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Caching the most popular contents at the wireless network edge such as small-cell base stations (SBSs) is a smart way of reducing duplicated content transmissions and offloading the mobile data traffic in the network backhaul. Currently, most small-cell caching strategies are conceived, designed, and optimized based on the global content request probability (GCRP), with very limited consideration of the individual content request probability (ICRP) reflecting personal preferences. To enable more efficient wireless caching, in this paper, we propose a novel localized deterministic caching framework, drawing upon the recent advances in recommendation systems based on machine learning techniques. By introducing the concept of the rating matrix, we first propose a new Bayesian learning method to predict personal preferences and estimate the ICRP. This crucial information is then incorporated into our caching strategy for maximizing the system throughput, or equivalently, minimizing the download latency, where a deterministic caching algorithm based on reinforcement learning is proposed to optimize the content placement. To this end, we extend the framework to enable device-to-device (D2D) connections to further reduce the download delay, and also design a feedback mechanism to improve the accuracy in the ICRP estimation. Our simulation results verified that with the estimated ICRP and the proposed caching strategy, the proposed framework can significantly outperform the existing methods in terms of hit rate and system throughput. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the feasibility of wireless edge caching in a hybrid millimeter-wave (mmWave)–micro-wave ($\mu $ Wave) network. Considering the average success probability (ASP) of file delivery as the performance metric, we derive expressions for the association probability of the typical user to the mmWave and $\mu $ Wave networks using stochastic geometric tools. Accordingly, we provide an upper bound on the ASP of file delivery and formulate the content caching placement scheme as an optimization problem with respect to caching probabilities, which jointly optimizes the ASP of file delivery considering both content placement and delivery phases. To simplify the non-convex problem and obtain design insights, we split it into two scenarios: 1) noise-limited and 2) interference-limited, and then propose optimal caching placement algorithms for both. We numerically evaluate the performance of the proposed schemes under several essential factors, such as content popularity, cache size, target data rate, blockages in the mmWave network, BS density, and path loss and also compare it with other common proactive caching schemes, namely uniform caching, caching $M$ most popular files, and random caching. Numerical results demonstrate the superiority of the proposed caching scheme over others, albeit certain trade-offs. [ABSTRACT FROM AUTHOR]

Simultaneous wireless information and power transfer (SWIPT) is characterized by the ambiguous role of multi-user interference. In short, the beneficial effect of multi-user interference on RF energy harvesting is obtained at the price of a reduced link capacity, thus originating nontrivial tradeoffs between the achievable information rate and the harvestable energy. Arguably, in indoor environments, this tradeoff might be affected by the propagation loss due to blockage objects like walls. Hence, a couple of fundamental questions arise. How much must the network elements be densified to counteract the blockage attenuation? Is blockage always detrimental on the achievable rate-energy tradeoff? In this paper, we analyze the performance of an indoor multiple-input multiple-output SWIPT-enabled network in the attempt to shed a light of those questions. The effects of the obstacles are examined with the help of a stochastic geometry approach in which the locations of energy sources (also referred to as power heads) are distributed by using a Poisson point process and walls are generated through a Manhattan Poisson line process. The stochastic behavior of the signal attenuation and the multi-user interference is studied to obtain the joint complementary cumulative distribution function of information rate and harvested power. Theoretical results are validated through Monte Carlo simulations. Eventually, the rate-energy tradeoff is presented as a function of the density of walls to emphasize the cross-dependences between the deployment of the network elements and the macro parameters characterizing the topology of the venue. [ABSTRACT FROM AUTHOR]

In this paper, we consider a wireless powered multi-relay network in which a multi-antenna hybrid access point underlaying a cellular system transmits information to distant receivers. Multiple relays capable of energy harvesting are deployed in the network to assist the information transmission. The hybrid access point can wirelessly supply energy to the relays, achieving multi-user gains from signal and energy cooperation. We propose a joint optimization for signal beamforming of the hybrid access point as well as wireless energy harvesting and collaborative beamforming strategies of the relays. The objective is to maximize the network throughput subject to probabilistic interference constraints at the cellular user equipment. We formulate the throughput maximization with both the time-switching and power-splitting schemes, which impose very different couplings between the operating parameters for wireless power and information transfer. Although the optimization problems are inherently non-convex, they share similar structural properties that can be leveraged for an efficient algorithm design. In particular, by exploiting monotonicity in the throughput, we maximize it iteratively via customized polyblock approximation with reduced complexity. The numerical results show that the proposed algorithms can achieve close to optimal performance in terms of the energy efficiency and throughput [ABSTRACT FROM AUTHOR]

The existing proactive caching policies are designed by assuming that all users request contents with identical activity level at uniformly distributed or known locations, among which most of the policies are optimized by assuming that user preference is identical to content popularity. However, these assumptions are not true based on the recent data analysis. In this paper, we investigate what happens without these assumptions. To this end, we establish a framework to optimize caching policy for base stations exploiting heterogeneous user preference, activity level, and spatial locality. We derive success probability and average rate of each user as utility function, respectively, and obtain the optimal caching policy maximizing a weighted sum of average utility (reflecting network performance) and minimal utility of users (reflecting user fairness). To investigate the intertwined impact of individual user request behavior on caching, we provide an algorithm to synthesize user preference from given content popularity and activity level with controlled preference similarity and validate the algorithm with the real datasets. Analysis and simulation results show that exploiting individual user behavior can improve both network performance and user fairness, and the gain increases with the skewness of spatial locality, and the heterogeneity of user preference and activity level. [ABSTRACT FROM AUTHOR]

Radar and wireless communication coexistence is considered in this paper as a possible solution to face the exploding demand and rising congestion in wireless networks. The transmission medium is modeled as an AWGN channel with additive radar interference. Standard constellations are not optimal in this context, and an auto-encoder (AE) is used to design proper constellations and corresponding receiver devices. AE is a powerful tool in neural networks that shares strong similarities with communication systems. This technique is particularly relevant in the lack of an analytical expression of the loss function. In the asymptotic region (high interference regime), the optimal constellation shape is known and the AE always converges toward this optimal solution. In the other regions, the AE is able to yield solutions that outperform the standard configurations. Several demapping alternatives are also considered leading to the conclusion that it is possible to maintain the communication link in the presence of radar interference independently of the interference power. This is a step further compared with previous works in which solutions were limited to low or high interference regimes. [ABSTRACT FROM AUTHOR]

