<![CDATA[ IEEE Communications Letters - new TOC ]]>
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TOC Alert for Publication# 4234 2017January 19<![CDATA[Table of contents]]>211C12301<![CDATA[IEEE Communications Society]]>211C2C290<![CDATA[Reviewers and Editors Appreciation 2016]]>21133103<![CDATA[Compressive Sensing-Based Pilot Design for Sparse Channel Estimation in OFDM Systems]]>21147736<![CDATA[Probability of Outage Due to Self-Interference in Indoor Wireless Environments]]>211811403<![CDATA[Round-Trip Energy Efficiency of Wireless Energy Powered Massive MIMO System With Latency Constraint]]>2111215245<![CDATA[Innovative Robust Modulation Classification Using Graph-Based Cyclic-Spectrum Analysis]]>2111619638<![CDATA[Novel Robust Band-Limited Signal Detection Approach Using Graphs]]>2112023567<![CDATA[Symbol-Based Belief Propagation Decoder for Multilevel Polar Coded Modulation]]>2112427440<![CDATA[Low-Complexity Belief-Propagation Decoding via Dynamic Silent-Variable-Node-Free Scheduling]]>2112831903<![CDATA[Informed Fixed Scheduling for Faster Convergence of Shuffled Belief-Propagation Decoding]]>informed fixed scheduling (IFS) scheme for shuffled belief-propagation (BP) decoding of binary low-density parity-check (LDPC) code is introduced to improve the BP decoding convergence. The IFS finds an appropriate order of variable nodes in accordance with the number of updated neighbors in the code graph, ensuring that the maximum number of latest message updates is utilized within a single iteration. This allows the utilization of most reliable message updates in a timely manner, leading to faster error-rate convergence. Simulation results show that the proposed IFS scheme improves the convergence speed of BP decoder by up to 20% for regular LDPC codes and 45% for irregular LDPC codes, without affecting the error-rate performance, at medium-to-high signal-to-noise ratio over binary-input additive white Gaussian noise channel.]]>2113235692<![CDATA[Analysis of the Probability of Sync-Words in Reed–Solomon Codes]]> . We give analytical expressions for calculating , which is applicable to RS codes. Knowledge of can be used to calculate the probability of finding a sync-word that is used as a marker in RS encoded data, . The probability is called the false acquisition probability in the synchonization of RS encoded data.]]>2113639390<![CDATA[Analysis of the Spatial Correlation of Indoor MIMO PLC Channels]]> MIMO channels measured in four different countries. The presented statistical analysis of the condition number reveals three important facts. First, the spatial correlation is almost independent of frequency, which has important implications in the development of top-down MIMO PLC channel models. Second, the use of an alternative injection method can notably reduce the spatial correlation and, consequently, increase the system bit-rate. Third, there exist countries whose channels have larger spatial correlation values than others. Since spatial correlation plays a key role in the performance of MIMO PLC systems, a hypothesis relating the type of wiring deployed in the indoor power grid to the spatial correlation is given and supported by simulations.]]>2114043534<![CDATA[Analytical Performance Evaluation of VDSL2]]>2114447809<![CDATA[Mutually Referenced Channel Shortening]]>2114851457<![CDATA[Delay Minimization in Real-Time Communications With Joint Buffering and Coding]]>2115255455<![CDATA[Expanded Constellation Mapping for Enhanced Far-End-Cross-Talk Cancellation in G.fast]]>2115659592<![CDATA[Design of an Adaptive Multiresolution $M$ -Ary DCSK System]]> -ary differential chaos shift keying (MR--DCSK) system enables unequal-priority transmission via exploiting non-uniformly spaced phase constellations. In this letter, an adaptive MR--DCSK system is proposed by using a new constellation parameter design. Aiming at maximizing the spectral efficiency, the constellation parameter is carefully selected based on signal-to-noise ratio, and then is further optimized by a new search algorithm. Both the analytical and simulation results show that the proposed adaptive MR--DCSK system not only can enhance the spectral efficiency as compared with the adaptive -DCSK system, but can satisfy different bit-error-rate requirements for different bits within a symbol as well.]]