<![CDATA[ IEEE Transactions on Wireless Communications - new TOC ]]>
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TOC Alert for Publication# 7693 2018December 13<![CDATA[Table of contents]]>1712C17818239<![CDATA[IEEE Transactions on Wireless Communications]]>1712C2C284<![CDATA[Cooperative Network Operation Design for Mobility-Aware Cloud Radio Access Network]]>1712781978331296<![CDATA[Crowdsourcing in Wireless-Powered Task-Oriented Networks: Energy Bank and Incentive Mechanism]]>energy bank keeps accounts for all devices, authenticates the trading, and settles payments through a lossless bookkeeping-like manner. We analyze the employer’s expense-minimized and workers’ profit-maximized decisions and prove that the optimal decisions compose a Stackelberg equilibrium. To quantify the potential in energy saving, we further apply the framework to a relay-based sensor network where a source employs relays to forward data with a minimum rate requirement. An algorithm is developed for the NP-hard expense minimization problem. The simulation results reveal that our proposed framework and mechanism improve the energy efficiency by providing a win-win situation for both sides.]]>1712783478481886<![CDATA[Impact of Mobility on Physical Layer Security Over Wireless Fading Channels]]>1712784978641751<![CDATA[Secrecy Analysis of Distributed CDD-Based Cooperative Systems With Deliberate Interference]]>1712786578781579<![CDATA[A Dynamic Combined Flow Algorithm for the Two-Commodity Max-Flow Problem Over Delay-Tolerant Networks]]>1712787978932400<![CDATA[Block-Sparsity-Based Multiuser Detection for Uplink Grant-Free NOMA]]>1712789479091603<![CDATA[Channel Energy Statistics Learning in Compressive Spectrum Sensing]]>1712791079211795<![CDATA[An Efficient Incentive Mechanism for Device-to-Device Multicast Communication in Cellular Networks]]>individual rationality and incentive compatibility. Greedy algorithms with low complexity are developed based on local optimization to obtain fast solutions for contract design. A Lagrange multiplier method based iterative algorithm that can be proved to obtain optimal contracts under information asymmetry is also proposed. Numerical results show that the proposed mechanism can handle information asymmetry better and has a better performance than linear and step pricing schemes, increasing the expected profit by up to 2.49 times and 1.8 times, respectively.]]>1712792279352916<![CDATA[Constraint Hubs Deployment for Efficient Machine-Type Communications]]>1712793679511410<![CDATA[Oversampling in One-Bit Quantized Massive MIMO Systems and Performance Analysis]]>1712795279641113<![CDATA[A Unified Framework for the Tractable Analysis of Multi-Antenna Wireless Networks]]>$ell _{1}$ -induced norm of a Toeplitz matrix, and the other is given in a finite sum form. With a compact representation, the former incorporates many existing analytical results on single- and multi-antenna networks as special cases and leads to tractable expressions for evaluating the coverage probability in both ad hoc and cellular networks. While the latter is more complicated for numerical evaluation, it helps analytically gain key design insights. In particular, it helps prove that the coverage probability of ad hoc networks is a monotonically decreasing convex function of the transmitter density and that there exists a peak value of the coverage improvement when increasing the number of transmit antennas. On the other hand, in multi-antenna cellular networks, it is shown that the coverage probability is independent of the transmitter density and that the outage probability decreases exponentially as the number of transmit antennas increases.]]>1712796579801584<![CDATA[A 2-D Non-Stationary GBSM for Vehicular Visible Light Communication Channels]]>1712798179922725<![CDATA[CARES: Computation-Aware Scheduling in Virtualized Radio Access Networks]]>scheduling, to select the transmission of those frames that do not result in computational outages, and 2) modulation and coding scheme (MCS) selection, to downgrade the selected MCS in case no sufficient computational resources are available. We formulate the resulting problem as a joint optimization and compute the (asymptotically) optimal solution to this problem. We further show that this solution involves solving an NP-hard problem, and propose an algorithm to obtain an approximate solution that is computationally efficient while providing bounded performance over the optimal. We thoroughly evaluate the proposed approach via simulation, showing that it can provide savings as high as 80% of the computational resources while paying a small price in performance.]]