<![CDATA[ IEEE Transactions on Wireless Communications - new TOC ]]>
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TOC Alert for Publication# 7693 2019August 22<![CDATA[Table of contents]]>188C1C4174<![CDATA[IEEE Transactions on Wireless Communications]]>188C2C2119<![CDATA[Analysis of Non-Stationary 3D Air-to-Air Channels Using the Theory of Algebraic Curves]]>188376737803084<![CDATA[Partially Informed Transmitter-Based Optical Space Shift Keying Under Atmospheric Turbulence]]>188378137961840<![CDATA[Unified Analysis of HetNets Using Poisson Cluster Processes Under Max-Power Association]]>SINR), of a typical user in a $K$ -tier HetNet under a $max $ power-based association strategy, where the BS locations of each tier follow either a Poisson point process (PPP) or a PCP. The key enabling step involves conditioning on the parent PPPs of all the PCPs, which allows us to express the coverage probability as a product of sum-product and probability generating functionals (PGFLs) of the parent PPPs. In addition to several useful insights, our analysis provides a rigorous way to study the impact of the cluster size on the ${it SINR}$ distribution, which was not possible using the existing PPP-based models.]]>188379738121664<![CDATA[Structured Turbo Compressed Sensing for Downlink Massive MIMO-OFDM Channel Estimation]]>188381338262385<![CDATA[Closed-Form Algebraic Solutions for Angle-of-Arrival Source Localization With Bayesian Priors]]>188382738422101<![CDATA[On Channel Sounding With Switched Arrays in Fast Time-Varying Channels]]>188384338554394<![CDATA[A Cluster-Based Channel Model for Massive MIMO Communications in Indoor Hotspot Scenarios]]>188385638704656<![CDATA[Fundamental Limits of Memory-Latency Tradeoff in Fog Radio Access Networks Under Arbitrary Demands]]>expected normalized delivery time (NDT) and the peak NDT which measures the transmission latency. We propose achievable transmission policies, and derive an information-theoretic bound on the expected NDT under uniform popularity distribution. The analytical results show that the proposed scheme is within a gap of 2.58 from the derived bound for both the expected NDT under uniform popularity distribution and the peak NDT. Next, we investigate the expected NDT under an arbitrary popularity distribution for an F-RAN with transmitter-side caches only. The achievable and information-theoretic bounds on the expected NDT are derived, where we analytically prove that our proposed scheme is optimal within a gap of two independent of the popularity distribution.]]>188387138861653<![CDATA[Resource Allocation for Vehicular Communications With Low Latency and High Reliability]]>188388739021909<![CDATA[Downlink Non-Orthogonal Multiple Access Without SIC for Block Fading Channels: An Algebraic Rotation Approach]]>$n$ -dimensional constellations corresponding to the same algebraic lattices from a number field, allowing every user attains full diversity gain with single-user decoding, i.e., no successive interference cancellation (SIC). The minimum product distances of the proposed scheme with arbitrary power allocation factor are analyzed and their upper bounds are derived. Within the proposed class of schemes, we also identify a special family of NOMA schemes based on lattice partitions of the underlying ideal lattices, whose minimum product distances can be easily controlled. Our analysis shows that among the proposed schemes, the lattice-partition-based schemes achieve the largest minimum product distances of the superimposed constellations, which are closely related to the symbol error rates for receivers with single-user decoding. The simulation results are presented to verify our analysis and to show the effectiveness of the proposed schemes as compared to benchmark NOMA schemes. Extensions of our design to the multi-antenna case are also considered where similar analysis and results are presented.]]>188390339181601<![CDATA[Platoon Cooperation in Cellular V2X Networks for 5G and Beyond]]>188391939322766<![CDATA[Reinforcement Learning for Self Organization and Power Control of Two-Tier Heterogeneous Networks]]>$epsilon $ -optimality with high probability is provided. We demonstrate, at the density of several thousands femtocells per km^{2}, the required quality of service of a macrocell user can be maintained via the proper selection of independent or cooperative learning and appropriate Markov state models.]]