>2116063738<![CDATA[Modulation Classification via Subspace Detection in MIMO Systems]]>2116467637<![CDATA[FSK-Based Reactive Jammer Piggybacking]]>2116871553<![CDATA[Security of an Ordered-Based Distributive Jamming Scheme]]>2117275229<![CDATA[Simplified High-Order DOA and Range Estimation With Linear Antenna Array]]>2117679482<![CDATA[An Efficient Semidefinite Relaxation Algorithm for Moving Source Localization Using TDOA and FDOA Measurements]]>2118083501<![CDATA[Coordinated Beamforming for Multi-Cell MIMO-NOMA]]>non-orthogonal multiple access combined with multiple-input multiple-output communication in the presence of inter-cell interference. The proposed schemes successfully deal with inter-cell interference, and increase the cell-edge users’ throughput, which in turn improves user fairness. In addition, they increase the number of served users, which makes them suitable for 5G networks where massive connectivity and higher spectral efficiency are required. Numerical results confirm the effectiveness of the proposed algorithms.]]>2118487391<![CDATA[Low Complexity Message Passing-Based Receiver Design for Wiener Phase-Noise Channels]]>2118891415<![CDATA[A Low Complexity Sensing Algorithm for Wideband Sparse Spectra]]>2119295739<![CDATA[DOA Estimation Based on Combined Unitary ESPRIT for Coprime MIMO Radar]]>2119699492<![CDATA[In-Band Wireless Information and Power Transfer With Lens Antenna Array]]>211100103658<![CDATA[How Much Computing Capability Is Enough to Run a Cloud Radio Access Network?]]>211104107699<![CDATA[Area Spectral Efficiency Analysis of Multi-Antenna Two-Tier Cellular Networks]]>211108111554<![CDATA[Pilot Allocation and Power Control in D2D Underlay Massive MIMO Systems]]>211112115401<![CDATA[Performance Comparison of Industrial Wireless Networks for Wireless Avionics Intra-Communications]]>211116119411<![CDATA[Optimizing Cache Placement for Heterogeneous Small Cell Networks]]>211120123547<![CDATA[3-D Position Location in Ad Hoc Networks: A Manhattanized Space]]>211124127948<![CDATA[Energy-Efficient Cooperation in Cognitive Wireless Powered Networks]]>211128131664<![CDATA[Cooperative Sensing With Joint Energy and Correlation Detection in Cognitive Radio Networks]]>211132135393<![CDATA[Cooperative Cross-Layer Resource Allocation for Self-Healing in Interworking of WLAN and Femtocell Systems]]>211136139495<![CDATA[An Optimal Service Strategy for Grouped Machine-Type Communications in Cellular Networks]]>211140143312<![CDATA[Energy-Aware Wireless Relay Selection in Load-Coupled OFDMA Cellular Networks]]> -hardness of the energy-aware wireless relay selection problem. To tackle computational complexity, a partial optimality condition is derived for providing insights in respect of designing an effective and efficient algorithm. Numerical results show the resulting algorithm achieves high energy performance.]]>211144147323<![CDATA[Resource Allocation for Virtualized Wireless Networks with Backhaul Constraints]]>211148151458<![CDATA[Adaptive Beacon Transmission in Cognitive-OFDM-Based Industrial Wireless Networks]]>211152155866<![CDATA[Energy-Aware Gateway Placement in Green Wireless Mesh Networks]]> gateways to be added, what is the optimal gateway placement with the constraint of energy-minimization for green wireless mesh networks. Unlike previous research, which focuses on throughput optimization, we contribute by developing a mixed-integer linear programming (MILP) formulation, which satisfies the given flow demands while minimizing the global energy consumption of the network. The proposed solution is NP-hard; therefore, we also propose a heuristic-based greedy algorithm to efficiently solve large instances of this problem. To capture interference in the mesh network, we use the physical-interference model but employ a greedy algorithm to reduce the computation time for finding maximal independent sets. We implement both the MILP formulation and the greedy solution along with three other contemporary solutions in the area. Numerical results show that the proposed exact scheme provides the optimal result, while the greedy solution provides a solution within 5% of the optimal solution with just 1% computation time for green wireless mesh networks.]]