In wireless distributed storage systems, storage nodes are connected by wireless channels, which are broadcast in nature. This paper exploits this unique feature to design an efficient repair mechanism, called broadcast repair, for wireless distributed storage systems in the presence of multiple-node failures. Due to the broadcast nature of wireless transmission, we advocate a new measure on repair performance called repair-transmission bandwidth. In contrast to repair bandwidth, which measures the average number of packets downloaded by a newcomer to replace a failed node, repair-transmission bandwidth measures the average number of packets transmitted by helper nodes per failed node. The storage system we considered can undergo an unlimited number of repair rounds. We obtain an upper bound on the maximum file size that can be supported by a cut analysis of a finite graph. The achievability is shown by codes constructed over a refined information flow graph, which is unbounded. In addition, the optimal storage-bandwidth tradeoff is obtained. The performance of broadcast repair is compared both analytically and numerically with that of cooperative repair, the basic repair method for wired distributed storage systems with multiple-node failures. While cooperative repair is based on the idea of allowing newcomers to exchange packets, broadcast repair is based on the idea of allowing a helper to broadcast packets to all newcomers simultaneously. We show that broadcast repair outperforms cooperative repair, offering a better tradeoff between storage efficiency and repair-transmission bandwidth. [ABSTRACT FROM AUTHOR]

This paper studies interference exploitation techniques for secure beamforming design in simultaneous wireless information and power transfer in multiple-input single-output systems. In particular, multiuser interference (MUI) and artificially generated noise (AN) signals are designed as constructive to the information receivers (IRs) yet kept disruptive to potential eavesdropping by the energy receivers. The objective is to improve the received signal-to-interference and noise ratio (SINR) at the IRs by exploiting the MUI and AN power in an attempt to minimize the total transmit power. We first propose second-order cone programming-based solutions for the perfect channel state information (CSI) case by defining strong upper and lower bounds on the energy harvesting (EH) constraints. We then provide semidefinite programming-based solutions for the problems. In addition, we also solve the worst case harvested energy maximization problem under the proposed bounds. Finally, robust beamforming approaches based on the above are derived for the case of imperfect CSI. Our results demonstrate that the proposed constructive interference precoding schemes yield huge saving in transmit power over conventional interference management schemes. Most importantly, they show that, while the statistical constraints of conventional approaches may lead to instantaneous SINR as well as EH outages, the instantaneous constraints of our approaches guarantee both constraints at every symbol period. [ABSTRACT FROM AUTHOR]

We study the optimal resource allocation in the MIMO-based wireless powered underground sensor network (WPUSN) for throughput maximization. Compared to existing WPUSNs that rely on single-antenna wireless power transfer techniques to transmit geological data in real time, the MIMO-based WPUSN can be adaptively replenished by beamforming. Note that, WPUSN has two remarkable features: the severe wireless path loss and diverse data traffic demands from different underground sensors. Further, by considering the quality of service (QoS) with respect to diverse data traffic demands and communication reliability, the throughput of the network is considered as a crucial measure, which suffers from a significant loss since it has to encounter a seriously unreasonable energy scarcity under the strong-heterogeneity underground environment. To this end, the MIMO is used to eliminate the unreasonable distribution of harvested energy resources and improve effective throughput for WPUSNs. In this paper, we formulate a non-convex optimization problem to maximize the system throughput in MIMO-based WPUSNs with QoS assurance. Specifically, we find there exists no mutual forbearance between the time allocation and the beamforming weight, and transform this non-convex problem to a solvable convex-constrained problem with convex sub-problems. Finally, we give a closed-form solution and show its advantages by simulations. [ABSTRACT FROM AUTHOR]

This paper proposes a novel design of cooperative non-orthogonal layered multicast multiple access in a heterogeneous network, where the information is encoded into the messages of high priority (HP) and low priority (LP). Two types of multicast users coexist in the network: 1) regular users (RUs), which are located far away from the base station (BS) and expect to decode only the HP message (due to the weak channels), and 2) advanced users (AUs), which are located close to the BS and expect to decode both HP and LP messages. To improve the reliability of layered multicast, we consider that the successful AUs (those AUs who successfully decode the HP and LP messages) serve as potential relays to assist other AUs/RUs. Based on this idea, two novel cooperation strategies are proposed for different cases of channel information availability. For each proposed strategy, we derive closed-form exact outage probabilities of AUs and RUs and then further analyze their diversity orders. Moreover, considering that the layered multicast is outage-constrained, we theoretically evaluate the energy consumption of both strategies and demonstrate their energy saving gains over the direct non-orthogonal multiple access for layered multicast. Finally, our theoretical analysis is verified by numerical results, and the advantages of the proposed strategies are also demonstrated. [ABSTRACT FROM AUTHOR]

Chemical reactions are a prominent feature of molecular communication systems, with no direct parallels in wireless communications. While chemical reactions may be used inside the transmitter nodes, receiver nodes, or the communication medium, we focus on its utility in the medium in this paper. Such chemical reactions can be used to perform computation over the medium as molecules diffuse and react with each other (physical-layer computation). We propose the use of chemical reactions for the following purposes: 1) to reduce signal-dependent observation noise of receivers by reducing the signal density; 2) to realize molecular physical-layer network coding (PNC) by performing the natural XOR operation inside the medium; and 3) to reduce the inter-symbol interference (ISI) of other transmitters by canceling out the remaining molecules from previous transmissions. To make the ideas formal, we consider an explicit two-way relaying example with a transparent receiver (which has a signal-dependent noise). The proposed ideas are used to define a modulation scheme (which we call the PNC scheme). We compare the PNC with a previously proposed scheme for this problem, where the XOR operation is performed at the relay node (using a molecular logic gate). We call the latter, the straightforward network coding (SNC). It is observed that in addition to the simplicity of the proposed PNC scheme, it outperforms the SNC scheme especially when we consider ISI. [ABSTRACT FROM AUTHOR]

In this paper, the effective use of multiple quadrotor drones as an aerial antenna array that provides wireless service to ground users is investigated. In particular, under the goal of minimizing the airborne service time needed for communicating with ground users, a novel framework for deploying and operating a drone-based antenna array system whose elements are single-antenna drones is proposed. In the considered model, the service time is minimized by minimizing the wireless transmission time as well as the control time that is needed for movement and stabilization of the drones. To minimize the transmission time, first, the antenna array gain is maximized by optimizing the drone spacing within the array. In this case, using perturbation techniques, the drone spacing optimization problem is addressed by solving successive, perturbed convex optimization problems. Then, according to the location of each ground user, the optimal locations of the drones around the array’s center are derived such that the transmission time for the user is minimized. Given the determined optimal locations of drones, the drones must spend a control time to adjust their positions dynamically so as to serve multiple users. To minimize this control time of the quadrotor drones, the speed of rotors is optimally adjusted based on both the destinations of the drones and external forces (e.g., wind and gravity). In particular, using bang–bang control theory, the optimal rotors’ speeds as well as the minimum control time are derived in closed-form. Simulation results show that the proposed approach can significantly reduce the service time to ground users compared with a fixed-array case in which the same number of drones form a fixed uniform antenna array. The results also show that, in comparison with the fixed-array case, the network’s spectral efficiency can be improved by 32% while leveraging the drone antenna array system. Finally, the results reveal an inherent tradeoff between the control time and transmission time while varying the number of drones in the array. [ABSTRACT FROM AUTHOR]

