基于最大比合并的低复杂度OTFS系统信号检测算法OA
A low-complexity signal detection algorithm for OTFS systems based on maximum ratio combining
在高速多径环境中,频率色散现象严重损害了正交频分复用(OFDM)系统子载波的正交性,而正交时频空(OTFS)调制因其良好的抗多径和多普勒干扰能力而具有广阔的应用前景.为降低OTFS系统中的信号检测复杂度,提出了一种基于最大比合并的低复杂度信号检测算法.该算法首先借助零填充技术以及信道矩阵的循环结构特性来降低复杂度;随后通过最大比合并算法对接收的多径信号分量进行提取和相干组合,从而提高组合信号的信噪比;同时运用广义最小残差算法对信道增益矩阵的求逆运算进行简化,进一步降低算法的复杂度.对不同算法在复杂度、误码率和收敛速度方面进行对比分析,表明所提出的算法在保证误码率性能的前提下,实现了更快的收敛速度和更低的计算复杂度.
In high-speed multipath environments,the orthogonality of orthogonal frequency division mul-tiplexing(OFDM)subcarriers is severely compromised by frequency dispersion.In contrast,orthogonal time frequency space(OTFS)modulation shows promising potential thanks to its excellent resistance to multipath and Doppler interferences.To reduce the signal detection complexity in OTFS systems,this pa-per proposes a low complexity signal detection algorithm based on maximal ratio combining.First,the al-gorithm reduces complexity by employing a zero-padding technique and exploiting the circulant structure property of channel matrices.Second,it employs the maximal ratio combining algorithm to extract and co-herently combine the received multipath signal components,thereby improving the signal-to-noise ratio of the combined signal.Third,the generalized minimal residual algorithm is utilized to simplify the inver-sion operation of the channel gain matrix,further lowering the algorithm's complexity.The comparative analysis incorporating computational complexity,bit error rate,and convergence speed of different algo-rithms demonstrates that the proposed algorithm achieves a faster convergence speed and lower computa-tional complexity while maintaining a competitive bit error rate performance.
周围;张艺;黄华;杨瑜;向波
重庆邮电大学 通信与信息工程学院,重庆 400065||重庆邮电大学 移动通信技术重庆市重点实验室,重庆 400065重庆邮电大学 通信与信息工程学院,重庆 400065||重庆邮电大学 移动通信技术重庆市重点实验室,重庆 400065重庆邮电大学 通信与信息工程学院,重庆 400065||重庆邮电大学 移动通信技术重庆市重点实验室,重庆 400065重庆邮电大学 移动通信技术重庆市重点实验室,重庆 400065重庆邮电大学 移动通信技术重庆市重点实验室,重庆 400065
信息技术与安全科学
OTFS最大比合并广义最小残差信号检测
orthogonal time frequency space(OTFS)maximal ratio combininggeneralized minimal re-sidualsignal detection
《南京邮电大学学报(自然科学版)》 2026 (2)
11-18,8
国家自然科学基金(61701062)和重庆市基础与前沿研究计划(cstc2019jcyj-msxmX0079)资助项目
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