage capability in future communication systems. Coordinated transmission among multiple UAVs significantly improves network coverage and throughput compared to a single UAV transmission. However, implementing coordinated multi-point (CoMP) transmission for UAV mobility requires complex cooperation procedures, regardless of the handoff mechanism involved. This paper designs a novel CoMP transmission strategy that enables terrestrial UEs to achieve reliable and seamless connections with mobile UAVs. Specifically, a computationally efficient CoMP transmission method based on the theory of Poisson-Delaunay triangulation is developed, where an efficient subdivision search strategy for a CoMP UAV set is designed to minimize search overhead by a divide-and-conquer approach. For concrete performance evaluation, the cooperative handoff probability of the typical UE is analyzed, and the coverage probability with handoffs is derived. Simulation results demonstrate that the proposed scheme outperforms the conventional Voronoi scheme with the nearest serving UAV regarding coverage probabilities with handoffs. Moreover, each UE has a fixed and unique serving UAV set to avoid real-time dynamic UAV searching and achieve effective load balancing, significantly reducing system resource costs and enhancing network coverage performance., Comment: 16 pages, 18 figures, 1 table

Narrowband Internet of Things (NB-IoT) is a technology specifically designated by the 3rd Generation Partnership Project (3GPP) to meet the explosive demand for massive machine-type communications (mMTC), and it is evolving to RedCap. Industrial companies have increasingly adopted NB-IoT as the solution for mMTC due to its lightweight design and comprehensive technical specifications released by 3GPP. This paper presents a system-level simulation framework for NB-IoT networks to evaluate their performance. The system-level simulator is structured into four parts: initialization, pre-generation, main simulation loop, and post-processing. Additionally, three essential features are investigated to enhance coverage, support massive connections, and ensure low power consumption, respectively. Simulation results demonstrate that the cumulative distribution function curves of the signal-to-interference-and-noise ratio fully comply with industrial standards. Furthermore, the throughput performance explains how NB-IoT networks realize massive connections at the cost of data rate. This work highlights its practical utility and paves the way for developing NB-IoT networks.

Unmanned aerial vehicle (UAV) communications have been widely accepted as promising technologies to support air-to-ground communications in the forthcoming sixth-generation (6G) wireless networks. This paper proposes a novel air-to-ground communication model consisting of aerial base stations served by UAVs and terrestrial user equipments (UEs) by integrating the technique of coordinated multi-point (CoMP) transmission with the theory of stochastic geometry. In particular, a CoMP set consisting of multiple UAVs is developed based on the theory of Poisson-Delaunay tetrahedralization. Effective UAV formation control and UAV swarm tracking schemes for two typical scenarios, including static and mobile UEs, are also developed using the multi-agent system theory to ensure that collaborative UAVs can efficiently reach target spatial positions for mission execution. Thanks to the ease of mathematical tractability, this model provides explicit performance expressions for a typical UE's coverage probability and achievable ergodic rate. Extensive simulation and numerical results corroborate that the proposed scheme outperforms UAV communications without CoMP transmission and obtains similar performance to the conventional CoMP scheme while avoiding search overhead., Comment: 14 pages, 9 figures, to appear in IEEE TWC

In the Internet of Things (IoT) networks, edge learning for data-driven tasks provides intelligent applications and services. As the network size becomes large, different users may generate distinct datasets. Thus, to suit multiple edge learning tasks for large-scale IoT networks, this paper performs efficient communication under the task-oriented principle by using the collaborative design of wireless resource allocation and edge learning error prediction. In particular, we start with multi-user scheduling to alleviate co-channel interference in dense networks. Then, we perform optimal power allocation in parallel for different learning tasks. Thanks to the high parallelization of the designed algorithm, extensive experimental results corroborate that the multi-user scheduling and task-oriented power allocation improve the performance of distinct edge learning tasks efficiently compared with the state-of-the-art benchmark algorithms., Comment: 16 pages, 8 figures; accepted for publication in IEEE TWC