The interest in polar codes has been increasing significantly since their adoption for use in the 5th generation wireless systems standard. Successive cancellation (SC) decoding algorithm has low implementation complexity, but yields mediocre error-correction performance at the code lengths of interest. SC-Flip algorithm improves the error-correction performance of SC by identifying possibly erroneous decisions made by SC and re-iterates after flipping one bit. It was recently shown that only a portion of bit-channels are most likely to be in error. In this paper, we investigate the average log-likelihood ratio (LLR) values and their distribution related to the erroneous bit-channels, and develop the Thresholded SC-Flip (TSCF) decoding algorithm. We also replace the LLR selection and sorting of SC-Flip with a comparator to reduce the implementation complexity. Simulation results demonstrate that for practical code lengths and a wide range of rates, TSCF shows negligible loss compared with the error-correction performance obtained when all single-errors are corrected. At matching maximum iterations, TSCF has an error-correction performance gain of up to 0.45 dB compared with SC-Flip decoding. At matching error-correction performance, the computational complexity of TSCF is reduced by up to 40% on average and requires up to $5\times $ lower maximum number of iterations. [ABSTRACT FROM AUTHOR]

This paper considers a wireless communication network consisting of multiple interfering multicast sessions. Different from a unicast system where each transmitter has only one receiver, in a multicast system, each transmitter has multiple receivers and broadcasts a common message to all of them. It is a well-known result for wireless unicast systems that the feasibility of a signal-to-interference-plus-noise power ratio (SINR) without power constraint is decided by the spectral radius of a nonnegative matrix. We generalize this result and obtain necessary and sufficient conditions for the feasibility of an SINR in a wireless multicast system with and without power constraint. The feasible SINR region and its geometric properties are studied. Besides, an iterative algorithm is proposed, which can efficiently check the feasibility condition and compute the boundary points of the feasible SINR region. [ABSTRACT FROM AUTHOR]

Massive multiple-input multiple-output (MIMO) systems operating within the millimeter wave frequency range offer exciting opportunities for the future fifth-generation (5G) wireless networks. While the increased bandwidth and spectral efficiency are attractive, transitioning to millimeter massive MIMO presents significant challenges with respect to blockages, high attenuation, and channel estimation errors. To address these challenges, this paper evaluates the outage performance of a millimeter wave cellular network using massive MIMO under a stochastic set-up subject to pilot contamination and matched-filter precoding. We model the cellular users and base stations with Poisson point processes. Furthermore, we consider blockages from random objects, and employ different path loss and fading models for the line-of-sight (LOS) and non-line-of-sight scenarios. Moreover, both fixed power transmissions and path loss inversion-based power control are considered along with the sectored antenna patterns. Using stochastic geometry, we derive the moment generating function of the interference experienced by a typical cellular user and its outage probability. It is observed that the environments with different path loss exponents have varying behaviour for similar blockage sizes and densities. In addition, the ratio of the number of cellular users to that of base stations, and the antenna beamwidth are critical parameters affecting the outage performance. [ABSTRACT FROM AUTHOR]

Mobility, node density, and the demand for large volumes of data exchange have aggravated competition for limited resources in the wireless communications environment. This paper proposes a novel MAC scheme called segmentation MAC (SMAC), which can be used in large-scale vehicle-to-everything (V2X) communication networks. SMAC functions to support the dynamical allocation of radio channels. It is compatible with the asynchronous multi-channel MAC sub-layer extension of the IEEE 802.11p standard. A key innovate feature of SMAC is that the segmentation of the network and channel allocations are dynamically adjusted according to the density of vehicles. We also propose a novel efficient forwarding mechanism to ensure inter-segment connectivity. To evaluate the performance of inter-segment connectivity, a rigorous analytical model is proposed to measure the multi-hop dissemination latency. The proposal is evaluated in network simulator NS2 as well as the standard IEEE 1609.4 and two asynchronous multi-channel MAC benchmarks. Both analytical and simulation results demonstrate better effectiveness of the proposed scheme compared with the existing similar schemes in the literature. [ABSTRACT FROM AUTHOR]

This paper investigates the optimal signaling schemes and capacities of non-coherent correlated multiple-input single-output (MISO) channels in fast Rayleigh fading. We consider both channels under per-antenna power constraints as well as channels under joint per-antenna and sum power constraints. For per-antenna power constraint channels, we first establish the convex and compact properties of the feasible sets, and demonstrate the existence of optimal input distribution and the uniqueness of optimal effective magnitude input distribution. By exploiting the solutions of a quadratic optimization problem, we show that the Kuhn–Tucker condition on the optimal inputs can be simplified to a single dimension. As a result, we can apply the Identity Theorem to show the discrete and finite nature of the optimal effective magnitude distribution, with a mass point located at the origin. By using this distribution, we then construct a finite and discrete optimal input vector distribution. The use of this input allows us to determine the capacity gain of MISO over SISO via the phase solutions of a constrained quadratic optimization problem on a sphere, which can be obtained using a proposed penalized optimization algorithm. We also extend the results to MISO channels subject to the joint per-antenna and sum power constraints. Under this consideration, it is shown that not all per-antenna constraints are active. While the finiteness and discreteness of the optimal effective magnitude and the optimal input vector distributions still hold, the optimal phases and the optimal power allocation among the transmit antennas need to be determined simultaneously via a quadratic optimization problem under inequality constraints. These solutions can finally be used to obtain the MISO capacity gain. [ABSTRACT FROM AUTHOR]

In this paper, we propose a simple yet powerful mapping scheme that converts any conventional square-matrix-based differential space-time coding (DSTC) into a nonsquare-matrix-based DSTC. This allows DSTC schemes to be used practically in open-loop large-scale multiple-input multiple-output scenarios. Our proposed scheme may be viewed as the differential counterpart of coherent spatial modulation (SM), of the generalized SM, of Bell Laboratories layered space-time architecture, and of subcarrier-index modulation. The fundamental impediment of the existing DSTC schemes is the excessive complexity imposed by the unitary constraint. Specifically, the transmission rate of conventional DSTC schemes decays as the number of transmit antennas increases. Our proposed scheme eliminates this impediment and thus achieves a significantly higher transmission rate. We introduce four novel construction methods for the nonsquare codewords, some of which include an arbitrary number of nonzero elements in each codeword column. Our analysis shows that the proposed encoding technique reduces the complexity of both the inverse Fourier transform and the detection processes. Our proposed scheme is shown to approach the performance of its coherent counterpart for low-mobility scenarios, where the number of transmit antennas is increased up to 256. [ABSTRACT FROM AUTHOR]