>1712799380062549<![CDATA[Doppler Spectrum Analysis of a Roadside Scatterer Model for Vehicle-to-Vehicle Channels: An Indirect Method]]>1712800780212862<![CDATA[Quantized Constant Envelope Precoding With PSK and QAM Signaling]]>1712802280341607<![CDATA[Coded Pilot Random Access for Massive MIMO Systems]]>1712803580461659<![CDATA[Spatial Channel Covariance Estimation for the Hybrid MIMO Architecture: A Compressive Sensing-Based Approach]]>1712804780622806<![CDATA[Enabling Online Robust Barcode-Based Visible Light Communication With Realtime Feedback]]>1712806380763157<![CDATA[Decode-and-Forward Relaying for Cooperative NOMA Systems With Direct Links]]>1712807780932278<![CDATA[Joint Data-Energy Beamforming and Traffic Offloading in Cloud Radio Access Networks With Energy Harvesting-Aided D2D Communications]]>1712809481071630<![CDATA[Hybrid Precoding With Partially Connected Structure for Millimeter Wave Massive MIMO OFDM: A Parallel Framework and Feasibility Analysis]]>1712810881221496<![CDATA[Channel Estimation for TDS-OFDM Systems in Rapidly Time-Varying Mobile Channels]]>partitioned TDS-OFDM system” is proposed to improve the system performance by inserting multiple PN sequences to the middle and end parts of the channel as well. In addition to providing the reconstruction error performance, Bayesian Cramer–Rao lower bound is derived analytically. Also, the LMMSE-based symbol detection is employed. To alleviate the negative effects of inter-carrier-interference (ICI) occuring in mobile channels, ICI cancellation is applied to enhance the detection performance. The simulation results demonstrate that the proposed TDS-OFDM system is superior to the conventional system and its corresponding performance is able to approach the achievable lower performance bound.]]>1712812381351366<![CDATA[Modeling and Performance of Uplink Cache-Enabled Massive MIMO Heterogeneous Networks]]>large number of antennas employing cache-enabled uplink transmission. In particular, we formulate a scenario, where the users upload their content to their strongest BSs, which are Poisson point process distributed. In addition, the BSs, exploiting the benefits of massive MIMO, upload their contents to the core network by means of a finite-rate backhaul. After proposing the caching policies, where we propose the modified von Mises distribution as the popularity distribution function, we derive the outage probability and the average delivery rate by taking advantage of tools from the deterministic equivalent and stochastic geometry analyses. Numerical results investigate the realistic performance gains of the proposed heterogeneous cache-enabled uplink on the network in terms of cardinal operating parameters. For example, insights regarding the BSs storage size are exposed. Moreover, the impacts of the key parameters such as the file popularity distribution and the target bitrate are investigated. Specifically, the outage probability decreases if the storage size is increased, while the average delivery rate increases. In addition, the concentration parameter, defining the number of files stored at the intermediate nodes (popularity), affects the proposed metrics directly. Furthermore, a higher target rate results in higher outage because fewer users obey this constraint. Also, we demonstrate that a denser network decreases the outage and increases the delivery rate. Hence, the introduction of caching at the uplink of the system design ameliorates the network performance.]]>1712813681491839<![CDATA[A Tractable Analysis of the Blind Spot Probability in Localization Networks Under Correlated Blocking]]>blind spot. In this paper, we analyze the blind spot probability of a typical target by using stochastic geometry to model the randomness in the obstacle and anchor locations. In doing so, we handle correlated anchor blocking induced by the obstacles, unlike previous works that assume independent anchor blocking. We first characterize the regime over which the independent blocking assumption underestimates the blind spot probability of the typical target, which in turn is characterized as a function of the distribution of the visible area surrounding the target location. Since this distribution is difficult to exactly characterize, we formulate the nearest two-obstacle approximation, which is equivalent to considering correlated blocking for only the nearest two obstacles from the target and assuming independent blocking for the remaining obstacles. Based on this, we derive an approximate expression for the blind spot probability, which helps to determine the anchor deployment intensity needed for the blind spot probability of a typical target to be bounded above by a threshold, $mu $ .]]>1712815081642424<![CDATA[Angle Domain Channel Estimation in Hybrid Millimeter Wave Massive MIMO Systems]]>1712816581792927<![CDATA[Energy Efficient SWIPT Systems in Multi-Cell MISO Networks]]>1712818081941854<![CDATA[Bandwidth Partitioning and Downlink Analysis in Millimeter Wave Integrated Access and Backhaul for 5G]]>equal partition: when all SBSs obtain equal share of the backhaul BW; 2) instantaneous load-based partition: when the backhaul BW share of an SBS is proportional to its instantaneous load; and 3) average load-based partition: when the backhaul BW share of an SBS is proportional to its average load. Our analysis shows that depending on the choice of the partition strategy, there exists an optimal split of access and backhaul BW for which the rate coverage is maximized. Further, there exists a critical volume of cell-load (total number of users) beyond which the gains provided by the IAB-enabled network disappear and its performance converges to that of the traditional macro-only network with no SBSs.]]