This paper designs a novel ground-to-air communication scheme to serve unmanned aerial vehicles (UAVs) through legacy terrestrial base stations (BSs). In particular, a tractable coordinated multi-point (CoMP) transmission based on the geometry of Poisson-Delaunay triangulation is developed, which provides reliable and seamless connectivity for UAVs. An effective dynamic frequency allocation scheme is designed to eliminate inter-cell interference by using the theory of circle packing. For exact performance evaluation, the handoff probability of a typical UAV is characterized, and then the coverage probability with handoffs is attained. Simulation and numerical results corroborate that the proposed scheme outperforms the conventional CoMP scheme with three nearest cooperating BSs in terms of handoff and coverage probabilities. Moreover, as each UAV has a fixed and unique CoMP BS set, it avoids the real-time dynamic BS searching process, thus reducing the feedback overhead., Comment: 14 pages, 13 figures, to appear in IEEE Transactions on Wireless Communications

Efficient channel estimation is challenging in full-dimensional multiple-input multiple-output communication systems, particularly in those with hybrid digital-analog architectures. Under a compressive sensing framework, this letter first designs a uniform dictionary based on a spherical Fibonacci grid to represent channels in a sparse domain, yielding smaller angular errors in three-dimensional beamspace than traditional dictionaries. Then, a Bayesian inference-aided greedy pursuit algorithm is developed to estimate channels in the frequency domain. Finally, simulation results demonstrate that both the designed dictionary and the proposed Bayesian channel estimation outperform the benchmark schemes and attain a lower normalized mean squared error of channel estimation., Comment: 5 pages, 5 figures, submitted for possible publication

As a forerunner in 5G technologies, Narrowband Internet of Things (NB-IoT) will be inevitably coexisting with the legacy Long-Term Evolution (LTE) system. Thus, it is imperative for NB-IoT to mitigate LTE interference. By virtue of the strong temporal correlation of the NB-IoT signal, this letter develops a sparsity adaptive algorithm to recover the NB-IoT signal from legacy LTE interference, by combining $K$-means clustering and sparsity adaptive matching pursuit (SAMP). In particular, the support of the NB-IoT signal is first estimated coarsely by $K$-means clustering and SAMP algorithm without sparsity limitation. Then, the estimated support is refined by a repeat mechanism. Simulation results demonstrate the effectiveness of the developed algorithm in terms of recovery probability and bit error rate, compared with competing algorithms., Comment: 5 pages, 7 figures, to appear in IEEE Wireless Communications Letters

Wireless powered backscatter communications (WPBC) is capable of implementing ultra-low-power communication, thus promising in the Internet of Things (IoT) networks. In practice, however, it is challenging to apply WPBC in large-scale IoT networks because of its short communication range. To address this challenge, this paper exploits an unmanned ground vehicle (UGV) to assist WPBC in large-scale IoT networks. In particular, we investigate the joint design of network planning and dynamic resource allocation of the access point (AP), tag reader, and UGV to minimize the total energy consumption. Also, the AP can operate in either half-duplex (HD) or full-duplex (FD) multiplexing mode. Under HD mode, the optimal cell radius is derived and the optimal power allocation and transmit/receive beamforming are obtained in closed form. Under FD mode, the optimal resource allocation, as well as two suboptimal ones with low computational complexity, is developed. Simulation results disclose that dynamic power allocation at the tag reader rather than at the AP dominates the network energy efficiency while the AP operating in FD mode outperforms that in HD mode concerning energy efficienc, Comment: 15 pages, 7 figures, to appear in IEEE Transactions on Wireless Communications