In this paper, a fundamental study of energy efficiency (EE) optimization for coordinated multi-point (CoMP) simultaneous wireless information and power transfer (SWIPT) heterogeneous networks (HetNets) is provided. We aim to optimize the EE while satisfying certain quality-of-service requirements in regard to transmission rate and energy harvesting at both the macro cell and small cells. The corresponding joint beamforming and power allocation in the presence of intra- and inter-cell interference constitutes an EE maximization problem that is non-convex, and hence, very challenging to solve. In order to solve this problem, we propose to separate the beamforming design and power allocation processes. First, we adopt linear zero-forcing (ZF) beamforming to suppress the multi-user interference from both the energy harvesting users (EH-UEs) as well as the information decoding UEs (ID-UEs), thus transforming the HetNet under consideration to a virtual point-to-point system. An efficient power allocation algorithm is then developed to maximize the corresponding EE. On the other hand, the ZF strategy does not utilize the notion that interference benefits the EH-UEs. As a result, we propose a partial ZF approach by differentiating the EH-UEs and ID-UEs in order to further improve the EE. Our findings show that the EE can be significantly improved through the integration of CoMP-SWIPT in HetNets. [ABSTRACT FROM AUTHOR]

Channel asymmetry and channel correlation are frequently encountered in wireless communication systems. Orthogonal transmission schemes are usually inefficient in dealing with these problems. In this paper, in order to boost the throughput performance for multiple-input multiple-output broadcast communications in the presence of channel asymmetry and/or channel correlation, we study optimization algorithms for multi-user superposition coding beamforming (SCBF). Starting with solving the minimum power optimization problem for the two-user case, we derive the optimal solution structure of the problem and two types of dedicated algorithms that could efficiently find the optimal solutions with all parameter setups. Extensions are then made to the same problem with the signals of more than two users multiplexed in the power domain as well as to the rate region computation problem. Finally, to adapt our algorithms to more general cases, novel hybrid precoding schemes are proposed, where certain user grouping strategy is used to combine zero-forcing beamforming and SCBF. Numerical simulations are provided to show that with our algorithms, a considerable performance gain is achieved by SCBF compared to the other orthogonal transmission methods. [ABSTRACT FROM AUTHOR]

In this paper, the problem of misinformation propagation is studied for an Internet of Battlefield Things (IoBT) system, in which an attacker seeks to inject false information in the IoBT nodes in order to compromise the IoBT operations. In the considered model, each IoBT node seeks to counter the misinformation attack by finding the optimal probability of accepting given information that minimizes its cost at each time instant. The cost is expressed in terms of the quality of information received as well as the infection cost. The problem is formulated as a mean-field game with multiclass agents, which is suitable to model a massive heterogeneous IoBT system. For this game, the mean-field equilibrium is characterized, and an algorithm based on the forward backward sweep method is proposed to find the mean-field equilibrium. Then, the finite-IoBT case is considered, and the conditions of convergence of the equilibria in the finite case to the mean-field equilibrium are presented. Numerical results show that the proposed scheme can achieve a 1.2-fold increase in the quality of information compared with a baseline scheme, in which the IoBT nodes are always transmitting. The results also show that the proposed scheme can reduce the proportion of infected nodes by 99% compared with the baseline. [ABSTRACT FROM AUTHOR]

Mobile edge computing (MEC) is expected to provide cloud-like capacities for mobile users (MUs) at the edge of wireless networks. However, deploying MEC systems faces many challenges, one of which is to achieve an efficient distributed offloading mechanism for multiple users in time-varying wireless environments. In this paper, we study a multi-user multi-edge-node computation offloading problem. Since edge nodes’ communication and computing capacities are limited which leads resource contention when many MUs offload to the same edge node at the same time, we formulate this problem as a non-cooperative exact potential game (EPG), where each MU, in each time slot, selfishly maximizes its number of processed central processor unit (CPU) cycles and reduces its energy consumption. Assuming that channel information is static and available to MUs, we show that MUs could achieve a Nash equilibrium via a best response-based offloading mechanism. Next, we extend the problem to a practical scenario, where the number of processed CPU cycles is time-varying and unknown to MUs because of the uncertain channel information. In this case, we adopt an unknown payoff game framework and prove that the EPG properties still hold. Then, we propose a model-free reinforcement learning offloading mechanism which helps MUs learn their long-term offloading strategies to maximize their long-term utilities. Numerical results illustrate that our proposed algorithm for unknown CSI outperforms other schemes, such as local processing and random assignment, and achieves up to 87.87% average long-term payoffs compared to the perfect CSI case. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a trellis-coded space shift keying modulation scheme, called trellis-coded space–time shift keying (TC-STSK), which combines trellis-coded modulation with space shift keying. By analyzing the rank criterion using a graph theoretic approach, we maximize the number of unique differences between pairwise codewords as the code design goal. We discuss the code design principles for achieving diversity, and propose a design algorithm that is mostly suitable for rate- $1/n$ codes, where $n$ is the number of the code output bits. We then propose a diversity adaptation mechanism by selecting only the codewords with desired diversity, and use it to design higher rate codes that achieve full diversity. We also provide the code designs and a modified soft Viterbi decoder for such schemes. Simulation results show that the proposed scheme can achieve diversity orders expected from the theoretical analysis, and that increasing the number of shift registers and transmit antennas improves the performance of the TC-STSK scheme. The results also show that TC-STSK outperforms a space–time trellis code with the same bit rate and the number of shift registers. [ABSTRACT FROM AUTHOR]

The use of unmanned aerial vehicles (UAVs) as communication platforms is of great significance in future wireless networks, especially for on-demand deployment in temporary events and emergency situations. Although prior works have shown the performance improvement by exploiting the UAV’s mobility, they mainly focus on delay-tolerant applications. As delay requirements fundamentally limit the UAV’s mobility, it remains unknown whether the UAV is able to provide any performance gain in delay-constrained communication scenarios. Motivated by the above, we study, in this paper, an UAV-enabled orthogonal frequency-division multiple access (OFDMA) network where an UAV is dispatched as the mobile base station (BS) to serve a group of users on the ground. We consider a minimum-rate ratio (MRR) for each user, defined as the minimum instantaneous rate required over the average achievable throughput, to flexibly adjust the percentage of its delay-constrained data traffic. Under a given set of constraints on the users’ MRRs, we aim to maximize the minimum average throughput of all users by jointly optimizing the UAV trajectory and OFDMA resource allocation. First, we show that the max–min throughput in general decreases as the users’ MRRs become larger, which reveals a fundamental throughput-delay tradeoff in UAV-enabled communications. Next, we propose an iterative parameter-assisted block coordinate descent method to optimize the UAV trajectory and OFDMA resource allocation alternately, by applying the successive convex optimization and the Lagrange duality, respectively. Furthermore, an efficient and systematic UAV trajectory initialization scheme is proposed based on the simple circular trajectory. Finally, simulation results are provided to verify our theoretical findings and demonstrate the effectiveness of our proposed designs. [ABSTRACT FROM AUTHOR]

