<![CDATA[ IEEE Transactions on Wireless Communications - new TOC ]]>
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TOC Alert for Publication# 7693 2019June 13<![CDATA[Table of contents]]>186C1C4232<![CDATA[IEEE Transactions on Wireless Communications]]>186C2C2119<![CDATA[Study of OFDM Precoded Filter-Bank Waveforms]]>186288929023991<![CDATA[Request Delay-Based Pricing for Proactive Caching: A Stackelberg Game Approach]]>186290329181714<![CDATA[Safeguarding UAV Communications Against Full-Duplex Active Eavesdropper]]>186291929311347<![CDATA[Load Balancing User Association in Millimeter Wave MIMO Networks]]>186293229451275<![CDATA[Joint Antenna Array Mode Selection and User Assignment for Full-Duplex MU-MISO Systems]]>186294629631867<![CDATA[Massive MIMO Forward Link Analysis for Cellular Networks]]>186296429762562<![CDATA[Moving Aerial Base Station Networks: A Stochastic Geometry Analysis and Design Perspective]]>186297729881833<![CDATA[Optimal Signaling Schemes and Capacity of Non-Coherent Rician Fading Channels With Low-Resolution Output Quantization]]>$pi /2$ circularly symmetric. A necessary and sufficient condition for an input signal to be optimal, which is referred to as the Kuhn-Tucker condition (KTC), and Lagrangian optimization problem are then established. By exploiting the novel log-quadratic bounds on the Gaussian $Q$ -function, it is then demonstrated that for a given mass point’s amplitude, the corresponding rotated mass points through the phase of LOS component must form a square grid centered at zero. Furthermore, the amplitude of the mass points in the optimal distribution can take on only one value. As a result, the capacity-achieving input with 1-bit ADC is a rotated quadrature phase-shift keying (QPSK) constellation, and the rotation angle depends on the Rician factor. The characterization of the optimal input has also been extended to the case of multi-bit ADCs. Specifically, it is shown that for a $K$ -bit ADC, the optimal input is discrete having atmost $2^{2K}$ mass points. In both the cases of 1-bit and $K$ -bit ADCs, the channel capacities are established in closed-form.]]>186298930044911<![CDATA[Adaptive Transmission in Cellular Networks: Fixed-Rate Codes With Power Control Versus Physical Layer Rateless Codes]]>186300530181069<![CDATA[Joint Interference Cancellation and Resource Allocation for Full-Duplex Cloud Radio Access Networks]]>186301930331434<![CDATA[Dynamic Transmission Policy for Multi-Pair Cooperative Device-to-Device Communication With Block-Diagonalization Precoding]]>data-sharing phase (i.e., phase 1) and a joint transmission phase (i.e., phase 2). Multicast precoders are used in phase 1 and coordinated block-diagonalization precoders are considered in phase 2. The precoders are jointly designed to maximize the long-term utility of the D2D users subject to long-term individual power and rate-gain constraints and an instantaneous interference constraint at the base-station. The long-term objective and constraints allow cooperating users to adapt their resources more flexibly over time, but increase the complexity of the design. By adopting the Lyapunov optimization framework and by constructing virtual queues to record the temporal evolution of the system states, the long-term utility maximization problem can be decoupled into a series of short-term weighted-rate-minus-energy-penalty (WRMEP) optimization problems that can be solved efficiently. A low-complexity algorithm is further proposed for solving the WRMEP problem when multicasting in the data-sharing phase is performed by a spatially white input. Theoretical performance guarantees and a bound on the virtual queue backlogs are also derived.]]>186303430481761<![CDATA[On the Diversity of Uncoded OTFS Modulation in Doubly-Dispersive Channels]]>$rightarrow infty $ ) is one. However, in the finite SNR regime, the potential for a higher order diversity is witnessed before the diversity one regime takes over. Also, the diversity one regime is found to start at lower BER values for increased frame sizes. We also propose a phase rotation scheme for the OTFS using transcendental numbers and show that the OTFS, with this proposed scheme, extracts full diversity in the delay-Doppler domain.]]>186304930631794<![CDATA[Message Passing-Based Joint CFO and Channel Estimation in mmWave Systems With One-Bit ADCs]]>186306430771594<![CDATA[Max-Min Fairness User Scheduling and Power Allocation in Full-Duplex OFDMA Systems]]>186307830921520<![CDATA[Multiple-Jammer-Aided Secure Transmission With Receiver-Side Correlation]]>186309331031458<![CDATA[Secret Key Generation With Precoding and Role Reversal in MIMO Wireless Systems]]>18631043112935<![CDATA[Augmenting LoRaWAN Performance With Listen Before Talk]]>186311331281826<![CDATA[Treating Content Delivery in Multi-Antenna Coded Caching as General Message Sets Transmission: A DoF Region Perspective]]>$K$ -user $(M,N)$ broadcast channel with general message sets, with $M$ and $N$ being the number of transmit and receive antennas, respectively. Then for any given set of coded messages, we find its minimum normalized delivery time (NDT) by searching the optimal DoF tuple in the DoF regions. The obtained minimum NDT is optimal at antenna configuration $frac {M}{N} in big(0,1big]cup big [K, infty big)$ and is within a multiplicative gap of $frac {M}{N}$ to optimum at $frac {M}{N} in (1,K)$ . Our NDT results can be evaluated for any user demand with both centralized and decentralized cache placements.]]