This work studies multigroup multicasting transmission in cloud radio access networks (C-RANs) with simultaneous wireless information and power transfer, where densely packed remote radio heads (RRHs) cooperatively provide information and energy services for information users (IUs) and energy users (EUs), respectively. To maximize the weighted sum rate (WSR) of information services while satisfying the energy harvesting levels at EUs, an optimization of joint beamforming design for the fronthaul and access links is formulated, which is however neither smooth nor convex and is indeed NP-hard. To tackle this difficulty, the smooth and successive convex approximations are used to transform the original problem into a sequence of convex problems, and two first-order algorithms are developed to find the initial feasible point and the nearly optimal solution, respectively. Moreover, an accelerated algorithm is designed to improve the convergence speed by exploiting both Nesterov and heavy-ball momentums. Numerical results demonstrate that the proposed first-order algorithms achieve almost the same WSR as that of traditional second-order approaches yet with much lower computational complexity, and the proposed scheme outperforms state-of-the-art competing schemes in terms of WSR., Comment: To appear in IEEE Journal of Selected Topics in Signal Processing, 16 pages, 7 figures. arXiv admin note: text overlap with arXiv:2007.09920

Non-orthogonal multiple access (NOMA) is a promising solution for secure transmission under massive access. However, in addition to the uncertain channel state information (CSI) of the eavesdroppers due to their passive nature, the CSI of the legitimate users may also be imperfect at the base station due to the limited feedback. Under both channel uncertainties, the optimal power allocation and transmission rate design for a secure NOMA scheme is currently not known due to the difficulty of handling the probabilistic constraints. This paper fills this gap by proposing novel transformation of the probabilistic constraints and variable decoupling so that the security guaranteed sum-rate maximization problem can be solved by alternatively executing branch-and-bound method and difference of convex programming. To scale the solution to a truly massive access scenario, a first-order algorithm with very low complexity is further proposed. Simulation results show that the proposed first-order algorithm achieves identical performance to the conventional method but saves at least two orders of magnitude in computation time. Moreover, the resultant transmission scheme significantly improves the security guaranteed sum-rate compared to the orthogonal multiple access transmission and NOMA ignoring CSI uncertainty., Comment: 17 pages, 6 figures, accepted for publication in IEEE Journal on Selected Areas in Communications

This work investigates the energy-efficient resource allocation for layered-division multiplexing (LDM) based non-orthogonal multicast and unicast transmission in cell-free massive multiple-input multiple-output (MIMO) systems, where each user equipment (UE) performs wireless information and power transfer simultaneously. To begin with, the achievable data rates for multicast and unicast services are derived in closed form, as well as the received radio frequency (RF) power at each UE. Based on the analytical results, a nonsmooth and nonconvex optimization problem for energy efficiency (EE) maximization is formulated, which is however a challenging fractional programming problem with complex constraints. To suit the massive access setting, a first-order algorithm is developed to find both initial feasible point and the nearly optimal solution. Moreover, an accelerated algorithm is designed to improve the convergence speed. Numerical results demonstrate that the proposed first-order algorithms can achieve almost the same EE as that of second-order approaches yet with much lower computational complexity, which provides insight into the superiority of the proposed algorithms for massive access in cell-free massive MIMO systems., Comment: 19 pages, 8 figures, 2 tables, Accepted for publications in IEEE Journal on Selected Areas in Communications

Massive multiple-input multiple-output communications can achieve high-level security by concentrating radio frequency signals towards the legitimate users. However, this system is vulnerable in a Rician fading environment if the eavesdropper positions itself such that its channel is highly "similar" to the channel of a legitimate user. To address this problem, this paper proposes an angle aware user cooperation (AAUC) scheme, which avoids direct transmission to the attacked user and relies on other users for cooperative relaying. The proposed scheme only requires the eavesdropper's angle information, and adopts an angular secrecy model to represent the average secrecy rate of the attacked system. With this angular model, the AAUC problem turns out to be nonconvex, and a successive convex optimization algorithm, which converges to a Karush-Kuhn-Tucker solution, is proposed. Furthermore, a closed-form solution and a Bregman first-order method are derived for the cases of large-scale antennas and large-scale users, respectively. Extension to the intelligent reflecting surfaces based scheme is also discussed. Simulation results demonstrate the effectiveness of the proposed successive convex optimization based AAUC scheme, and also validate the low-complexity nature of the proposed large-scale optimization algorithms., Comment: 14 pages, 12 figures, to appear in IEEE Journal on Selected Areas in Communications