The millimeter-wave (mmWave) full-dimensional (FD) MIMO system employs planar arrays at both the base station and the user equipment and can simultaneously support both azimuth and elevation beamforming. In this paper, we propose atomic-norm-based methods for mm-wave FD-MIMO channel estimation under both uniform planar arrays (UPA) and non-uniform planar arrays (NUPA). Unlike existing algorithms, such as compressive sensing (CS) or subspace methods, the atomic-norm-based algorithms do not require to discretize the angle spaces of the angle of arrival and angle of departure into grids, thus provide much better accuracy in estimation. In the UPA case, to reduce the computational complexity, the original large-scale atomic norm minimization problem is approximately reformulated as a semi-definite program (SDP) containing two decoupled two-level Toeplitz matrices. The SDP is then solved via the alternating direction method of multipliers where each iteration involves only closed-form computations. In the NUPA case, the atomic-norm-based formulation for channel estimation becomes nonconvex and a gradient-decent-based algorithm is proposed to solve the problem. Simulation results show that the proposed algorithms achieve better performance than the CS-based and subspace-based algorithms. [ABSTRACT FROM AUTHOR]

In this paper, new enhanced cognitive radio networks (E-CRNs) based on spectrum sharing (SS) and spectrum aggregation (SA) are proposed for fifth generation (5G) wireless networks. The E-CRNs jointly exploit the licensed spectrum shared with the primary user (PU) networks and the unlicensed spectrum aggregated from the industrial, scientific, and medical bands. The PU networks include TV systems in TV white space and different incumbent systems in the long term evolution time division duplexing bands. The harmful interference from the E-CRNs to the PU networks are delicately controlled. Furthermore, the coexistence between the E-CRNs and other unlicensed systems, such as WiFi, is studied. The E-CRNs framework including dynamic spectrum management (DSM) is designed for the key parameters of licensed SS and unlicensed SA. The essential tradeoff between sharing efficiency and aggregation efficiency for the E-CRNs is discussed. Based on this tradeoff, a spectrum lean-management scheme is proposed to fulfill the DSM. Moreover, a water-filling algorithm is designed to dynamically access the available spectrum. Numerical results demonstrate that the proposed E-CRNs can significantly improve the system performance in terms of data rate, outage probability, and spectrum efficiency. In particular, the E-CRNs framework provides a spectrum usage prototype for 5G wireless communication networks. [ABSTRACT FROM AUTHOR]

This paper proposes a novel semi-blind uplink interference suppression scheme for multicell multiuser massive multiple-input multiple-output (MIMO) systems. The inter-cell interference (ICI) becomes intenser when a number of users are spatially multiplexed via massive MIMO. Here arises a pilot contamination problem due to the limitation of orthogonal sequence set and thus inter-user interference (IUI) also remains unsuppressed. Our proposal employs a constant modulus algorithm (CMA) known as a blind interference suppression scheme and exploits channel state information (CSI)-aided minimum mean square error (MMSE) postcoding weight as an initial weight of CMA. Although MMSE weight cannot suppress ICI and IUI due to the pilot contamination, it can help subsequent CMA to capture the desired signals which is required for CMA to effectively work. Since CMA can fully exploit degree of freedom of massive arrays by using uncorrelated data signal part, derived weight successfully suppresses ICI/IUI while resolving the pilot contamination problem. A decision feedback channel estimation (DFCE) is then introduced to further improve CSI estimation accuracy and subsequent interference suppression performance. A series of signal processing, MMSE–CMA–DFCE, can be iteratively performed. The computer simulation reveals that our proposal can improve outage probability and it satisfies below the fifth percentile of cumulative distribution with saved symbol amount. [ABSTRACT FROM AUTHOR]

Prior works in a designing caching policy do not distinguish content popularity with user preference. In this paper, we illustrate the caching gain by exploiting individual user behavior in sending requests. After showing the connection between the two concepts, we provide a model for synthesizing user preference from content popularity. We then optimize the caching policy with the knowledge of user preference and activity level to maximize the offloading probability for cache-enabled device-to-device communications, and develop a low-complexity algorithm to find the solution. In order to learn user preference, we model the user request behavior resorting to probabilistic latent semantic analysis, and learn the model parameters by the expectation maximization algorithm. By analyzing a Movielens data set, we find that the user preferences are less similar, and the activity level and topic preference of each user change slowly over time. Based on this observation, we introduce a prior knowledge-based learning algorithm for user preference, which can shorten the learning time. Simulation results show a remarkable performance gain of the caching policy with user preference over existing policy with content popularity, both with realistic data set and synthetic data validated by the real data set. [ABSTRACT FROM AUTHOR]

It is challenging to derive closed-form performance expressions for composite channels considering both the large-scale lognormal fading and small-scale fading, thus most existing analyses on the composite channels are based on numerical approaches such as the Gauss–Hermite quadrature. In this paper, we develop a simple framework to achieve closed-form asymptotic expressions for the outage probabilities and the error rates of the composite lognormal-X fading channels, where the “X” can be Rayleigh, Rician, Nakagami- $m$ or any other fading channels that have finite diversity orders. It is proved that the lognormal fading contributes an exponential factor to the asymptotic expressions, and the exponential factor is related to the diversity order of the X channel and the lognormal parameters. The new analytical tool is shown to be versatile in evaluating the performance of radio-frequency communications suffering both the large-scale and small-scale fading, including diversity reception systems, relaying systems, and distributed antenna systems. It is also shown to be useful in evaluating free-space optical communication systems with pointing error, and in deriving asymptotic signal-to-noise ratio gaps between different modulation formats over lognormal fading channels. The elegant asymptotic expressions reveal insights into the composite fading channels and can be a criterion for various system designs. [ABSTRACT FROM AUTHOR]

This paper focuses on distributed linear precoding when users transmit correlated information over a fading multiple-input and multiple-output multiple access channel. The precoders are optimized in order to minimize the sum-mean square error (MSE) between the source and the estimated symbols. When sources are correlated, minimizing the sum-MSE results in a non-convex optimization problem. The precoders for an arbitrary number of users and transmit and receive antennas are thus obtained via a projected steepest-descent algorithm and a low-complexity heuristic approach. For the more restrictive case of two single-antenna users, a closed-form expression for the minimum sum-MSE precoders is derived. Moreover, for the scenario with a single receive antenna and any number of users, a solution is obtained by means of a semi-definite relaxation. Finally, we also consider precoding schemes where the precoders are decomposed into complex scalars and unit norm vectors. Simulation results show a significant improvement when source correlation is exploited at precoding, especially for low signal-to-noise ratios and when the number of receive antennas is lower than the number of transmitting nodes. [ABSTRACT FROM AUTHOR]

