<![CDATA[ IEEE Transactions on Wireless Communications - new TOC ]]>
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TOC Alert for Publication# 7693 2018February 15<![CDATA[Table of contents]]>172C1710241<![CDATA[IEEE Transactions on Wireless Communications]]>172C2C282<![CDATA[Distributed Resource Allocation in SDCN-Based Heterogeneous Networks Utilizing Licensed and Unlicensed Bands]]>1727117212057<![CDATA[Downlink Resource Allocation Under Time-Varying Interference: Fairness and Throughput Optimality]]>$alpha $ –fair scheduling, and propose a policy that ensures asymptotic convergence to the optimal $alpha $ –fair throughput. Second, we propose a throughput optimal resource allocation policy, i.e., a policy that can stably support the largest possible set of traffic rates under the interference scenario considered. Estimating the outage probability from the outdated SINR values plays an important role in both scheduling paradigms, and we accomplish this using tool from renewal theory.]]>1727227351838<![CDATA[Cache-Enabled Physical Layer Security for Video Streaming in Backhaul-Limited Cellular Networks]]>1727367511416<![CDATA[Hybrid LISA Precoding for Multiuser Millimeter-Wave Communications]]>linear successive allocation method developed for the traditional fully digital version. It successively allocates data streams to users and suppresses the respective interstream interference in two stages, which perfectly matches the hybrid architecture. Furthermore, a low-complexity version is developed by exploiting the typical structure of mm-wave channels. The good performance of the proposed method and its low-complexity version is demonstrated by simulation results.]]>172752765918<![CDATA[Optimizing Cluster Size Through Handoff Analysis in User-Centric Cooperative Wireless Networks]]>$K$ closest BSs, while in the DBC mode, it is served by all BSs within a given distance. However, due to the randomness of network topology, it is a challenging task to track handoffs and to characterize data rates. To address this issue, we propose a stochastic geometric analysis framework on user mobility, to derive a theoretical expression for the handoff rate experienced by an active user with arbitrary movement trajectory. Then, we characterize the average downlink user data rate under a common non-coherent joint-transmission scheme, which is used to illustrate the tradeoff between handoff rate and data rate in optimizing the cooperative cluster size. We conclude that in the NBC (resp. DBC) mode, the optimal cluster size is asymptotically inversely (resp. inversely) proportional to the square of the user speed and asymptotically inversely (resp. inversely) proportional to the BS intensity. Finally, computer simulation is conducted to validate the correctness and usefulness of our analysis.]]>1727667782012<![CDATA[Caching Meets Millimeter Wave Communications for Enhanced Mobility Management in 5G Networks]]>$mu text{W}$ ) frequencies. In this paper, a novel approach to analyzing and managing mobility in joint mmwave–$mu text{W}$ networks is proposed. The proposed approach leverages device-level caching along with the capabilities of dual-mode SBSs to minimize handover failures and reduce inter-frequency measurement energy consumption. First, fundamental results on the caching capabilities are derived for the proposed dual-mode network scenario. Second, the impact of caching on the number of handovers (HOs), energy consumption, and the average handover failure (HOF) is analyzed. Then, the proposed cache-enabled mobility management problem is formulated as a dynamic matching game between mobile user equipments (MUEs) and SBSs. The goal of this game is to find a distributed HO mechanism that, under network constraints on HOFs and limited cache sizes, allows each MUE to choose between: 1) executing an HO to a target SBS; 2) being connected to the macrocell base station; or 3) perform a transparent HO by using the cached content. To solve this dynamic matching problem, a novel algorithm is proposed and its convergence to a two-sided dynamically stable HO policy for MUEs and target SBSs is proved. Numerical results corroborate the analytical derivations and show that the proposed solution will significantly reduce both the HOF and energy consumption of MUEs, resulting in an enhanced mobility management for heterogeneous wireless networks with mm-wave capabilities.]]