>1712819582102430<![CDATA[Coverage and Rate Analysis of Millimeter Wave NOMA Networks With Beam Misalignment]]>1712821182271657<![CDATA[Underwater Anchor-AUV Localization Geometries With an Isogradient Sound Speed Profile: A CRLB-Based Optimality Analysis]]>1712822882381271<![CDATA[Outage Probability Constrained MIMO-NOMA Designs Under Imperfect CSI]]>1712823982551199<![CDATA[Closed-Form Word Error Rate Analysis for Successive Interference Cancellation Decoders]]>${hat { {{x}}}}in mathbb {Z}^{n}$ from the linear observation ${{y}}= {A} {hat { {{x}}}} + {v}$ , where ${A}in mathbb {R}^{mtimes n}$ is a random matrix with independent and identically distributed (i.i.d.) standard Gaussian $mathcal {N}(0,1)$ entries, and ${v}in mathbb {R}^{m}$ is a noise vector with i.i.d. $mathcal {N}(0,sigma ^{2})$ entries with given $sigma $ . In digital communications, ${hat { {{x}}}}$ is typically uniformly distributed over an $n$ -dimensional box $mathcal {B}$ . For this detection problem, successive interference cancellation decoders are popular due to their low complexity, and a detailed analysis of their word error rates (WERs) is highly useful. In this paper, we derive closed-form WER expressions for two cases: (1) ${hat { {{x}}}}in mathbb {Z}^{n}$ is fixed and (2) ${hat { {{x}}}}$ is uniformly distributed over $mathcal {B}$ . We also investigate some of their properties in detail and show that they agree closely with simulated word error probab-
lities.]]>1712825682671039<![CDATA[Encryption Over the Air: Securing Two-Way Untrusted Relaying Systems Through Constellation Overlapping]]>1712826882821549<![CDATA[Optimal Control of Wireless Computing Networks]]>Augmented information (AgI) services allow users to consume information that results from the execution of a chain of service functions that process source information to create real-time augmented value. Applications include real-time analysis of remote sensing data, real-time computer vision, personalized video streaming, and augmented reality, among others. We consider the problem of optimal distribution of AgI services over a wireless computing network, in which nodes are equipped with both communication and computing resources. We characterize the wireless computing network capacity region and design a joint flow scheduling and resource allocation algorithm that stabilizes the underlying queuing system while achieving a network cost arbitrarily close to the minimum, with a tradeoff in network delay. Our solution captures the unique chaining and flow scaling aspects of AgI services while exploiting the use of the broadcast approach coding scheme over the wireless channel.]]>1712828382981453<![CDATA[Buffer-Aided Serial Relaying for FSO Communications: Asymptotic Analysis and Impact of Relay Placement]]>$N_{r}$ and an arbitrary buffer size $L$ . The closed-form evaluation links the system performance to the various network parameters in a simple and intuitive manner, and it is useful for offering clear insight on the impact of the relay placement and the selection of the buffer size for practical FSO systems. We prove that buffer-aided multi-hop systems can reap a diversity gain that ranges from $lceil ({N_{r}}/{2})rceil +1$ to $N_{r}+1$ compared with multi-hop buffer-free systems while the asymptotic APD values can range from $N_{r}$ to $(L-1)N_{r}$ for $Lgeq 2$ . Our analysis also highlights the optimal solutions capable of concurrently minimizing the OP and APD.]]>1712829983131230<![CDATA[Interference Exploitation in Full-Duplex Communications: Trading Interference Power for Both Uplink and Downlink Power Savings]]>1712831483291627<![CDATA[Moments of Interference in Vehicular Networks With Hardcore Headway Distance]]>1712833083411389<![CDATA[2-to-<inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> Coordinated Multipoint-Based Uplink Transmission in Ultra-Dense Cellular Networks]]>$M$ ) cooperating BSs with channel inversion power control in a multi-channel scenario. The performance of the proposed uplink CoMP is analyzed in the context of UDNs using stochastic geometry, in terms of outage probability and ergodic capacity, considering the effects of BS intensity, power control, number of cooperating nodes, and network tiers, first in a single-tier network, and later extended to a $K$ -tier heterogeneous network. Performance evaluation through extensive simulations is conducted and it is shown that the simulation results fit well with the analytical ones. The performance of the proposed scheme is then compared with that of the non-CoMP scheme, and it is found that the proposed scheme can significantly improve outage probability and ergodic capacity of mobile users.]]