We propose a computationally-efficient soft-output detector for multiple-input multiple-output channels based on augmented channel puncturing in order to reduce tree processing complexity. The proposed detector, dubbed augmented WL detector (AWLD), employs a punctured channel with a special structure derived by triangulizing the original channel in augmented form, followed by Gaussian elimination. We prove that these punctured channels are optimal in maximizing the lower-bound on the achievable information rate (AIR) based on a newly proposed mismatched detection model. We show that the AWLD decomposes into a minimum mean-square error (MMSE) prefilter and channel-gain compensation stages, followed by a regular unaugmented WL detector (WLD). It attains the same performance as the existing AIR partial marginalization (AIR-PM) detector, but with much simpler processing.
A family of low-complexity detection schemes based on channel matrix puncturing targeted for large multiple-input multiple-output (MIMO) systems is proposed. It is well-known that the computational cost of MIMO detection based on QR decomposition is directly proportional to the number of non-zero entries involved in back-substitution and slicing operations in the triangularized channel matrix, which can be too high for low-latency applications involving large MIMO dimensions. By systematically puncturing the channel to have a specific structure, it is demonstrated that the detection process ca…
Channel puncturing transforms a multiple-input multiple-output (MIMO) channel into a sparse lower-triangular form using the so-called WL decomposition scheme in order to reduce tree-based detection complexity. We propose computationally efficient soft-output detectors based on two forms of channel puncturing: augmented and two-sided. The augmented WL detector (AWLD) employs a punctured channel derived by triangularizing the true channel in augmented form, followed by leftsided Gaussian elimination. The two-sided WL detector (dubbed WLZ) employs right-sided reduction and left-sided elimination …
We consider the problem of efficient ultra-massive multiple-input multiple-output (UM-MIMO) data detection in terahertz (THz)-band non-orthogonal multiple access (NOMA) systems. We argue that the most common THz NOMA configuration is power-domain superposition coding over quasi-optical doubly-massive MIMO channels. We propose spatial tuning techniques that modify antenna subarray arrangements to enhance channel conditions. Towards recovering the superposed data at the receiver side, we propose a family of data detectors based on low-complexity channel matrix puncturing, in which higher-order d…
In this thesis, we investigate the problem of efficient data detection in large MIMO and high order MU-MIMO systems. First, near-optimal low-complexity detection algorithms are proposed for regular MIMO systems. Then, a family of low-complexity hard-output and soft-output detection schemes based on channel matrix puncturing targeted for large MIMO systems is proposed. The performance of these schemes is characterized and analyzed mathematically, and bounds on capacity, diversity gain, and probability of bit error are derived. After that, efficient high order MU-MIMO detectors are proposed, bas…
Lattice reduction algorithms, such as the LLL algorithm, have been proposed as preprocessing tools in order to enhance the performance of suboptimal receivers in MIMO communications. In this paper we introduce a new kind of lattice reduction-aided decoding technique, called augmented lattice reduction, which recovers the transmitted vector directly from the change of basis matrix, and therefore doesn't entail the computation of the pseudo-inverse of the channel matrix or its QR decomposition. We prove that augmented lattice reduction attains the maximum receive diversity order of the channel; …
We address receiver (RX) signal processing in MIMO systems under in-phase/quadrature (I/Q) imbalance, which causes cross-talk of mirror-subcarriers in OFDM systems. We extend the typically reported single-user studies to uplink OFDMA-based multiuser MIMO, with simultaneous user multiplexing in frequency and spatial domains. We also incorporate multiple external interferers, for modeling challenging conditions in heterogeneous networks. In the signal processing developments, we exploit the augmented subcarrier processing, which processes each subcarrier jointly with its counterpart at the image…
In limited feedback multi-user multiple-input multiple-output (MU-MIMO) cellular networks, users send quantized information about the channel conditions to the associated base station (BS) for downlink beamforming. However, channel quantization and beamforming have been treated as two separate tasks conventionally, which makes it difficult to achieve global system optimality. In this paper, we propose an augmented deep unfolding (ADU) approach that jointly optimizes the beamforming scheme at the BSs and the channel quantization scheme at the users. In particular, the classic WMMSE beamformer i…
