可适应的混合束形与子集优化算法,用于多用户大规模的MIMO系统
Ziyang Huang1, Longcheng Yang2, Weiqiang Tan1
1School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou 510006, China.
Sensors (Basel, Switzerland)
|July 13, 2024
概括
本研究介绍了一种子集优化算法-混合波束成形 (SOA-HBF),以减少大规模MIMO系统的干扰. 新方法提高了系统容量和性能,即使在使用智能反射表面的障碍物上也是如此.
科学领域:
- 无线通信无线通信
- 信号处理 信号处理
- 信息理论 信息理论
背景情况:
- 大规模MIMO系统中的混合光束成型 (HBF) 提供了诸如增加总量率和减少功耗等好处.
- 设计有效的HBF是复杂的,用户间的干扰会降低系统性能.
研究的目的:
- 开发一种新的混合光束成形方案,即子集优化算法-混合光束成形 (SOA-HBF),以减轻用户间的干扰.
- 通过优化混合光束变压器来最大限度地提高系统容量.
- 在有障碍和没有障碍的场景中评估方案的有效性,使用智能反射表面 (IRS).
主要方法:
- 该子集优化算法 (SOA) 适应将用户集划分为子集,以优化混合束形.
- 开发了一种包含智能反射表面 (IRS) 的系统模型,以克服通信阻塞.
- 通过对SOA-HBF与基线方法进行比较的模拟来评估性能.
主要成果:
- 拟议的SOA-HBF方案显著减少了用户间的干扰.
- 与基线方法相比,模拟结果显示性能改善幅度从8.1%到59.1%.
- 该方案在毫米波大规模MIMO和IRS辅助的全连接混合波束成形系统中都被证明有效.
结论:
- SOA-HBF是一种有效的策略,用于在大型MIMO系统中增强混合光束成形.
- 整合IRS进一步提高了通信效率,特别是在受阻的环境中.
- 开发的方案为在先进的无线网络中最大限度地提高系统容量和性能提供了强大的解决方案.
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