>1712834283562729<![CDATA[Spatiotemporal Model for Uplink IoT Traffic: Scheduling and Random Access Paradox]]>scheduling versus random access paradox actually depends on the operational scenario. Particularly, the RA-UL scheme offers low access delays but suffers from limited scalability, i.e., cannot support a large number of IoT devices. On the other hand, SC-UL transmission is better suited for higher device intensities and traffic rates.]]>1712835783721864<![CDATA[Lexicographic Codebook Design for OFDM With Index Modulation]]>1712837383872547<![CDATA[Spatio–Temporal Edge Service Placement: A Bandit Learning Approach]]>a priori, optimal placement decisions must be made while learning this benefit. We pose this problem as a novel combinatorial contextual bandit learning problem. It is “combinatorial” because only a limited number of edge sites can be rented to provide the edge service given the ASP’s budget. It is “contextual” because we utilize user context information to enable finer-grained learning and decision-making. To solve this problem and optimize the edge computing performance, we propose SEEN, a Spatial-temporal Edge sErvice placemeNt algorithm. Furthermore, SEEN is extended to scenarios with overlapping service coverage by incorporating a disjunctively constrained knapsack problem. In both cases, we prove that our algorithm achieves a sublinear regret bound when it is compared with an Oracle algorithm that knows the exact benefit information. Simulations are carried out on a real-world dataset, whose results show that SEEN significantly outperforms benchmark solutions.]]>1712838884012187<![CDATA[Machine Learning Methods for RSS-Based User Positioning in Distributed Massive MIMO]]>proof-of-concept that we can localize users by training an ML model with noise-free RSS and using the trained model to estimate the test user locations from their noisy RSS. We consider two GP methods for localization, namely, the conventional GP (CGP) and the numerical approximation GP (NaGP). We find that the CGP provides unrealistically small $2sigma $ error-bars on the location estimates. Therefore, we derive the true predictive distribution and employ NaGP to obtain realistic $2sigma $ error-bars on the location estimates. Next, we derive a Bayesian Cramer–Rao lower bound (BCRLB) on the root-mean-squared-error (RMSE) performance of the two GP methods. Numerical studies reveal that: 1) the NaGP indeed provides realistic $2sigma $ error-bars on the estimated locations; 2) both the CGP and NaGP achieve RMSEs that are close to the BCRLBs; 3) the presence of correlated shadowing improves the RMSE performance; and 4) extrapolation to the zero input noise scenario can significantly improve the RMSE achieved by the NaGP.]]>1712840284171712<![CDATA[On Contract Design for Incentivizing Users in Cooperative Content Delivery With Adverse Selection]]>1712841884322481<![CDATA[FDM-Structured Preamble Optimization for Channel Estimation in MIMO-OQAM/FBMC Systems]]>1712843384431043<![CDATA[Security-Reliability Tradeoff for Distributed Antenna Systems in Heterogeneous Cellular Networks]]>1712844484561732<![CDATA[Adaptive Resource Allocation for Secure Two-Hop Relaying Communication]]>a-priori statistical information on the fading channels. The simulation results demonstrate the effectiveness of the proposed schemes over benchmark schemes under various secrecy constraints and signal-to-noise power ratio regimes.]]>1712845784721253<![CDATA[Achievable-Rate-Enhancing Self-Interference Cancellation for Full-Duplex Communications]]>1712847384841427<![CDATA[Gridless Channel Estimation for Mixed One-Bit Antenna Array Systems]]>1712848585013258<![CDATA[Massive MIMO With Antenna Selection: Fundamental Limits and Applications]]>fixed-size subset of the available antennas with the strongest channel gains. For this setup, the input-output mutual information of the system is shown to be well-approximated by a normal random variable when the number of transmit antennas is large. The mean of this random variable grows proportional to the number of antennas and its variance vanishes in the large-system limit. This behavior of the mutual information generalizes the well-known channel hardening property in massive MIMO systems to the cases with antenna selection. Our investigations show that 90% of the ergodic rate achieved by full antenna selection can be achieved by selecting less than 30% of the transmit antennas. Using large-system analysis, we drive an analytical expression for the number of selected antennas that maximizes the energy efficiency. This number is also derived for the case where a certain fraction of the totally achievable rate is aimed to be achieved. Our numerical investigations demonstrate a close match between the analytical and simulation results even for scenarios with not-so-large dimensions.]]>1712850285161499<![CDATA[Achieving Covert Wireless Communications Using a Full-Duplex Receiver]]>1712851785301426<![CDATA[Deployment and Trajectory Optimization of UAVs: A Quantization Theory Approach]]>1712853185461655<![CDATA[Introducing IEEE Collabratec]]>1712854785472137<![CDATA[IEEE Access]]>1712854885481293<![CDATA[IEEE Communications Society]]>1712C3C373<![CDATA[Blank page]]>1712C4C44