>188393339472755<![CDATA[On the Delay/Throughput-Security Tradeoff in Wiretap TDMA Networks With Buffered Nodes]]>188394839601657<![CDATA[Hybrid NOMA for an Energy Harvesting MAC With Non-Ideal Batteries and Circuit Power]]>188396139731560<![CDATA[Lossy-Forward Relaying for Lossy Communications: Rate-Distortion and Outage Probability Analyses]]>188397439861806<![CDATA[Energy Efficiency of Massive MIMO Systems With Low-Resolution ADCs and Successive Interference Cancellation]]>188398740022047<![CDATA[Terminal Orientation in OFDM-Based LiFi Systems]]>$5times 3.5times 3,,text{m}^{3}$ indoor room.]]>188400340162683<![CDATA[Timely Updates in Energy Harvesting Two-Hop Networks: Offline and Online Policies]]>timely fashion that minimizes the age of information, defined as the time elapsed since the most recent update at the destination was generated at the source. The source and the relay communicate using energy harvested from nature, which is stored in infinite-sized batteries. Both nodes use fixed transmission rates, and hence updates incur fixed delays (service times). Two problems are formulated: an offline problem, in which the energy arrival information is known a priori, and an online problem, in which such information is revealed casually over time. In both problems, it is shown that it is optimal to transmit updates from the source just in time as the relay is ready to forward them to the destination, making the source and the relay act as one combined node. A recurring theme in the optimal policy is that updates should be as uniformly spread out over time as possible, subject to energy causality and service time constraints. This is perfectly achieved in the offline setting, and is achieved almost surely in the online setting by a best effort policy.]]>188401740301089<![CDATA[Spatially Modulated Code-Division Multiple-Access for High-Connectivity Multiple Access]]>188403140461872<![CDATA[Signal Shaping for Generalized Spatial Modulation and Generalized Quadrature Spatial Modulation]]>188404740591963<![CDATA[Multi-Cell Sparse Activity Detection for Massive Random Access: Massive MIMO Versus Cooperative MIMO]]>188406040741864<![CDATA[Cognitive Multi-Hop Multi-Branch Relaying: Spectrum Leasing and Optimal Power Allocation]]>$M$ in both the primary and secondary networks, where $M$ is the number of cognitive branches. The simulation results also show that optimizing the allocation of power significantly decreases the risk of spectrum leasing failure.]]>188407540881734<![CDATA[Covert Transmission With a Self-Sustained Relay]]>$xi ^{ast }$ at the source based on which we determine the maximum effective covert rate $Psi ^{ast }$ subject to a given covertness constraint on $xi ^{ast }$ . Our analysis shows that $xi ^{ast }$ is the same for the TS and PS schemes, which leads to the fact that the cost of achieving $Psi ^{ast }$ in both the two schemes in terms of the required increase in the energy conversion efficiency at the relay is the same, although the values of $Psi ^{ast }$ in these two schemes can be different in specific scenarios. For example, the TS scheme outperforms the PS scheme in terms of achieving a higher $Psi ^{ast }$ when the transmit power at the source is relatively low. If the covertness constraint is tighter than a specific value, it is the covertness constraint that limits $Psi ^{ast }$ , and otherwise, it is upper bound on the energy conversion efficiency that limits $Psi ^{ast }$ .]]>188408941021174<![CDATA[Stochastic Interference Modeling and Experimental Validation for Pulse-Based Terahertz Communication]]>188410341152560<![CDATA[A Supplier-Firm-Buyer Framework for Computation and Content Resource Assignment in Wireless Virtual Networks]]>188411641282179<![CDATA[Closed-Form Analysis of Non-Linear Age of Information in Status Updates With an Energy Harvesting Transmitter]]>188412941421871<![CDATA[Body-Guided Galvanic Coupling Communication for Secure Biometric Data]]>−6 with a transmit power of −2 dBm, in addition to over 7$times$ reduction of signal radiation outside the body compared to capacitive coupling.]]>188414341562738<![CDATA[Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication]]>188415741702690<![CDATA[Energy Efficient Optimization of Base Station Intensities for Hybrid RF/VLC Networks]]>188417141831735<![CDATA[Adaptive Grouping Sparse Bayesian Learning for Channel Estimation in Non-Stationary Uplink Massive MIMO Systems]]>188418441981467<![CDATA[IEEE Communications Society]]>188C3C3109