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arXiv 2401.00166cs.ITeess.SPmath.IT
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块级MU-MISO干扰利用预编码:最优结构与显式对偶性

Block-Level MU-MISO Interference Exploitation Precoding: Optimal Structure and Explicit Duality

Junwen Yang, Ang Li, Xuewen Liao, Christos Masouros, A. L. Swindlehurst

AI总结:

本文针对MU-MISO下行链路提出块级干扰利用预编码,通过联合优化块内预编码器降低更新频率,并利用最优结构与显式对偶性分解问题,在保证性能的同时显著降低复杂度。

摘要:

本文研究了多用户多输入单输出(MU-MISO)下行链路系统中的块级干扰利用(IE)预编码。为克服符号级IE预编码需要频繁更新预编码矩阵的问题,我们提出在一个传输块内联合优化所有预编码器或发射信号。由此得到的预编码器每个块只需更新一次,虽然不要求在所有符号时隙上恒定,我们将该技术称为块级时隙可变IE预编码。通过仔细考察块级功率最小化(PM)与信干噪比(SINR)均衡(SB)问题中固有的最优结构和显式对偶性,我们发现联合优化可以分解为变量规模更小的子问题。进一步地,我们通过在时隙可变IE预编码上添加结构约束以在整个块内保持恒定预编码器,提出了块级时隙不变IE预编码。我们还提出了一种新的用于IE的线性预编码器,并证明了当符号时隙数不超过用户数时,所提出的时隙可变与时隙不变IE预编码具有相同的解。数值仿真表明,与基准方案相比,所提出的预编码器在不牺牲性能的情况下显著降低了复杂度。

英文摘要:

This paper investigates block-level interference exploitation (IE) precoding for multi-user multiple-input single-output (MU-MISO) downlink systems. To overcome the need for symbol-level IE precoding to frequently update the precoding matrix, we propose to jointly optimize all the precoders or transmit signals within a transmission block. The resultant precoders only need to be updated once per block, and while not necessarily constant over all the symbol slots, we refer to the technique as block-level slot-variant IE precoding. Through a careful examination of the optimal structure and the explicit duality inherent in block-level power minimization (PM) and signal-to-interference-plus-noise ratio (SINR) balancing (SB) problems, we discover that the joint optimization can be decomposed into subproblems with smaller variable sizes. As a step further, we propose block-level slot-invariant IE precoding by adding a structural constraint on the slot-variant IE precoding to maintain a constant precoder throughout the block. A novel linear precoder for IE is further presented, and we prove that the proposed slot-variant and slot-invariant IE precoding share an identical solution when the number of symbol slots does not exceed the number of users. Numerical simulations demonstrate that the proposed precoders achieve a significant complexity reduction compared against benchmark schemes, without sacrificing performance.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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