In this paper,we present a novel and robust nonlinear precoding(NLP)design and detection structure specifically tailored for multiple-input multipleoutput space division multiple access(MIMO-SDMA)systems toward 6G wir...In this paper,we present a novel and robust nonlinear precoding(NLP)design and detection structure specifically tailored for multiple-input multipleoutput space division multiple access(MIMO-SDMA)systems toward 6G wireless.Our approach aims to effectively mitigate the impact of imperfect channel estimation by leveraging the channel fluctuation mean square error(MSE)for reconstructing a highly accurate precoding matrix at the transmitter.Furthermore,we introduce a simplified receiver structure that eliminates the need for equalization,resulting in reduced interference and notable enhancements in overall system performance.We conduct both computer simulations and experimental tests to validate the efficacy of our proposed approach.The results reveals that the proposed NLP scheme offers significant performance improvements,making it particularly well-suited for the forthcoming 6G wireless.展开更多
大规模多入多出(Massive MIMO)系统中,随着天线数的增加,线性预编码算法的性能逐渐趋于最优,选择合适的线性预编码对系统性能具有重要的意义。针对发射端信道状态信息(Channel State Information at Transmitter,CSIT)不完美的Massive M...大规模多入多出(Massive MIMO)系统中,随着天线数的增加,线性预编码算法的性能逐渐趋于最优,选择合适的线性预编码对系统性能具有重要的意义。针对发射端信道状态信息(Channel State Information at Transmitter,CSIT)不完美的Massive MIMO系统,推导出了迫零(Zero-Forcing,ZF)和最大比传输(Maximum Ratio Transmission,MRT)这两种常见预编码方案在向量归一化方式下的下行可达和速率下界,并给出了证明。随后对两种下界进行了分析,提出了一个关于系统用户数的阈值,当系统用户数和阈值的大小关系不同时,两种预编码性能的优劣关系也不相同。根据分析结果,文章进一步提出了一种以系统中用户数为参量的预编码选择策略,可以保证不论用户数如何变化,系统都能选择出更优的那一个预编码算法来对信号进行预处理。分析的有效性和方案的可靠性通过仿真得到了验证。展开更多
基金supported in part by National Key R&D Program of China(2020YFB1807203)National Science Foundation of China under Grant number 62071111+2 种基金the Fundamental Research Funds for the Central Universities under Grant 2242022k60006Natural Science Foundation of Sichuan Province under Grant number 2022NSFSC0487the National Key Laboratory of Wireless Communications Foundation under Grant IFN20230104。
文摘In this paper,we present a novel and robust nonlinear precoding(NLP)design and detection structure specifically tailored for multiple-input multipleoutput space division multiple access(MIMO-SDMA)systems toward 6G wireless.Our approach aims to effectively mitigate the impact of imperfect channel estimation by leveraging the channel fluctuation mean square error(MSE)for reconstructing a highly accurate precoding matrix at the transmitter.Furthermore,we introduce a simplified receiver structure that eliminates the need for equalization,resulting in reduced interference and notable enhancements in overall system performance.We conduct both computer simulations and experimental tests to validate the efficacy of our proposed approach.The results reveals that the proposed NLP scheme offers significant performance improvements,making it particularly well-suited for the forthcoming 6G wireless.
文摘大规模多入多出(Massive MIMO)系统中,随着天线数的增加,线性预编码算法的性能逐渐趋于最优,选择合适的线性预编码对系统性能具有重要的意义。针对发射端信道状态信息(Channel State Information at Transmitter,CSIT)不完美的Massive MIMO系统,推导出了迫零(Zero-Forcing,ZF)和最大比传输(Maximum Ratio Transmission,MRT)这两种常见预编码方案在向量归一化方式下的下行可达和速率下界,并给出了证明。随后对两种下界进行了分析,提出了一个关于系统用户数的阈值,当系统用户数和阈值的大小关系不同时,两种预编码性能的优劣关系也不相同。根据分析结果,文章进一步提出了一种以系统中用户数为参量的预编码选择策略,可以保证不论用户数如何变化,系统都能选择出更优的那一个预编码算法来对信号进行预处理。分析的有效性和方案的可靠性通过仿真得到了验证。