Personal area networks (PANs) and body-to-body (B2B) networks are of increasing importance for applications ranging from medical monitoring to entertainment. The performance of such networks is largely determined by the propagation channels in which they operate, and which in turn are strongly impacted by the human body/bodies in these channels. It is thus essential to quantify the impact of different body types/sizes on the channel characteristics for PAN and B2B channels. In this paper, we present an extensive propagation channel measurement campaign in the 2–10 GHz frequency band for SIMO (single-input-multiple-output) PAN and MIMO (multiple-input-multiple-output) B2B channels. The measurements were done using 60 (for PAN) and 9 (B2B) human subjects, which had widely varying body mass index (BMI) values grouped into three categories. For each BMI category, parameters such as the average path gain, shadowing gain, root-mean-squared delay spread, channel spatial correlation coefficients, amplitude fading statistics, and channel capacity values were extracted for both PAN and B2B channels. Our analysis reveals considerable differences between these parameters for different BMI categories. [ABSTRACT FROM AUTHOR]

Recent physical-layer designs capable of decoding multi-packet collisions demonstrate great potential for improving the network performance. Current network protocols, however, tailor the traditional physical layer to avoid collisions and thus cannot fully exploit the benefits of concurrent transmission techniques. In this paper, we propose an innovative generic concurrent transmission aware routing design called mShare. The mShare design exploits the benefits of these techniques by scheduling concurrent senders to utilize co-owned receiver(s) in parallel. This design significantly increases the available number of routing choices and thus improves the network performance. To illustrate the versatility of our design, we test mShare in three settings: unicast, opportunistic routing, and data collection (convergecast). The performance of mShare is evaluated with physical testbed experiments running on USRP and simulations. The experimental results show that compared to conventional designs, mShare: 1) improves 277% of the throughput in unicast; 2) saves 78% of transmissions in opportunistic routing; and 3) reduces 70% of the delivery delay in data collection. [ABSTRACT FROM AUTHOR]

Millimeter-wave (mmWave) communication and network densification hold great promise for achieving high-rate communication in next-generation wireless networks. Cloud radio access network (CRAN), in which low-complexity remote radio heads (RRHs) coordinated by a central unit (CU) are deployed to serve users in a distributed manner, is a cost-effective solution to achieve network densification. However, when operating over a large bandwidth in the mmWave frequencies, the digital fronthaul links in a CRAN would be easily saturated by the large amount of sampled and quantized signals to be transferred between the RRHs and the CU. To tackle this challenge, we propose in this paper a new architecture for the mmWave-based CRAN with advanced lens antenna arrays at the RRHs. Due to the energy focusing property, the lens antenna arrays are effective in exploiting the angular sparsity of mmWave channels, and thus help in substantially reducing the fronthaul rate and simplifying the signal processing at the multi-antenna RRHs and the CU, even when the channels are frequency-selective. We consider the uplink transmission in a mmWave CRAN with lens antenna arrays and propose a low-complexity quantization bit allocation scheme for multiple antennas at each RRH to meet the given fronthaul rate constraint. Furthermore, we propose a channel estimation technique that exploits the energy focusing property of the lens array and can be implemented at the CU with low complexity. Finally, we compare the proposed mmWave CRAN using lens antenna arrays with a conventional CRAN using uniform planar arrays at the RRHs, and show that the proposed design achieves significant throughput gains, yet with much lower complexity. [ABSTRACT FROM AUTHOR]

A base-station (BS) equipped with multiple antennas can use its spatial dimensions in three different ways: 1) to serve multiple users, thereby achieving a multiplexing gain; 2) to provide spatial diversity in order to improve user rates; and 3) to null interference in neighboring cells. This paper answers the following question: What is the optimal balance between these three competing benefits? We answer this question in the context of the downlink of a cellular network, where multi-antenna BSs serve multiple single-antenna users using zero-forcing beamforming with equal power assignment, while nulling interference at a subset of out-of-cell users. Any remaining spatial dimensions provide transmit diversity for the scheduled users. Utilizing tools from stochastic geometry, we show that, surprisingly, to maximize the per-BS ergodic sum rate, with an optimal allocation of spatial resources, interference nulling does not provide a tangible benefit. The strategy of avoiding inter-cell interference nulling, reserving some fraction of spatial resources for multiplexing, and using the rest to provide diversity, is already close-to-optimal in terms of the sum-rate. However, interference nulling does bring significant benefit to cell-edge users, particularly when adopting a range-adaptive nulling strategy where the size of the cooperating BS cluster is increased for cell-edge users. [ABSTRACT FROM AUTHOR]

In this paper, we investigate physical layer security in a two-tier heterogeneous network with sub-6 GHz massive multi-input multi-output (MIMO) macro cells and millimeter wave (mmWave) small cells. By considering pilot attacks from the eavesdroppers, we analyze the coverage and secrecy performance using stochastic geometry. For the sub-6 GHz tier, we show that increasing the number of BS antennas is more effective than increasing BS density in improving the coverage performance, whereas densifying BS is more effective for security enhancement. For the mmWave tier, we first derive the success probability of beam alignment based on a beam sweeping-based channel training model. It is shown that the mmWave tier may outperform the sub-6 GHz counterpart in terms of both coverage and secrecy through densifying the base stations. Our results also reveal that the mmWave small cell can provide better coverage performance in the high transmission rate region, and can achieve higher security in the low redundant rate region, which reveals the advantage of using mmWave for secure communication. Numerical results verify the analysis. [ABSTRACT FROM AUTHOR]

In this paper, we consider a non-orthogonal multiple access cognitive radio network, where a full-duplex (FD) multi-antenna relay assists transmission from an access point (AP) to a cognitive far user, while at the same time, the AP transmits to a cognitive near user. Our objective is to maximize the rate of the near user under a constraint that the rate of the far user is above a certain threshold. To this end, a non-convex joint optimization problem of relay beamforming and the transmit powers at the AP and FD relay is solved as a semi-definite relaxation problem, in conjunction with an efficiently solvable line-search approach. We also consider a low complexity fixed beamformer design, where the optimum power allocation between the AP and FD relay is solved. Several fixed beamforming designs based on the zero-forcing criterion are proposed for which exact and asymptotic outage probability expressions corresponding to the near and far users are derived. Our results demonstrate that the proposed joint optimization can significantly reduce the self-interference impact at the FD relay and inter-user interference in the near user case. [ABSTRACT FROM AUTHOR]

Massive multiple-input multiple-output (MIMO) systems, where base stations (BSs) are equipped with hundreds of antennas, are an attractive way to handle the rapid growth of data traffic. As the number of user equipments (UEs) increases, the initial access and handover in contemporary networks will be flooded by user collisions. In this paper, a random access protocol is proposed that resolves collisions and performs timing estimation by simply utilizing the large number of antennas envisioned in massive MIMO networks. UEs entering the network perform spreading in both time and frequency domains, and their timing offsets are estimated at the BS in closed form using a subspace decomposition approach. This information is used to compute channel estimates that are subsequently employed by the BS to communicate with the detected UEs. The favorable propagation conditions of massive MIMO suppress interference among UEs, whereas the inherent timing misalignments improve the detection capabilities of the protocol. Numerical results are used to validate the performance of the proposed procedure in massive MIMO networks, under uncorrelated and correlated fading channels. With $2.5 \times 10^{3}$ UEs that may simultaneously become active with probability 1%, a total of 16 frequency–time codes, and 100 antennas, a given UE is detected with probability 75%, and the accuracy of its timing estimate is on the order of few samples. [ABSTRACT FROM AUTHOR]