>186312931411122<![CDATA[Reverse TDD-Based Massive MIMO Systems With Underlay Spectrum Sharing]]>186314231601599<![CDATA[Efficient Downlink Channel Reconstruction for FDD Multi-Antenna Systems]]>186316131762453<![CDATA[High-Mobility Wideband Massive MIMO Communications: Doppler Compensation, Analysis and Scaling Laws]]>$1/sqrt {M}$ ($M$ is the number of transmit antennas) when $M$ is sufficiently large. The numerical results are provided to corroborate the proposed scheme.]]>186317731911472<![CDATA[3D Trajectory Optimization in Rician Fading for UAV-Enabled Data Harvesting]]>three-dimensional (3D) trajectory. Different from the existing works that assume the simplified line-of-sight (LoS) UAV-ground channels, we consider the more practically accurate angle-dependent Rician fading channels between the UAV and SNs with the Rician factors determined by the corresponding UAV-SN elevation angles. However, the formulated optimization problem is intractable due to the lack of a closed-form expression for a key parameter termed effective fading power that characterizes the achievable rate given the reliability requirement in terms of outage probability. To tackle this difficulty, we first approximate the parameter by a logistic (“S” shape) function with respect to the 3D UAV trajectory by using the data regression method. Then, the original problem is reformulated to an approximate form, which, however, is still challenging to solve due to its non-convexity. As such, we further propose an efficient algorithm to derive its suboptimal solution by using the block coordinate descent technique, which iteratively optimizes the communication scheduling, the UAV’s horizontal trajectory, and its vertical trajectory. The latter two subproblems are shown to be non-convex, while locally optimal solutions are obtained for them by using the successive convex approximation technique. Finally, extensive numer-
cal results are provided to evaluate the performance of the proposed algorithm and draw new insights on the 3D UAV trajectory under the Rician fading as compared to conventional LoS channel models.]]>186319232072734<![CDATA[Optimal Multi-User Scheduling for the Unbalanced Full-Duplex Buffer-Aided Relay Systems]]>186320832211591<![CDATA[Resource Allocation for Full-Duplex-Enabled Cognitive Backscatter Networks]]>Ambient backscatter communications (AmBC) enable wireless communications riding on ambient radio frequency (RF) signals instead of self-generated RF signals. Therefore, it has been considered as a promising candidate for the future Internet-of-Things with stringent energy and spectrum constraints. In this paper, we investigate a full-duplex-enabled cognitive backscatter network, in which an AmBC system underlays a primary cellular system, and the primary access point can transmit primary signals and receive backscatter signals simultaneously via full-duplex communications. We aim to maximize the throughput of the AmBC system while guaranteeing the minimum rate requirements of the primary system via joint time scheduling, transmit power allocation, and reflection coefficient (RC) adjustment. To solve the problem, we propose an iterative method utilizing block coordinated decent to partition the variables into the time scheduling variable and the joint transmit power allocation and RC adjustment variable. For the time scheduling problem, we first prove its convexity and then utilize the interior-point method to solve it. For the joint power allocation and RC adjustment problem, we resort to the concave-convex procedure to transform it into a sequence of convex optimization problems, and then adopt Lagrange dual decomposition to tackle these convex optimization problems. The simulation results demonstrate that the proposed method can significantly increase the throughput of the AmBC system with a fast convergence speed.]]>186322232351706<![CDATA[Generalized Channel Estimation and User Detection for Massive Connectivity With Mixed-ADC Massive MIMO]]>186323632502239<![CDATA[Mobile-Traffic-Aware Offloading for Energy- and Spectral-Efficient Large-Scale D2D-Enabled Cellular Networks]]>186325132642244<![CDATA[Secure Communications in Tiered 5G Wireless Networks With Cooperative Jamming]]>186326532802616<![CDATA[Deep Reinforcement Learning-Based Modulation and Coding Scheme Selection in Cognitive Heterogeneous Networks]]>186328132943276<![CDATA[Beamforming Design and Performance Analysis of Full-Duplex Cooperative NOMA Systems]]>186329533111515<![CDATA[Joint Mode Selection and Transceiver Design for Device-to-Device Communications Underlaying Multi-User MIMO Cellular Networks]]>186331233282486<![CDATA[IEEE Communications Society]]>186C3C3107