>1727797931826<![CDATA[Compressed-Sensing Assisted Spatial Multiplexing Aided Spatial Modulation]]>1727948072175<![CDATA[On Protocol and Physical Interference Models in Poisson Wireless Networks]]>1728088211363<![CDATA[Secure Transmission in Linear Multihop Relaying Networks]]>1728228341356<![CDATA[Complementary Coded Scrambling Multiple Access and Its Performance in Downlink MIMO Channels]]>1728358471753<![CDATA[A General Approach Toward Green Resource Allocation in Relay-Assisted Multiuser Communication Networks]]>subcarrier time sharing, and by applying a successive convex approximation approach. Based on the dual decomposition method, we derive an optimal solution to the joint optimization problem. The impact of different network parameters, namely number of subcarriers and number of users, on the attainable EE and spectral efficiency (SE) performance of the proposed design framework is also investigated. The numerical results are provided to validate the theoretical findings and to demonstrate the effectiveness of the proposed algorithm for achieving higher EE and SE than the existing schemes.]]>1728488621516<![CDATA[Performance Analysis of Near-Optimal Energy Buffer Aided Wireless Powered Communication]]>continuous-state Markov chains to analyze the limiting distribution of the stored energy for finite- and infinite-size energy buffers. We provide this limiting distribution in closed form for a Nakagami-$m$ fading DL channel and analyze the outage probability for a Nakagami-$m$ fading UL channel. All derived analytical results are not limited to EH via RF WPT but are applicable for any independent and identically distributed EH process from e.g. solar and wind energy. Our results reveal that, for low-to-medium outage probabilities, the best-effort policy is superior to the on-off policy and the optimal UL transmit power of the EH node that minimizes the outage probability is always less than the average harvested power. The opposite behaviour is observed for high outage probabilities. Furthermore, we show that the minimum outage probability of the two proposed policies is near-optimal.]]>1728638812761<![CDATA[Dynamic Spectrum Reservation for CR Networks in the Presence of Channel Failures: Channel Allocation and Reliability Analysis]]>1728828983572<![CDATA[An Information-Theoretic Analysis of the Gaussian Multicast Channel With Interactive User Cooperation]]>1728999131756<![CDATA[Ergodic Rate of Millimeter Wave Ad Hoc Networks]]>1729149261140<![CDATA[Power Control for Multi-Cell Networks With Non-Orthogonal Multiple Access]]>1729279421581<![CDATA[Blind Channel Estimation and Symbol Detection for Multi-Cell Massive MIMO Systems by Expectation Propagation]]>1729439541407<![CDATA[Energy Efficiency in Cache-Enabled Small Cell Networks With Adaptive User Clustering]]>1729559681361<![CDATA[Gibbsian On-Line Distributed Content Caching Strategy for Cellular Networks]]>finite collection of base stations are scattered on the plane, each covering a cell (possibly overlapping with other cells). Mobile users request downloads from a finite set of contents according to some popularity distribution which may be known or unknown to the base stations. Each base station has a fixed memory space that can store only a strict subset of the contents at a time; hence, if a user requests content that is not stored at any of its serving base stations, the content has to be downloaded from the backhaul. Hence, we consider the problem of optimal content placement which minimizes the rate of download from the backhaul, or equivalently maximize the cache hit rate. It is known that, when multiple cells can overlap with one another (e.g., under dense deployment of base stations in small cell networks), it is not optimal to place the most popular contents in each base station. However, the optimal content placement problem is NP-complete. Using the ideas of Gibbs sampling, we propose simple sequential content update rules that decide whether to store content at a base station (if required from the base station) and which content has to be removed from the corresponding cache, based on the knowledge of contents stored in its neighboring base stations. The update rule is shown to be asymptotically converging to the optimal content placement for all nodes under the knowledge of content popularity. Next, we extend the algorithm to address the situation where content popularities and cell topology are initially unknown, but are estimated as new requests arrive to the base stations; we show that our algorithm working with the running estimates of content popularities and cell topology also converges asymptotically to the optimal content placement. Finally, we-
