Hybrid Transceiver Design and Sparse CSI Learning in MU THz Hybrid MIMO systems

被引:0
|
作者
Garg, Abhisha [1 ]
Kumar, Akash [1 ]
Srivastava, Suraj [2 ]
Jagannatham, Aditya K. [1 ]
机构
[1] Indian Inst Technol Kanpur, Dept Elect Engn, Kanpur, Uttar Pradesh, India
[2] Indian Inst Technol Jodhpur, Dept Elect Engn, Jodhpur, Rajasthan, India
关键词
CHANNEL ESTIMATION;
D O I
10.1109/SPCOM60851.2024.10631591
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper conceives a new generalized simultaneous orthogonal matching pursuit (GSOMP)-based algorithm to effectively estimate the sparse channel state information (CSI) in a multiuser (MU) THz hybrid MIMO system. The proposed framework also incorporates low-resolution analog-to-digital converters (ADCs) together with a sampled version of the transmit pulse shaping filter. The proposed techniques are based on a practical dual-wideband THz channel model that is developed initially, which considers both the spatial and frequency wide-band effects. The model also embraces the reflection, absorption and free-spaces losses that are a characteristic feature of the THz band. Subsequently, a novel MU hybrid transceiver design framework is advanced, based on the generalized alternating direction method of multipliers (MU-GADMM), which generates a new set of basis vectors toward robust approximation of the optimal precoder, in order to account for the beamsquint effect. Extensive simulations are conducted to evaluate the performance of the proposed CSI learning and beamforming techniques in a practical THz channel generated using the high-resolution transmission (HITRAN) database.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] OTFS Transceiver Design and Sparse Doubly-Selective CSI Estimation in Analog and Hybrid Beamforming Aided mmWave MIMO Systems
    Srivastava, Suraj
    Singh, Rahul Kumar
    Jagannatham, Aditya K.
    Chockalingam, A.
    Hanzo, Lajos
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2022, 21 (12) : 10902 - 10917
  • [2] Hybrid Distributed MRC With Imperfect CSI for MU-MIMO Systems
    Li, Shuang
    Smith, Peter J.
    Dmochowski, Pawel A.
    IEEE COMMUNICATIONS LETTERS, 2021, 25 (09) : 3109 - 3113
  • [3] Hybrid Transceiver Design for Tera-Hertz MIMO Systems Relying on Bayesian Learning Aided Sparse Channel Estimation
    Srivastava, Suraj
    Tripathi, Ajeet
    Varshney, Neeraj
    Jagannatham, Aditya K.
    Hanzo, Lajos
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2023, 22 (04) : 2231 - 2245
  • [4] Robust THP Transceiver Design with Partial CSI in TDD MU-MIMO Systems
    Ji, Wei
    Qiu, Ling
    Li, Yuanjie
    2018 IEEE 88TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL), 2018,
  • [5] Transceiver Design for MIMO Wireless Systems Incorporating Hybrid ARQ
    Lee, Jungwon
    Lou, Hui-Ling
    Toumpakaris, Dimitris
    Jang, Edward W.
    Cioffi, John M.
    IEEE COMMUNICATIONS MAGAZINE, 2009, 47 (01) : 32 - 40
  • [6] Beam Misalignment Aware Hybrid Transceiver Design in mmWave MIMO Systems
    Pradhan, Chandan
    Li, Ang
    Zhuo, Li
    Li, Yonghui
    Vucetic, Branka
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (10) : 10306 - 10310
  • [7] An Iterative Hybrid Transceiver Design Algorithm for Millimeter Wave MIMO Systems
    Chen, Chiao-En
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2015, 4 (03) : 285 - 288
  • [8] Transceiver Design for MIMO systems with imperfect CSI at Transmitter and Receiver
    Thian, Boon Sim
    Zhou, Sheng
    Goldsmith, Andrea
    2011 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2011,
  • [9] A Deep Learning-based Hybrid Precoding with Attention Mechanism for THz Massive MU-MIMO Systems
    Liu, Zhongyan
    Ke, Huamei
    Zhang, Yinghui
    Zhao, Xin
    Liu, Yang
    Jin, Minglu
    ICC 2023-IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2023, : 5639 - 5644
  • [10] Dictionary-Learning (DL)-Based Sparse CSI Estimation in Multiuser Terahertz (THz) Hybrid MIMO Systems Under Hardware Impairments and Beam-Squint Effect
    Maity, Priyanka
    Srivastava, Suraj
    Khatri, Sunaina
    Jagannatham, Aditya K.
    IEEE ACCESS, 2022, 10 : 113699 - 113714