In this paper, a novel $3$D cellular model consisting of aerial base stations (aBSs) and aerial user equipments (aUEs) is proposed, by integrating the coordinated multi-point (CoMP) transmission technique with the theory of stochastic geometry. For this new $3$D architecture, a tractable model for aBSs' deployment based on the binomial-Delaunay tetrahedralization is developed, which ensures seamless coverage for a given space. In addition, a versatile and practical frequency allocation scheme is designed to eliminate the inter-cell interference effectively. Based on this model, performance metrics including the achievable data rate and coverage probability are derived for two types of aUEs: {\it i)} the general aUE (i.e., an aUE having distinct distances from its serving aBSs) and {\it ii)} the worst-case aUE (i.e., an aUE having equal distances from its serving aBSs). Simulation and numerical results demonstrate that the proposed approach emphatically outperforms the conventional binomial-Voronoi tessellation without CoMP. Insightfully, it provides a similar performance to the binomial-Voronoi tessellation which utilizes the conventional CoMP scheme; yet, introducing a considerably reduced computational complexity and backhaul/signaling overhead., Comment: 16 pages, 18 figures, Accepted by IEEE Transactions on Wireless Communications

Cloud radio access network (C-RAN) has been recognized as a promising architecture for next-generation wireless systems to \textcolor{black}{support} the rapidly increasing demand for higher data rate. However, the performance of C-RAN is limited by the backhaul capacities, especially for the wireless deployment. While C-RAN with fixed BS caching has been demonstrated to reduce backhaul consumption, it is more challenging to further optimize the cache allocation at BSs with multi-cluster multicast backhaul, where the inter-cluster interference induces additional non-convexity to the cache optimization problem. Despite the challenges, we propose an accelerated first-order algorithm, which achieves much higher content downloading sum-rate than a second-order algorithm running for the same amount of time. Simulation results demonstrate that, by simultaneously delivering the required contents to different multicast clusters, the proposed algorithm achieves significantly higher downloading sum-rate than those of time-division single-cluster transmission schemes. Moreover, it is found that the proposed algorithm allocates larger cache sizes to the farther BSs within the nearer clusters, which provides insight to the superiority of the proposed cache allocation., Comment: 14 pages, 8 figures, accepted by IEEE Transactions on Wireless Communications

Coordinated multi-point (CoMP) transmission is a cooperating technique among base stations (BSs) in a cellular network, with outstanding capability at inter-cell interference (ICI) mitigation. ICI is a dominant source of error, and has detrimental effects on system performance if not managed properly. Based on the theory of Poisson-Delaunay triangulation, this paper proposes a novel analytical model for CoMP operation in cellular networks. Unlike the conventional CoMP operation that is dynamic and needs on-line updating occasionally, the proposed approach enables the cooperating BS set of a user equipment (UE) to be fixed and off-line determined according to the location information of BSs. By using the theory of stochastic geometry, the coverage probability and spectral efficiency of a typical UE are analyzed, and simulation results corroborate the effectiveness of the proposed CoMP scheme and the developed performance analysis., Comment: 14 pages, 11 figures, accepted by IEEE Transactions on Wireless Communications

While machine-type communication (MTC) devices generate considerable amounts of data, they often cannot process the data due to limited energy and computational power. To empower MTC with intelligence, edge machine learning has been proposed. However, power allocation in this paradigm requires maximizing the learning performance instead of the communication throughput, for which the celebrated water-filling and max-min fairness algorithms become inefficient. To this end, this paper proposes learning centric power allocation (LCPA), which provides a new perspective on radio resource allocation in learning driven scenarios. By employing 1) an empirical classification error model that is supported by learning theory and 2) an uncertainty sampling method that accounts for different distributions at users, LCPA is formulated as a nonconvex nonsmooth optimization problem, and is solved using a majorization minimization (MM) framework. To get deeper insights into LCPA, asymptotic analysis shows that the transmit powers are inversely proportional to the channel gains, and scale exponentially with the learning parameters. This is in contrast to traditional power allocations where quality of wireless channels is the only consideration. Last but not least, a large-scale optimization algorithm termed mirror-prox LCPA is further proposed to enable LCPA in large-scale settings. Extensive numerical results demonstrate that the proposed LCPA algorithms outperform traditional power allocation algorithms, and the large-scale optimization algorithm reduces the computation time by orders of magnitude compared with MM-based LCPA but still achieves competing learning performance., Comment: 14 figures, 15 pages, to appear in IEEE Transactions on Wireless Communications

