基于信道相关性的非线性预编码卫星通信系统用户分组算法

Ke Wang, Baorui Feng, Jingui Zhao, Wenliang Lin, Zhongliang Deng, Dongdong Wang, Yi Cen, Genan Wu
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引用次数: 0

摘要

低地球轨道(LEO)多波束卫星将广泛应用于下一代卫星通信系统,其波束间干扰将不可避免地限制整个系统的性能。非线性预编码(如汤姆林森-原岛预编码(THP)算法)与线性预编码相比具有较小的噪声放大效应,已被证明是解决这一问题的可行技术。然而,不同用户信道的相似性(定义为信道相关性)会降低 THP 算法的性能。本文定性分析了低地轨道卫星在特定覆盖区域内全过程的波束间干扰,以及应用 THP 时信道相关性对接收器信噪比(SNR)的影响。在分析信道相关性的基础上,提出了一种用户分组算法,该算法可以减少每个预编码组中信道相关性高的用户数量,从而提高 THP 的性能。此外,我们的算法是在同频部署和正交频分复用(OFDM)的前提下设计的,与现有的地球静止轨道卫星广播系统研究相比,在波束间干扰严重的情况下,我们的算法可以获得更多用户。仿真结果表明,与现有研究相比,所提出的用户分组算法在高信噪比条件下具有更高的信道容量和更好的误码率(BER)性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Channel correlation based user grouping algorithm for nonlinear precoding satellite communication system
Low Earth Orbit (LEO) multibeam satellites will be widely used in the next generation of satellite communication systems, whose inter-beam interference will inevitably limit the performance of the whole system. Nonlinear precoding such as Tomlinson-Harashima precoding (THP) algorithm has been proved to be a promising technology to solve this problem, which has smaller noise amplification effect compared with linear precoding. However, the similarity of different user channels (defined as channel correlation) will degrade the performance of THP algorithm. In this paper, we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area, and the impact of channel correlation on Signal-to-Noise Ratio (SNR) of receivers when THP is applied. One user grouping algorithm is proposed based on the analysis of channel correlation, which could decrease the number of users with high channel correlation in each precoding group, thus improve the performance of THP. Furthermore, our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing (OFDM), which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems. Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER) performance in high SNR conditions relative to existing works.
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