In random access for machine-type communications, it is required not only to detect active devices, but also to estimate their channel state information when they transmit preambles. In this paper, we consider an approach for simultaneous multipacket channel estimation and reception (SMuCER) with a multicarrier system under frequency-selective fading, where the channel estimation becomes challenging due to frequency-selective fading and different round-trip delay between the devices. In the proposed approach, circular-shifted preambles are used to effectively increase the number of preambles (that can lower the probability of preamble collision), and compressive sensing (CS)-based multiuser detection (MUD) is employed. In order to have a good performance of CS-based MUD for SMuCER, we consider Alltop sequences. Furthermore, we formulate an optimization problem to maximize the number of successfully recovered active devices, where a large single system is to be divided into multiple subsystems. It is shown that multiple subsystems have not only a higher throughput, but also a lower computational complexity than a large single system. [ABSTRACT FROM AUTHOR]

This paper studies physical-layer security for a cache-enabled heterogeneous cellular network comprised of a macro base station and multiple small base stations (SBSs). We investigate a joint design on caching placement and file delivery for realizing secure and energy-efficient transmissions against randomly distributed eavesdroppers. We propose a novel hybrid “most popular content” and “largest content diversity” caching placement policy to distribute the files of different popularities. Depending on the availability and placement of the requested file, we employ three cooperative transmission schemes, namely, distributed beamforming, frequency-domain orthogonal transmission, and best SBS relaying. We derive analytical expressions for the connection outage probability and secrecy outage probability for each transmission scheme. Afterward, we design the optimal transmission rates and caching allocation successively to achieve a maximal overall secrecy throughput and secrecy energy efficiency, respectively. Numerical results verify the theoretical analyses and demonstrate the superiority of the proposed hybrid caching policy. [ABSTRACT FROM AUTHOR]

In this paper, we strive to improve the throughput of heterogeneous cellular networks by exploiting the pre-cached files at user end to manage interference. We consider a transmission scheme, where network-coded multicast is employed to help cancel multi-user interference, and reconstructed interference cancelation (RIC) is used to help eliminate inter-cell interference. Because RIC is opportunistic, base station (BS) muting is used to coordinate the residual strong interference. Since user association affects residual interference and is coupled with BS muting while both are operated in a very different timescale from content caching, we jointly optimize user association and BS muting for a given caching policy to maximize the number of users simultaneously served by the transmission scheme. By transforming the formulated problem into a maximal independent set problem with constructed conflict graph, the global optimal solution is found with graph theory methods. By exploiting the topology feature of heterogeneous networks, we proceed to propose two low-complexity algorithms, respectively, implemented in a centralized and distributed manner, which are viable for large-scale networks. Simulation results show that the optimized transmission scheme achieves a remarkable performance gain over the existing schemes. [ABSTRACT FROM AUTHOR]

Communication at millimeter wave frequencies will be one of the essential new technologies in 5G. Acquiring an accurate channel estimate is the key to facilitate advanced millimeter wave hybrid multiple-input multiple-output (MIMO) precoding techniques. Millimeter wave MIMO channel estimation, however, suffers from a considerably increased channel use overhead. This happens due to the limited number of radio frequency (RF) chains that prevent the digital baseband from directly accessing the signal at each antenna. To address this issue, recent research has focused on adaptive closed-loop and two-way channel estimation techniques. In this paper, unlike the prior approaches, we study a non-adaptive, hence rather simple, open-loop millimeter wave MIMO channel estimation technique. We present a random phase rotation design of channel subspace sampling signals and show that they obey the restricted isometry property (RIP) with high probability. We then formulate the channel estimation as a low-rank subspace decomposition problem and, based on the RIP, show that the proposed framework reveals resilience to a low signal-to-noise ratio. It is revealed that the required number of channel uses ensuring a bounded estimation error is linearly proportional to the degrees of freedom of the channel, whereas it converges to a constant value if the number of RF chains can grow proportionally to the channel dimension while keeping the channel rank fixed. In particular, we show that the tighter the RIP characterization the lower the channel estimation error is. We also devise an iterative technique that effectively finds a suboptimal, but stationary, solution to the formulated problem. The proposed technique is shown to have improved channel estimation accuracy with a substantially low channel use overhead as compared to that of previous closed-loop and two-way adaptation techniques. [ABSTRACT FROM AUTHOR]

Energy harvesting is a key technology for futureenergy neutralubiquitous wireless communication systems. Among the many available sources of energy, RF harvesting is a natural choice for wireless communications since the devices can be efficiently designed for RF harvesting operations. To achieve energy autonomy a rechargeable energy storage is needed. However, the bursty nature of energy arrival associated with wireless power transfer and the energy usage pattern induced by devices’ activity may cause considerable stress to the battery and reduce its life span. In fact, deep charging and discharging cycles degrade the battery state of health, that is, the maximum amount of energy that can be stored. In this paper, a framework for the optimization of wireless nodes’ transmission and charging strategy is presented, where the battery aging rate is made explicit as a performance metric. The proposed framework is based on MDP theory, where the embedded stochastic model captures the energy arrival and data generation processes, and the control variable takes the form of a transmission power selection and energy acceptance/rejection. The tradeoff between the achievable throughput and the aging rate is explored for different parameters setting. [ABSTRACT FROM AUTHOR]

Social groups open up the opportunity for a new form of caching. This paper investigates how a social group of users can jointly optimize bandwidth usage, by each caching network-coded parts of the data demand, and then opportunistically share these parts among themselves upon meeting. First, the problem is formulated as a linear program (LP) with exponential complexity in the number of users. Then, a heuristic algorithm is proposed, which is inspired by the bipartite set-cover problem and operates in polynomial time. For some scenarios, a worst-case performance guarantee of the heuristic with respect to the optimal LP solution is proved. Finally, the performance of the algorithm is assessed using real-world mobility traces synthesized using the SWIM model and from the MIT Reality Mining project data set. The proposed heuristic offers bandwidth savings up to 65% for a waiting time of 30 minutes and up to 28% performance gains with respect to the alternative solutions. These benefits make the algorithm a feasible candidate solution for bandwidth savings. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA)-based cognitive wireless networks can improve the spectral efficiency to utilize the vacant spectrum resource and exploit the power domain diversity. In this paper, we formulate a max-min resource allocation problem for video traffic in NOMA-based cognitive wireless networks as a mixed integer non-linear programming (MINLP) problem. The max-min video transmission problem is subject to the constraints of maximum accessed user number at each subchannel, total available energy of each secondary user, video encoding characteristics, and interference power threshold. To solve the formulated MINLP problem, we divide it into two subproblems, i.e., a power allocation and secondary user scheduling subproblem, and a video packet scheduling subproblem. First, we apply a successive convex approximation to transform the joint power allocation and secondary user scheduling subproblem into a bi-convex programming problem. Second, the binary search and dual decomposition methods are combined to obtain the approximated optimal power allocation and secondary user scheduling solutions. Finally, we propose a heuristic packet scheduling algorithm. Simulation numerical results show that the proposed algorithm improves the video quality and guarantees the fairness among different secondary users. [ABSTRACT FROM AUTHOR]