While backscatter communication emerges as a promising solution to reduce power consumption at IoT devices, the transmission range of backscatter communication is short. To this end, this work integrates unmanned ground vehicles (UGVs) into the backscatter system. With such a scheme, the UGV could facilitate the communication by approaching various IoT devices. However, moving also costs energy consumption and a fundamental question is: what is the right balance between spending energy on moving versus on communication? To answer this question, this paper proposes a joint graph mobility and backscatter communication model. With the proposed model, the total energy minimization at UGV is formulated as a mixed integer nonlinear programming (MINLP) problem. Furthermore, an efficient algorithm that achieves a local optimal solution is derived, and it leads to automatic trade-off between spending energy on moving versus on communication. Numerical results are provided to validate the performance of the proposed algorithm., Comment: Proc. IEEE ICC'19, Shanghai, China, May 2019, 6 pages

Collecting data from massive Internet of Things (IoT) devices is a challenging task, since communication circuits are power-demanding while energy supply at IoT devices is limited. To overcome this challenge, backscatter communication emerges as a promising solution as it eliminates radio frequency components in IoT devices. Unfortunately, the transmission range of backscatter communication is short. To facilitate backscatter communication, this work proposes to integrate unmanned ground vehicle (UGV) with backscatter data collection. With such a scheme, the UGV could improve the communication quality by approaching various IoT devices. However, moving also costs energy consumption and a fundamental question is: what is the right balance between spending energy on moving versus on communication? To answer this question, this paper studies energy minimization under a joint graph mobility and backscatter communication model. With the joint model, the mobility management and power allocation problem unfortunately involves nonlinear coupling between discrete variables brought by mobility and continuous variables brought by communication. Despite the optimization challenges, an algorithm that theoretically achieves the minimum energy consumption is derived, and it leads to automatic trade-off between spending energy on moving versus on communication in the UGV backscatter system. Simulation results show that if the noise power is small (e.g., -100 dBm), the UGV should collect the data with small movements. However, if the noise power is increased to a larger value (e.g., -60 dBm), the UGV should spend more motion energy to get closer to IoT users., Comment: Journal paper with 15 pages

One key feature of massive multiple-input multiple-output systems is the large number of antennas and users. As a result, reducing the computational complexity of beamforming design becomes imperative. To this end, the goal of this paper is to achieve a lower complexity order than that of existing beamforming methods, via the parallel accelerated random coordinate descent (ARCD). However, it is known that ARCD is only applicable when the problem is convex, smooth, and separable. In contrast, the beamforming design problem is nonconvex, nonsmooth, and nonseparable. Despite these challenges, this paper shows that it is possible to incorporate ARCD for multicast beamforming by leveraging majorization minimization and strong duality. Numerical results show that the proposed method reduces the execution time by one order of magnitude compared to state-of-the-art methods., Comment: IEEE ICASSP'19, Brighton, UK, May 2019

For Poisson-Delaunay triangulations in $d$-dimensional Euclidean space $\mathbb{R}^{d}$, a structured and computationally efficient form of the probability density function (PDF) of the volume of a typical cell is analytically derived in this paper. In particular, the ensuing PDF and the corresponding cumulative density function (CDF) are exact and unified, applicable to spaces of arbitrary dimension ($d \ge 1$). Then, the special cases and shape characteristics of the resulting PDF are thoroughly examined. Finally, various applications of the obtained distribution functions are outlined and, in particular, a novel coordinated multi-point transmission scheme based on Poisson-Delaunay triangulation is developed and the pertinent void cell effect is precisely evaluated by using the obtained distribution functions., Comment: 10 pages, 7 figures, 2 tables

