基于交叉熵的1位DAC大规模MIMO预编码方案  

Precoding scheme for massive MIMO with one-bit DACs based on cross entropy

作　　者：张航宇 张锐[1] 廖方圆 李勇朝[1] ZHANG Hangyu;ZHANG Rui;LIAO Fangyuan;LI Yongzhao(State Key Laboratory of Integrated Service Networks,Xidian University,Xi’an 710071,China;China Electronic Technology Cyber Security Co.,Ltd.,Chengdu 610093,China)

机构地区：[1]西安电子科技大学综合业务网理论及关键技术国家重点实验室,陕西西安710071 [2]中国电子科技网络信息安全有限公司,四川成都610093

出　　处：《西安电子科技大学学报》2022年第6期1-8,共8页Journal of Xidian University

基　　金：国家自然科学基金(61901345,61901333,62001358);陕西省重点研发计划(2021 ZDLGY04-08)。

摘　　要：大规模多进多出系统具有空间分辨率高、频谱效率大、覆盖范围广的优势,其采用1位数模转换器可以显著地减少系统的功耗,降低硬件的复杂度及部署的成本。然而1位数模转换器会引入量化噪声,导致线性预编码后的符号严重失真,系统误比特率极度下降,且随着信噪比增加而过早地达到饱和。针对该问题,与线性预编码不同,非线性预编码方案将量化的影响考虑在内,直接设计量化后的符号,可大幅度地提升系统的误比特率性能。在该系统下,考虑到1位数模转换器量化后的符号属于有限集合且集合元素少,从组合优化的角度对1位量化下非线性预编码问题重新建模,并提出基于交叉熵算法的非线性预编码求解方案。这种方案通过最小化交叉熵自适应地更新每次迭代预编码向量中各元素的概率分布,可快速地收敛得到预编码向量,同时该方案易扩展至采用多位数模转换器的系统。仿真结果表明,所提方案在高信噪比下误比特率性能优于现有基于凸优化的方案,对信道估计错误具有鲁棒性,且适用于多位数模转换器的系统。Massive multiple-input multiple-output(MIMO) systems have the advantages of high spatial resolution, high spectral efficiency, and wide coverage.Utilizing one-bit digital-to-analog converters(DACs) can significantly reduce the power consumption, hardware complexity, and deployment costs in massive MIMO systems.However, due to the quantized noise introduced by the one-bit DACs, the symbols after linear precoding suffer from inevitable distortions.The system bit error rate(BER) performance will significantly fall and reach saturation prematurely with the increase of the signal-to-noise rate(SNR).Unlike linear precoding, nonlinear precoding considers the effect of one-bit quantization, and directly designs the quantized symbols, which can significantly improve the BER.Considering that the symbols after one-bit quantization belong to a finite set with a few elements, we modeled the nonlinear precoding problem from the perspective of combinatorial optimization, and a cross-entropy based algorithm was proposed.The proposed algorithm adaptively updates the probability distribution of each element in the precoding vector at each iteration by minimizing the cross entropy, and can quickly converge to obtain the precoding vector.Meanwhile, the proposed algorithm can be readily extended to the systems with multi-bit DACs.Simulation results show that the proposed algorithm outperforms existing algorithms based on convex optimization in terms of BER under a high SNR,and is robust to channel estimation errors.Besides, the applicability of the proposed scheme to multi-bit DACs is also verified by simulation.

关 键 词：大规模多进多出 1位数模转换器 预编码 交叉熵算法 

分 类 号：TN929.5[电子电信—通信与信息系统]