demonstrate the improvement in cache hit rate compared with the most popular content placement and independent content placement strategies via numerical exploration.]]>172969981791<![CDATA[Degrees of Freedom of Full-Duplex Multiantenna Cellular Networks]]>completely characterize the sum DoFs for both FD cellular networks. The key idea of the proposed scheme is to carefully allocate UL and DL streams using interference alignment and beam forming techniques. By comparing the DoFs of the FD systems with those of the conventional HD systems, we show that the DoF can approach the two-fold gain over the HD systems, when the number of users becomes large enough compared with the number of antennas at the BS.]]>1729829951944<![CDATA[Macrodiversity in Cellular Networks With Random Blockages]]>$n$ th order LOS probability and show that macrodiversity gains are higher when the blocking objects are small. We also show that the BS density must scale as the square of the blockage density to maintain a given level of LOS probability.]]>17299610102665<![CDATA[Multi-Channel Resource Allocation Toward Ergodic Rate Maximization for Underlay Device-to-Device Communications]]>172101110251531<![CDATA[Message-Passing Strategy for Joint User Association and Resource Blanking in HetNets]]>172102610371360<![CDATA[Millimeter Wave Beam-Selection Using Out-of-Band Spatial Information]]>weighted sparse signal recovery problem, and obtain the weighting information from sub-6 GHz channels. In addition, we outline a structured precoder/combiner design to tailor the training to out-of-band information. We also extend the proposed out-of-band aided compressed beam-selection approach to leverage information from all active subcarriers at mmWave. To simulate multi-band frequency dependent channels, we review the prior work on frequency dependent channel behavior and outline a multi-frequency channel model. The simulation results for achievable rate show that out-of-band aided beam-selection can considerably reduce the training overhead of in-band only beam-selection.]]>172103810522491<![CDATA[Rate Adaptation, Scheduling, and Mode Selection in D2D Systems With Partial Channel Knowledge]]>172105310651339<![CDATA[Full-Duplex Cognitive Radio With Asynchronous Energy-Efficient Sensing]]>172106610802167<![CDATA[Half-Duplex or Full-Duplex Communications: Degrees of Freedom Analysis Under Self-Interference]]>172108110931306<![CDATA[Performance Analysis of FDD Massive MIMO Systems Under Channel Aging]]>172109411081339<![CDATA[A New Link Adaptation Method to Mitigate SINR Mismatch in Ultra-Dense Small Cell LTE Networks]]>172110911222903<![CDATA[Millimeter Wave Channel Estimation via Exploiting Joint Sparse and Low-Rank Structures]]>172112311331406<![CDATA[Arena Function: A Framework for Computing Capacity Bounds in Wireless Networks]]>transmission arenas, which indicates the presence of active transmissions near any given location in the network. This novel space-based approach is well-suited to untangle the interactions of simultaneous transmissions. Avoiding a graph-based model of the network, it opens new avenues of studying capacities. For homogeneous networks, we recover classical bounds. However, our methodology applies to arbitrary networks and can, thus, inform placing and activating of nodes also in the presence of clustering. Our method works with all classical channel models and dimensions. It provides bounds on the transport capacity which involve only high-level knowledge of node locations, such as the length of Euclidean minimum spanning tree. As an additional novelty, we establish bounds on wireless unicast and multicast capacities.]]>17211341146965<![CDATA[SINR and Throughput of Dense Cellular Networks With Stretched Exponential Path Loss]]>$r$ as $e^{-alpha r^{beta }}$ , where $alpha$ and $beta$ are tunable parameters. Using experimental propagation measurements, we show that the proposed model is accurate for short to moderate distances in the range $r in ~(5,300)$ meters and so is a suitable model for dense and ultradense networks. We integrate this path loss model into a downlink cellular network with base stations modeled by a Poisson point process, and derive expressions for the coverage probability, potential throughput, and area spectral efficiency. Although the most general result for coverage probability has a double integral, several special cases are given, where the coverage probability has a compact or even closed form. We then show that the potential throughput is maximized for a particular BS density and then collapses to zero for high densities, assuming a fixed signal-to-interference-plus-noise ratio (SINR) threshold. We next prove that the area spectral efficiency, which assumes an adaptive SINR threshold, is nondecreasing with the BS density and converges to a constant for high densities.]]