In this paper, outage performance of hybrid automatic repeat request with incremental redundancy (HARQ-IR) is analyzed. Unlike prior analyses, time-correlated Nakagami-$m$ fading channel is considered. The outage analysis thus involves the probability distribution analysis of a product of multiple correlated shifted Gamma random variables and is more challenging than prior analyses. Based on the finding of the conditional independence of the received signal-to-noise ratios (SNRs), the outage probability is exactly derived by using conditional Mellin transform. Specifically, the outage probability of HARQ-IR under time-correlated Nakagami-$m$ fading channels can be written as a weighted sum of outage probabilities of HARQ-IR over independent Nakagami fading channels, where the weightings are determined by a negative multinomial distribution. This result enables not only an efficient truncation approximation of the outage probability with uniform convergence but also asymptotic outage analysis to further extract clear insights which have never been discovered for HARQ-IR even under fast fading channels. The asymptotic outage probability is then derived in a simple form which clearly quantifies the impacts of transmit powers, channel time correlation and information transmission rate. It is proved that the asymptotic outage probability is an inverse power function of the product of transmission powers in all HARQ rounds, an increasing function of the channel time correlation coefficients, and a monotonically increasing and convex function of information transmission rate. The simple expression of the asymptotic result enables optimal power allocation and optimal rate selection of HARQ-IR with low complexity. Finally, numerical results are provided to verify our analytical results and justify the application of the asymptotic result for optimal system design.

In this paper, the performance of an underlay multiple-input multiple-output (MIMO) cognitive radio system is analytically studied. In particular, the secondary transmitter operates in a spatial multiplexing transmission mode, while a zero-forcing (ZF) detector is employed at the secondary receiver. Additionally, the secondary system is interfered by multiple randomly distributed single-antenna primary users (PUs). To enhance the performance of secondary transmission, optimal power allocation is performed at the secondary transmitter with a constraint on the interference temperature (IT) specified by the PUs. The outage probability of the secondary receiver is explicitly derived in an exact closed-form expression. Also, some special cases of practical interest, including co-located PUs and massive MIMO, are discussed. Further, to mitigate instantaneous excessive interference onto PUs caused by the time-average IT, an iterative antenna reduction algorithm is developed for the secondary transmitter and, accordingly, the average number of transmit antennas is analytically computed. Extensive numerical and simulation results corroborate the effectiveness of our analysis., Comment: IEEE Transactions on Vehicular Technology, Accepted for publication, 2017

While two-way relaying is a promising way to enhance the spectral efficiency of wireless networks, the imbalance of relay-user distances may lead to excessive wireless power at the nearby-users. To exploit the excessive power, the recently proposed harvest-then-transmit technique can be applied. However, it is well-known that harvest-then-transmit introduces uplink-downlink coupling for a user. Together with the co-dependent relationship between paired users and interference among multiple user pairs, wirelessly powered two-way relay network suffers from the unique pairwise uplink-downlink coupling, and the joint uplink-downlink network design is nontrivial. To this end, for the one pair users case, we show that a global optimal solution can be obtained. For the general case of multi-pair users, based on the rank-constrained difference of convex program, a convergence guaranteed iterative algorithm with an efficient initialization is proposed. Furthermore, a lower bound to the performance of the optimal solution is derived by introducing virtual receivers at relay. Numerical results on total transmit power show that the proposed algorithm achieves a transmit power value close to the lower bound.

This paper analyzes the spectral efficiency of massive multiple-input multiple-output (MIMO) systems in both centralized and distributed configurations, referred to as C-MIMO and D-MIMO, respectively. By accounting for real environmental parameters and antenna characteristics, namely, path loss, shadowing effect, multi-path fading and antenna correlation, a novel comprehensive channel model is first proposed in closed-form, which is applicable to both types of MIMO schemes. Then, based on the proposed model, the asymptotic behavior of the spectral efficiency of the MIMO channel under both the centralized and distributed configurations is analyzed and compared in exact forms, by exploiting the theory of very long random vectors. Afterwards, a case study is performed by applying the obtained results into MIMO networks with circular coverage. In such a case, it is attested that for the D-MIMO of cell radius $r_{\mathrm{c}}$ and circular antenna array of radius~$r_{\mathrm{a}}$, the optimal value of~$r_{\mathrm{a}}$ that maximizes the average spectral efficiency is accurately established by $r_{\mathrm{a}}^{\mathrm{opt}}=r_{\mathrm{c}}/1.31$. Monte Carlo simulation results corroborate the developed spectral-efficiency analysis., Comment: IEEE Transactions on Communications, accepted for publication, January 2016; 12 pages, 8 figures