>211156159475<![CDATA[$mathsf{REboost}$ : Improving Throughput in Wireless Networks Using Redundancy Elimination]]>REboost to enable the TCP layer to be aware of the underlying RE system and improve the throughput. Our evaluation with a prototype shows that REboost significantly improves the throughput compared with the previous RE systems.]]>211160163558<![CDATA[Uplink Modeling of $K$ -Tier Heterogeneous Networks: A Queuing Theory Approach]]> -tier HetNet, as an M/G/1 queue with interruption operating at the packet level. By integrating key findings on HetNets (using stochastic geometry) into the queue, a realistic model is obtained. This model enables us to understand what a UE experiences in terms of throughput, an angle that has barely been looked through by others. The modeling framework considers all the essential HetNet parameters, including the transmit power, spatial distribution, service rate, traffic flow intensity, and base station coverage threshold, to obtain the probability generating function and related statistics of the UE queue length.]]>211164167498<![CDATA[High-Rate APSK-Aided Differential Spatial Modulation: Design Method and Performance Analysis]]>211168171793<![CDATA[Error Vector Magnitude Analysis of Uplink Multiuser OFDMA and SC-FDMA Systems in the Presence of Nonlinear Distortion]]>211172175478<![CDATA[An Improved Uplink Sparse Coded Multiple Access]]>211176179604<![CDATA[Distributed Channel Access for Device-to-Device Communications: A Hypergraph-Based Learning Solution]]>211180183414<![CDATA[Definition of QoE Fairness in Shared Systems]]>QoE fairness index , which has desirable key properties as well as the rationale behind it. By using examples and a measurement study involving multiple users downloading web content over a bottleneck link, we differentiate the proposed index from QoS fairness and the widely used Jain’s fairness index. Based on results, we argue that neither QoS fairness nor Jain’s fairness index meet all of the desirable QoE-relevant Properties, which are met by . Consequently, the proposed index may be used to compare QoE fairness across systems and applications, thus serving as a benchmark for QoE management mechanisms and system optimization.]]>211184187488<![CDATA[A Low Complexity Sub-Optimal Approach to Dynamic Spectrum Allocation for White Space Devices With Heterogeneous Bandwidth Requirements]]> as compared with that of the optimal solution .]]>211188191652<![CDATA[Multiple-Access Interference Mitigation for Acquisition of Code-Division Multiple-Access Continuous-Wave Signals]]>211192195473<![CDATA[Construction of a Generalized DFT Codebook Using Channel-Adaptive Parameters]]>211196199567<![CDATA[On the DMT of RF Energy Harvesting-Based Dynamic Decode-and-Forward Relaying]]>211200203539<![CDATA[Space-Time and Space-Frequency Block Coded Vector OFDM Modulation]]>211204207676<![CDATA[Packet Error Rate Analysis of Uncoded Schemes in Block-Fading Channels Using Extreme Value Theory]]> -function bit error rate forms. The EVT approach leads us to a best closed-form approximation, in terms of accuracy and computational efficiency, of the average PER in block-fading channels. The numerical analysis shows that the approximation holds tight for any value of signal-to-noise ratio (SNR) and packet length whereas the earlier studies approximate the average PER only at asymptotic SNRs and packet lengths.]]>211208211577<![CDATA[Analysis of Uplink ICI and IBI in Heterogeneous Cellular Networks With Multiple Macrocells]]>211212215894<![CDATA[Underlay Cognitive Relaying System Over $alpha $ - $mu $ Fading Channels]]>$alpha $ -$mu $ fading channel is studied. The contribution is first described by the exact closed-form expression for the outage probability and later extended to the symbol error rate calculation. Both analytical and simulation results show how the outage saturation paradigm appears when the interference level is constrained. Also, it is shown that the system achieves a better performance when higher interference constraint is employed.]]>211216219481<![CDATA[IEEE Communications Society]]>211C3C3120