Enhanced mobile broadband (eMBB) and ultrareliable and low-latency communications (URLLC) are two major expected services in the fifth-generation mobile communication systems (5G). Specifically, eMBB applications support extremely high data rate communications, while URLLC services aim to provide stringent latency with high reliability communications. Due to their differentiated quality-of-service (QoS) requirements, the spectrum sharing between URLLC and eMBB services becomes a challenging scheduling issue. In this paper, we aim to investigate the URLLC and eMBB coscheduling/coexistence probl…
Augmented and virtual reality systems (AR/VR) are rapidly becoming key components of the wireless landscape. For immersive AR/VR experience, these devices should be able to construct accurate depth perception of the surrounding environment. Current AR/VR devices rely heavily on using RGB-D depth cameras to achieve this goal. The performance of these depth cameras, however, has clear limitations in several scenarios, such as the cases with shiny objects, dark surfaces, and abrupt color transition among other limitations. In this paper, we propose a novel solution for AR/VR depth map constructio…
This paper investigates the system achievable rate and optimization for the multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) system with an energy harvesting (EH) relay. Firstly we propose a time switchingbased relaying (TSR) protocol to enable the simultaneous information processing and energy harvesting at the relay. Then, we discuss its achievable rate performance theoretically and formulated an optimization problem to maximize the system achievable rate. As the problem is difficult to solve, we design an Augmented Lagrangian Penalty Function (ALPF) me…
DiffPace: Diffusion-based Plug-and-play Augmented Channel Estimation in mmWave and Terahertz Ultra-Massive MIMO Systems
Terahertz Wireless Communications (TWC) Laboratory, Shanghai Jiao Tong University（太赫兹无线通信实验室，上海交通大学）；Cooperative Medianet Innovation Center (CMIC), School of Information Science and Electronic Engineering, Shanghai Jiao Tong University（协作中位网创新中心（CMIC），信息科学与电子工程学院，上海交通大学）；Institute for Digital Communications, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)（数字通信研究所，弗赖堡-亚历山大-大学埃尔朗根-纽伦堡（FAU））
In this paper, we consider the precoder design for an underloaded or critically loaded downlink multi-user multiple-input multiple-output (MIMO) communication system. We propose novel precoding and decoding schemes which enhance system performance based on rate splitting at the transmitter and single-stage successive interference cancellation at the receivers. The proposed successive null-space (SNS) precoding utilizes linear combinations of the null-space basis vectors of the successively augmented MIMO channel matrices of the users as precoding vectors to adjust the inter-user-interference e…
In this paper, we examine cognitive radio systems that evolve dynamically over time due to changing user and environmental conditions. To combine the advantages of orthogonal frequency division multiplexing (OFDM) and multiple-input, multiple-output (MIMO) technologies, we consider a MIMO-OFDM cognitive radio network where wireless users with multiple antennas communicate over several non-interfering frequency bands. As the network's primary users (PUs) come and go in the system, the communication environment changes constantly (and, in many cases, randomly). Accordingly, the network's unlicen…
Multi-Agent Reinforcement Learning for Movable Antenna-aided Cell-Free Massive MIMO Systems
State Key Laboratory of Advanced Rail Autonomous Operation（先进轨道交通运行安全国家实验室）；School of Electronic and Information Engineering, Beijing Jiaotong University（北京交通大学电子与信息技术工程学院）；School of Communications and Information Engineering, Xi’an University of Posts and Telecommunications（西安邮电大学通信与信息工程学院）；Purple Mountain Laboratories（紫金山实验室）；ZTE Corporation（中兴通讯股份有限公司）；State Key Laboratory of Mobile Network and Mobile Multimedia Technology（移动网络与移动多媒体技术国家重点实验室）；University of New South Wales（新南威尔士大学）
Large Language Model Empowered Next-Generation MIMO Networks: Fundamentals, Challenges, and Visions
State Key Laboratory of Advanced Rail Autonomous Operation（先进轨道交通自主运行状态关键实验室）；Beijing Jiaotong University（北京交通大学）；School of Electronics and Information Engineering（电子与信息工程学院）；University of Hong Kong（香港大学）；College of Computing & Data Science（计算与数据科学学院）；Nanyang Technological University（南洋理工大学）；Hong Kong University of Science and Technology（香港科技大学）
Cramér-Rao Bound Optimization for Massive MIMO DFRC Systems with 1-Bit DACs and ADCs
State Key Laboratory of Mathematical Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences（中国科学院数学与系统科学研究院）；Ministry of Education Key Laboratory of Mathematics and Information Networks, School of Mathematical Sciences, Beijing University of Posts and Telecommunications（北京邮电大学数学科学与技术学院）
Recursive Flow: A Generative Framework for MIMO Channel Estimation
College of Information Science and Electronic Engineering, Zhejiang University（浙江大学信息与电子工程学院）；Research Institute for Digital Future, Khalifa University（哈利法大学数字未来研究院）