In this paper, spectrum-sharing technology is integrated into cellular systems to improve spectrum efficiency. Macrocell users are primary users (PUs) while those within local cells, e.g., femtocell users, or desiring cost-effective services, e.g., roamers, are identified as secondary users (SUs). The SUs share the spectrum resources of the PUs in a underlay way, thus the transmit power of a secondary is strictly limited by the primary's tolerable interference power. Given such constraints, a cooperative relaying transmission between a SU and the macrocell base station (BS) is necessary. In order to guarantee the success of dual-hop relaying and avoid multi-hop relaying, a new cooperative paradigm is proposed, where an idle PU (instead of a secondary as assumed in general) in the vicinity of a target SU is chosen to serve as a relaying node, thanks to the fact that any PU can always transmit to the macrocell BS directly. Moreover, two-way relaying strategy is applied at the chosen relaying node so as to further improve the spectral efficiency. Our results demonstrate that the proposed system is particularly suitable for delay-tolerant wireless services with asymmetric downlink/uplink traffics, such as e-mail checking, web browsing, social networking and data streaming, which are the most popular applications for SUs in spectrum-sharing cellular networks., Comment: IEEE Transactions on Vehicular Technology, accepted for publication, 11 pages, 7 figures

Far-field wireless power transfer (WPT) is a promising technique to resolve the painstaking power-charging problem inherent in various wireless terminals. This paper investigates the power transfer efficiency of the WPT segment in future communication systems in support of simultaneous power and data transfer, by means of analytically computing the time-average output direct current (DC) power at user equipments (UEs). In order to investigate the effect of channel variety among UEs on the average output DC power, different policies for the scheduling of the power transfer among the users are implemented and compared in two scenarios: homogeneous, whereby users are symmetric and experience similar path loss, and heterogeneous, whereby users are asymmetric and exhibit different path losses. Specifically, if opportunistic scheduling is performed among $N$ symmetric/asymmetric UEs, the power scaling laws are attained by using extreme value theory, and reveal that the gain in power transfer efficiency is $\ln{N}$ if UEs are symmetric whereas the gain is $N$ if UEs are asymmetric, compared with that of conventional round-robin scheduling. Thus, the channel variety among UEs inherent to the wireless environment can be exploited by opportunistic scheduling to significantly improve the power transfer efficiency when designing future wireless communication systems in support of simultaneous power and data transfer., Comment: 13 pages, to appear in IEEE Transactions on Signal Processing

Two major relay-selection strategies widely applied in cooperative decode-and-forward (DF) relaying networks, namely, reactive relay selection (RRS) and proactive relay selection (PRS), are generally looked upon as independent and studied separately. In this paper, RRS and PRS are proven to be equivalent with respect to the end-to-end outage probability from the first principle, i.e. their respective relay-selection criteria. On the other hand, RRS is shown to be superior to PRS with respect to the end-to-end symbol error rate. Afterwards, a case study of a general DF relaying system, subject to co-channel interferences and additive white Gaussian noise at both the relaying nodes and the destination, is performed to explicitly illustrate the aforementioned outage equivalence. These fundamental relations provide intuitive yet insightful performance benchmarks for comparing various applications of these two relay-selection strategies., Comment: 4 pages, to appear in IEEE Communications Letters

