计算机与现代化 ›› 2025, Vol. 0 ›› Issue (01): 67-73.doi: 10.3969/j.issn.1006-2475.2025.01.011

• 网络与通信 • 上一篇    下一篇

基于BD格缩减辅助的连续干扰消除检测算法





  

  1. (大连民族大学信息与通信工程学院,辽宁 大连 116000)
  • 出版日期:2025-01-27 发布日期:2025-01-27
  • 基金资助:
    国家自然科学基金资助项目(62071084)

BD Based Lattice Reduction Assisted Continuous Interference Cancellation Detection Algorithm

  1. (College of Information and Communication Engineering, Dalian Minzu University, Dalian 116000, China)
  • Online:2025-01-27 Published:2025-01-27

摘要: 在多用户MIMO-OFDM通信系统中,随着接入用户与收发天线数量的不断增多会导致严重的多址干扰和多流干扰,因此可利用多用户BD思想对同一频段上的多个用户进行信号检测。本文提出一种基于BD的格缩减辅助的连续干扰消除算法。首先利用2次奇异值分解技术将多用户总信道分解为多个相互独立的单用户子信道,理论上可以完全消除多址干扰。然后再利用格缩减技术与QR排序技术对分解后的信道进行排序优化,在提高信道矩阵正交性的同时降低计算复杂度。最后对接收端接收信号执行基于MMSE准则的连续干扰消除检测,逐层恢复原始信号,消除每个用户的多流干扰。通过仿真实验表明,本文提出的算法可以在不提升计算复杂度的基础上显著提升通信系统的检测性能,当误码率为10-3时比传统的多用户BD检测算法性能提高了5.5 dB,比结合了BD的多用户MMSE检测算法和ZF检测算法性能提升了4 dB左右。

关键词: MIMO, OFDM, 格缩减, BD, 连续干扰消除

Abstract: In multi-user MIMO-OFDM communication systems, the increasing number of access users and transmitting/receiving antennas leads to severe multi-user interference and multi-stream interference. Therefore, a multi-user block diagonalization(BD)approach is employed to perform signal detection for multiple users on the same frequency band. An algorithm for continuous interference elimination based on BD and lattice reduction is proposed. Initially, the total channel for multiple users is decomposed into several mutually independent single-user subchannels using two singular value decomposition techniques. In theory, this step can completely eliminate multi-user interference. Subsequently, lattice reduction and QR sorting techniques are applied to optimize the decomposed channels, enhancing the orthogonality of the channel matrix while reducing computational complexity. Finally, a continuous interference elimination detection based on the minimum mean square error (MMSE) criterion is performed on the received signals at the receiver. This process systematically restores the original signals, eliminating multi-stream interference for each user. Simulation experiments demonstrate that the proposed algorithm significantly improves the detection performance of the communication system without increasing computational complexity. At a bit error rate of 10-3, the performance enhancement is 5.5 dB compared to traditional multi-user BD detection algorithms and around 4 dB compared to combined BD-based multi-user MMSE and zero-forcing (ZF) detection algorithms.

Key words:  , multi-input multi-output (MIMO), orthogonal-frequency-division-multiplexing (OFDM), lattice reduction (LR), block diagonalization (BD), successive interference cancellation (SIC)

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