This paper considers the application of relay to enhance the performance of massive non-orthogonal multiple access (NOMA) systems and solve the challenge of channel state information acquisition in the case of a massive number of users. First, we design a general framework for a multiple-relay-aided massive NOMA system. Then, we analyze the performance of the multiple-relay-aided massive NOMA system, and derive a closed-form expression for a lower bound on the spectral efficiency. In particular, we reveal the impact of system parameters on the spectral efficiency via asymptotic analysis in three important scenarios, e.g., a large number of antennas at the base station (BS), a high transmit power at the BS or the relays, and a large number of relays. To further improve the spectral efficiency in the context of massive access, we propose two effective schemes to optimize the transmit power at the BS and relays, respectively. Finally, extensive simulation results validate the effectiveness of the proposed multiple-relay-aided massive NOMA scheme. [ABSTRACT FROM AUTHOR]

This paper considers the uplink of multiuser multiple-input multiple-output systems, where several mobile stations (MSs) cooperatively transmit hybrid messages, including common messages and private messages, to a single base station (BS). We aim to jointly design transmit precoding at the MSs’ side and antenna selection at the BS side to maximize the achievable system throughput while reducing implementation complexity. The problem at hand is nonconvex and difficult to solve due to the antenna selection constraint. By exploiting the problem structure and linear relaxation, we propose using the Frank–Wolfe method and the well-known weighted mean-square error minimization approach to tackle the problem, leading to an efficient iterative algorithm. Moreover, due to the large number of antennas, the sparsity of antenna selection is also taken into account by introducing an $l_{0}$ -norm penalty function into the objective function. To tackle this nonconvex and discontinuous problem, we resort to quadratic approximation with smooth optimization and extend our proposed algorithm to the sparse optimization problem. The convergence of the proposed algorithms is analyzed and its effectiveness is verified by numerical examples in terms of the achieved system throughput. [ABSTRACT FROM AUTHOR]

This paper proposes an opportunistic spatial modulation (OSM) scheme where the transmit antennas are divided into $K\geq 1 $ equal groups, and the best antenna from each group is selected to form a $K$ transmit antenna subset for implementing spatial modulation (SM). Thus, the activation of one antenna from the subset to transmit one of the $M$ -ary modulation symbols achieves a data rate of $\log _{2} (K) +\log _{2} (M)$ bits per channel use. Notably, special cases of OSM include conventional SM and pure single transmit antenna selection. To characterize and comparatively evaluate OSM, we first consider phase-shift keying modulation and derive a closed-form, improved union-bound of symbol error probability (SEP) with a single-antenna receiver. Explicit expressions for the SEP in the high signal-to-noise ratio regime are also presented. Extensions to quadrature amplitude modulation analysis and simulations of multiple-antenna reception case are also provided. Simulation results corroborate the analytical results and reveal the interesting interplay between the signal and spatial constellation diagrams. For a given number of transmit antennas and targeted data rate, asymptotically, the SEP can be minimized by using only one antenna group and the largest size of signal constellation, as this configuration achieves the full-diversity order. [ABSTRACT FROM AUTHOR]

Extensive deployment of heterogeneous small cells in cellular networks results in ultra-dense small-cell networks (USNs). The USNs have been established as one of the vital networking architectures in the 5G to expand system capacity and augment network coverage. However, intensive deployment of cells results in a complex interference problem. In this paper, we propose a distributed multi-domain interference management scheme among cooperative small cells. The proposed scheme mitigates the interference while optimizing the overall network utility. In addition, we jointly investigate OFDMA scheduling, TDMA scheduling, interference alignment (IA), and power control. We model small cells’ coordination behavior as an overlapping coalition formation game. In this game, each base station can make an autonomous decision and participate in more than one coalition to perform IA and suppress intra-coalition interference. To achieve this goal, we propose a distributed joint interference management (JIM) algorithm. The proposed algorithm allows each small-cell base station to self-organize and interact into a stable overlapping coalition structure and reduce interference gradually from multi-domain, thus achieving an optimal tradeoff between costs and benefits. Compared with existing approaches, the proposed JIM algorithm provides appreciable performance improvement in terms of total throughput, which is demonstrated by simulation results. [ABSTRACT FROM AUTHOR]

Ultra-reliable and low-latency communications (URLLC) have stringent requirements on quality-of-service and network availability. Due to path loss and shadowing, it is very challenging to guarantee the stringent requirements of URLLC with satisfactory communication range. In this paper, we first provide a quantitative definition of network availability in the short blocklength regime: the probability that the reliability and latency requirements can be satisfied when the blocklength of channel codes is short. Then, we establish a framework to maximize the available range, defined as the maximal communication distance subject to the network availability requirement, by exploiting multi-connectivity. The basic idea is using both device-to-device (D2D) and cellular links to transmit each packet. The practical setup with correlated shadowing between D2D and cellular links is considered. Besides, since processing delay for decoding packets cannot be ignored in URLLC, its impacts on the available range are studied. By comparing the available ranges of different transmission modes, we obtained some useful insights on how to choose transmission modes. Simulation and numerical results validate our analysis and show that multi-connectivity can improve the available ranges of D2D and cellular links remarkably. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel modulation technique for dual-polarization communication systems, which reduces the error rate compared with the existent schemes. This modulation places the symbols in a 3-D constellation, rather than the classic approach of 2-D. Adjusting the phase of these symbols depending on the information bits, we are able to increase the bit rate. Hence, the proposed scheme conveys information by selecting both polarization state and the phase of radiated electromagnetic wave. We also analyses the performance of the 3-D polarized modulation (PMod) for different constellation sizes and we obtain a curve of rate adaptation. Finally, we compare the proposed 3-D PMod with the other existing schemes, such as single polarization phase shift keying and double polarization vertical Bell Laboratories layer space–time, both carrying the same number of information bits. The results show that the 3-D PMod always outperforms all other schemes, except for low-order modulation. Therefore, we can conclude that the 3-D PMod is an excellent candidate for medium- and high-modulation-order transmissions. [ABSTRACT FROM AUTHOR]