This paper studies the impact of co-channel interferences (CCIs) on the system performance of multi-hop amplify-and-forward (AF) relaying, in a simple and explicit way. For generality, the desired channels along consecutive relaying hops and the CCIs at all nodes are subject to Nakagami-$m$ fading with different shape factors. This study reveals that the diversity gain is determined only by the fading shape factor of the desired channels, regardless of the interference and the number of relaying hops. On the other hand, although the coding gain is in general a complex function of various system parameters, if the desired channels are subject to Rayleigh fading, the coding gain is inversely proportional to the accumulated interference at the destination, i.e. the product of the number of relaying hops and the average interference-to-noise ratio, irrespective of the fading distribution of the CCIs., Comment: 4 pages, 2 figures, accepted by IEEE Wireless Communications Letters

In spectrum-sharing cognitive radio systems, the transmit power of secondary users has to be very low due to the restrictions on the tolerable interference power dictated by primary users. In order to extend the coverage area of secondary transmission and reduce the corresponding interference region, multi-hop amplify-and-forward (AF) relaying can be implemented for the communication between secondary transmitters and receivers. This paper addresses the fundamental limits of this promising technique. Specifically, the effect of major system parameters on the performance of spectrum-sharing multi-hop AF relaying is investigated. To this end, the optimal transmit power allocation at each node along the multi-hop link is firstly addressed. Then, the extreme value theory is exploited to study the limiting distribution functions of the lower and upper bounds on the end-to-end signal-to-noise ratio of the relaying path. Our results disclose that the diversity gain of the multi-hop link is always unity, regardless of the number of relaying hops. On the other hand, the coding gain is proportional to the water level of the optimal water-filling power allocation at secondary transmitter and to the large-scale path-loss ratio of the desired link to the interference link at each hop, yet is inversely proportional to the accumulated noise, i.e. the product of the number of relays and the noise variance, at the destination. These important findings do not only shed light on the performance of the secondary transmissions but also benefit system designers improving the efficiency of future spectrum-sharing cooperative systems., Comment: 12 pages, 6 figures

In this paper, linear beamforming design for amplify-and-forward relaying cellular networks is considered, in which base station, relay station and mobile terminals are all equipped with multiple antennas. The design is based on minimum mean-square-error criterion, and both uplink and downlink scenarios are considered. It is found that the downlink and uplink beamforming design problems are in the same form, and iterative algorithms with the same structure can be used to solve the design problems. For the specific cases of fully loaded or overloaded uplink systems, a novel algorithm is derived and its relationships with several existing beamforming design algorithms for conventional MIMO or multiuser systems are revealed. Simulation results are presented to demonstrate the performance advantage of the proposed design algorithms., Comment: 24 Pages, 8 figures, Submitted to Wireless Communications April 2010; Wireless Communications April 2010

In this paper, robust transceiver design with Tomlinson-Harashima precoding (THP) for multi-hop amplify-and-forward (AF) multiple-input multiple-output (MIMO) relaying systems is investigated. At source node, THP is adopted to mitigate the spatial intersymbol interference. However, due to its nonlinear nature, THP is very sensitive to channel estimation errors. In order to reduce the effects of channel estimation errors, a joint Bayesian robust design of THP at source, linear forwarding matrices at relays and linear equalizer at destination is proposed. With novel applications of elegant characteristics of multiplicative convexity and matrix-monotone functions, the optimal structure of the nonlinear transceiver is first derived. Based on the derived structure, the transceiver design problem reduces to a much simpler one with only scalar variables which can be efficiently solved. Finally, the performance advantage of the proposed robust design over non-robust design is demonstrated by simulation results., Comment: IEEE Journal on Selected Areas in Communications - Special Issue on Theories and Methods for Advanced Wireless Relays The final version and several typos have been corrected

The opportunistic beamforming in the downlink of multiple-input single-output (MISO) systems forms $N$ transmit beams, usually, no more than the number of transmit antennas $N_t$. However, the degrees of freedom in this downlink is as large as $N_t^2$. That is, at most $N_t^2$ rather than only $N_t$ users can be simultaneously transmitted and thus the scheduling latency can be significantly reduced. In this paper, we focus on the opportunistic beamforming schemes with $N_t