Downlink Channel Covariance Matrix Reconstruction for FDD Massive MIMO Systems with Limited Feedback

The downlink channel covariance matrix (CCM) acquisition is the key step for the practical performance of massive multiple-input and multiple-output (MIMO) systems, including beamforming, channel tracking, and user scheduling. However, this task is challenging in the popular frequency division duplex massive MIMO systems with Type I codebook due to the limited channel information feedback. In this paper, we propose a novel formulation that leverages the structure of the codebook and feedback values for an accurate estimation of the downlink CCM. Then, we design a cutting plane algorithm to consecutively shrink the feasible set containing the downlink CCM, enabled by the careful design of pilot weighting matrices. Theoretical analysis shows that as the number of communication rounds increases, the proposed cutting plane algorithm can recover the ground-truth CCM. Numerical results are presented to demonstrate the superior performance of the proposed algorithm over the existing benchmark in CCM reconstruction

Stochastic switching of TiO2 based memristive devices with identical initial memory states

In this work, we show that identical TiO2-based memristive devices that possess the same initial resistive states are only phenomenologically similar as their internal structures may vary significantly, which could render quite dissimilar switching dynamics. We experimentally demonstrated that the resistive switching of practical devices with similar initial states could occur at different programming stimuli cycles. We argue that similar memory states can be transcribed via numerous distinct active core states through the dissimilar reduced TiO2-x filamentary distributions. Our hypothesis was finally verified via simulated results of the memory state evolution, by taking into account dissimilar initial filamentary distribution

6G Non-Terrestrial Networks Enabled Low-Altitude Economy: Opportunities and Challenges

The unprecedented development of non-terrestrial networks (NTN) utilizes the low-altitude airspace for commercial and social flying activities. The integration of NTN and terres- trial networks leads to the emergence of low-altitude economy (LAE). A series of LAE application scenarios are enabled by the sensing, communication, and transportation functionalities of the aircrafts. The prerequisite technologies supporting LAE are introduced in this paper, including the network coverage and aircrafts detection. The LAE functionalities assisted by aircrafts with respect to sensing and communication are then summarized, including the terrestrial and non-terrestrial targets sensing, ubiquitous coverage, relaying, and traffic offloading. Finally, several future directions are identified, including aircrafts collaboration, energy efficiency, and artificial intelligence enabled LAE.Comment: This paper has been submitted to IEEE for possible publicatio

Joint Beamforming Design and Stream Allocation for Non-Coherent Joint Transmission in Cell-Free MIMO Networks

We consider joint beamforming and stream allocation to maximize the weighted sum rate (WSR) for non-coherent joint transmission (NCJT) in user-centric cell-free MIMO networks, where distributed access points (APs) are organized in clusters to transmit different signals to serve each user equipment (UE). We for the first time consider the common limits of maximum number of receive streams at UEs in practical networks, and formulate a joint beamforming and transmit stream allocation problem for WSR maximization under per-AP transmit power constraints. Since the integer number of transmit streams determines the dimension of the beamformer, the joint optimization problem is mixed-integer and nonconvex with coupled decision variables that is inherently NP-hard. In this paper, we first propose a distributed low-interaction reduced weighted minimum mean square error (RWMMSE) beamforming algorithm for WSR maximization with fixed streams. Our proposed RWMMSE algorithm requires significantly less interaction across the network and has the current lowest computational complexity that scales linearly with the number of transmit antennas, without any compromise on WSR. We draw insights on the joint beamforming and stream allocation problem to decouple the decision variables and relax the mixed-integer constraints. We then propose a joint beamforming and linear stream allocation algorithm, termed as RWMMSE-LSA, which yields closed-form updates with linear stream allocation complexity and is guaranteed to converge to the stationary points of the original joint optimization problem. Simulation results demonstrate substantial performance gain of our proposed algorithms over the current best alternatives in both WSR performance and convergence time

Origin of the OFF state variability in ReRAM cells

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This work exploits the switching dynamics of nanoscale resistive random access memory (ReRAM) cells with particular emphasis on the origin of the observed variability when cells are consecutively cycled/programmed at distinct memory states. It is demonstrated that this variance is a common feature of all ReRAM elements and is ascribed to the formation and rupture of conductive filaments that expand across the active core, independently of the material employed as the active switching core, the causal physical switching mechanism, the switching mode (bipolar/unipolar) or even the unit cells’ dimensions. Our hypothesis is supported through both experimental and theoretical studies on TiO2 and In2O3 : SnO2 (ITO) based ReRAM cells programmed at three distinct resistive states. Our prototypes employed TiO2 or ITO active cores over 5 × 5μm2 and 100 × 100 μm2 cell areas, with all tested devices demonstrating both unipolar and bipolar switching modalities. In the case of TiO2-based cells, the underlying switching mechanism is based on the non-uniform displacement of ionic species that foster the formation of conductive filaments. On the other hand, the resistive switching observed in the ITO-based devices is considered to be due to a phase change mechanism. The selected experimental parameters allowed us to demonstrate that the observed programming variance is a common feature of all ReRAM devices, proving that its origin is dependent upon randomly oriented local disorders within the active core that have a substantial impact on the overall state variance, particularly for high-resistive states

Frame Structure and Protocol Design for Sensing-Assisted NR-V2X Communications

The emergence of the fifth-generation (5G) New Radio (NR) technology has provided unprecedented opportunities for vehicle-to-everything (V2X) networks, enabling enhanced quality of services. However, high-mobility V2X networks require frequent handovers and acquiring accurate channel state information (CSI) necessitates the utilization of pilot signals, leading to increased overhead and reduced communication throughput. To address this challenge, integrated sensing and communications (ISAC) techniques have been employed at the base station (gNB) within vehicle-to-infrastructure (V2I) networks, aiming to minimize overhead and improve spectral efficiency. In this study, we propose novel frame structures that incorporate ISAC signals for three crucial stages in the NR-V2X system: initial access, connected mode, and beam failure and recovery. These new frame structures employ 75% fewer pilots and reduce reference signals by 43.24%, capitalizing on the sensing capability of ISAC signals. Through extensive link-level simulations, we demonstrate that our proposed approach enables faster beam establishment during initial access, higher throughput and more precise beam tracking in connected mode with reduced overhead, and expedited detection and recovery from beam failures. Furthermore, the numerical results obtained from our simulations showcase enhanced spectrum efficiency, improved communication performance and minimal overhead, validating the effectiveness of the proposed ISAC-based techniques in NR V2I networks

Communication-efficient distributed precoding design for Massive MIMO

A communication-efficient distributed precoding scheme was proposed for multi-baseband processing unit (BBU) baseband processing architecture, aiming to reduce fronthaul data exchange and computational complexity between BBUs.Firstly, a distributed framework based on R-WMMSE algorithm was proposed, which utilized the subspace property of the optimal solution to compress the interactive data losslessly, thereby reducing data exchange.Furthermore, two learnable compression modules based on matrix multiplication were designed, using optimized computing structures and matrix parameters to reduce the parameters and computations while maintaining function expressiveness.Finally, the learnable modules and the distributed precoding framework were jointly optimized with achievable rate as the optimization objective to obtain the final model.The proposed scheme can achieve guaranteed precoding performance under lower requirements on data interaction and computational complexit