>172114711601811<![CDATA[LTE Multimedia Broadcast Multicast Service Provisioning Based on Robust Header Compression]]>172116111721561<![CDATA[Traffic-Aware Energy-Saving Base Station Sleeping and Clustering in Cooperative Networks]]>172117311861443<![CDATA[Spatial Reuse for Coexisting LTE and Wi-Fi Systems in Unlicensed Spectrum]]>small cell base stations equipped with multiple transmit antennas and operating in the unlicensed spectrum, some spatial degrees of freedom (DoF)s are dedicated to serving small cell user terminals (SUEs) and others are employed to mitigate interference to the co-existing co-channel Wi-Fi users by applying a linear multi-user precoding technique, such as zero-forcing transmit beamforming (ZFBF). Through careful allocation of spatial DoFs, enhanced spatial reuse of unlicensed spectrum resources can be achieved, thereby improving spectrum efficiency on unlicensed bands. However, due to inherent channel state information (CSI) estimation and feedback errors, ZFBF cannot completely alleviate detrimental co-channel interference effects. After analysing the so-called intra radio technology (intra-RAT) interference among SUEs, i.e., the residual interference caused by imperfect CSI used in ZFBF, and the inter-RAT interference experienced by the Wi-Fi users, we derive the throughput of the co-existing LTE and Wi-Fi systems, respectively. Based on the derived throughput, spatial DoF and power can be optimally allocated to balance the throughput between the small cell and Wi-Fi systems in different scenarios. Our theoretical analysis and proposed schemes are further confirmed with exhaustive numerical simulation results.]]>172118711982037<![CDATA[Performance Study for SWIPT Cooperative Communication Systems in Shadowed Nakagami Fading Channels]]>$m$ fading channels. Both coherent and non-coherent modulations, namely, binary phase-shift keying (BPSK) and binary differential phase-shift keying (BDPSK) are considered. We propose closed-form expressions of the moment generating function and the probability density function for the received signal-to-noise ratio of the cooperative link. Based on this, we further derive the average bit-error-rate and the outage probability expressions for the systems with both BPSK and BDPSK modulations. All of these expressions are given in closed-form except one in single integral that can be easily evaluated using numerical integration methods. Numerical results are used to confirm the validity of the proposed analytical results. It is shown that the performance of the systems is more susceptible to the fading parameter $m$ than to the shadowing level ${sigma _{s}}$ and does not change much with the power splitting ratio.]]>172119912111278<![CDATA[Factor Graph-Based Equalization for Two-Way Relaying With General Multi-Carrier Transmissions]]>172121212252683<![CDATA[A Novel Self-Interference Cancellation Scheme for Channel-Unaware Differential Space-Time Two-Way Relay Networks]]>172122612411444<![CDATA[Unified Near-Field and Far-Field Localization for AOA and Hybrid AOA-TDOA Positionings]]>172124212541318<![CDATA[On the Fast and Precise Evaluation of the Outage Probability of Diversity Receivers Over $alpha -mu $ , $kappa -mu $ , and $eta -mu $ Fading Channels]]>$alpha -mu $ , $kappa -mu $ , and $eta -mu $ random variables in the setting of rare event simulations. To this end, we present a simple and efficient importance sampling approach. The main result of this work is the bounded relative error property of the proposed estimators. Capitalizing on this result, we accurately estimate the outage probability of multibranch maximum ratio combining and equal gain diversity receivers over $alpha -mu $ , $kappa -mu $ , and $eta -mu $ fading channels. Selected numerical simulations are discussed to show the robustness of our estimators compared with naive Monte Carlo estimators.]]>172125512681663<![CDATA[Joint Sensing Duration Adaptation, User Matching, and Power Allocation for Cognitive OFDM-NOMA Systems]]>172126912821405<![CDATA[Optimization and Analysis of Probabilistic Caching in $N$ -Tier Heterogeneous Networks]]>$N$ -tier wireless heterogeneous network (HetNet) using stochastic geometry. A general and tractable expression of the successful delivery probability (SDP) is first derived. We then optimize the caching probabilities for maximizing the SDP in the high signal-to-noise ratio regime. The problem is proved to be convex and solved efficiently. We next establish an interesting connection between $N$ -tier HetNets and single-tier networks. Unlike the single-tier network where the optimal performance only depends on the cache size, the optimal performance of $N$ -tier HetNets depends also on the base station (BS) densities. The performance upper bound is, however, determined by an equivalent single-tier network. We further show that with uniform caching probabilities regardless of content popularities, to achieve a target SDP, the BS density of a tier can be reduced by increasing the cache size of the tier when the cache size is larger than a threshold; otherwise, the BS density and BS cache size can be increased simultaneously. It is also found analytically that the BS density of a tier is inverse to the BS cache size of the same tier and is linear to BS cache sizes of other tiers.]]>172128312972113<![CDATA[Leveraging High Order Cumulants for Spectrum Sensing and Power Recognition in Cognitive Radio Networks]]>172129813101410<![CDATA[Power-Aware Optimized RRH to BBU Allocation in C-RAN]]>172131113223074<![CDATA[Gallager Bound for MIMO Channels: Large- $N$ Asymptotics]]>et al. 2015. We also obtain an expression for the Gallager exponent in the case when the codelength spans several Rayleigh fading blocks, hence taking into account the situation when the channel varies during each transmission.]]>17213231330450<![CDATA[Iterative Demodulation and Decoding Algorithm for 3GPP/LTE-A MIMO-OFDM Using Distribution Approximation]]>$K$ -best algorithms to take advantage of both the types of approximations and the list decoder. Unlike existing algorithms, our proposed $K$ -best algorithms make use of the a priori probabilities to generate the list. Simulations of standard-compliant LTE systems demonstrate that the proposed algorithms outperform the existing ones.]]>172133113421148<![CDATA[Adaptive Coding and Modulation for Large-Scale Antenna Array-Based Aeronautical Communications in the Presence of Co-Channel Interference]]>172134313572049<![CDATA[Max–Min Fair Transmit Precoding for Multi-Group Multicasting in Massive MIMO]]>172135813731579<![CDATA[Robust Long-Term Predictive Adaptive Video Streaming Under Wireless Network Uncertainties]]>predictive-DASH (P-DASH) is of paramount importance to handling the practical uncertainty implied in predicted information. In this paper, we propose a stochastic QoS-aware robust predictive-DASH (RP-DASH) scheme over future wireless networks that takes into account imperfect rate predictions. The objective is to achieve long-term quality fairness among the DASH users while capping the probability of service degradation by an operator predefined level. A deterministic formulation is then obtained using the scenario approximation, which adopts the probability density function (PDF) of predicted rates. A linear conservative approximation is introduced to provide an NP-complete formulation, which can be optimized by commercial solvers. Since exact PDF might not be available, Gaussian approximation is adopted by the introduced scheme to provide a closed form less complexity formulation. To support real-time implementations, a guided heuristic algorithm is devised to obtain near-optimal resource allocations and quality selections, while satisfying the predefined QoS level. Previous non-robust P-DASH schemes are evaluated in this paper, while considering typical error models in predicted rates. Such schemes resulted in increased QoS and the quality of experience degradations with the network load, which was avoided by the introduced RP-DASH. Results further revealed the ability of RP-DASH to reach optimal and fair QoS satisfactions.]]>172137413881734<![CDATA[Joint Interference Mitigation and Data Recovery for Massive Carrier Aggregation via Non-Linear Compressive Sensing]]>172138914042573<![CDATA[IEEE Communications Society]]>172C3C373<![CDATA[[Blank page]]]>172C4C43