In terahertz (THz) massive multiple-input multiple-output (MIMO) systems, the combination of huge bandwidth and massive antennas results in severe beam split, thus making the conventional phase-shifter based hybrid precoding architecture ineffective. With the incorporation of true-time-delay (TTD) lines in the hardware implementation of the analog precoders, delay-phase precoding (DPP) emerges as a promising architecture to effectively overcome beam split. However, existing DPP approaches suffer from poor performance, high complexity, and weak robustness in practical THz channels. In this paper, we propose a novel DPP approach in wideband THz massive MIMO systems. First, the optimization problem is converted into a compressive sensing (CS) form, which can be solved by the extended spatially sparse precoding (SSP) algorithm. To compensate for beam split, frequency-dependent measurement matrices are introduced, which can be approximately realized by feasible phase and delay codebooks. Then, several efficient atom selection techniques are developed to further reduce the complexity of extended SSP. In simulation, the proposed DPP approach achieves superior performance, complexity, and robustness by using it alone or in combination with existing DPP approaches.
翻译:在Thahertz(Thz)大规模多投入多输出(MIMO)系统中,巨大的带宽和大型天天线的结合导致巨大的波束分化,从而使传统的分阶段交替者混合编码结构无效。随着将实时交替(TTD)线纳入模拟预编码器硬件的安装中,延迟预编码(DPP)作为有效克服光束分裂的一个有希望的结构出现。然而,现有的DPP方法由于实际的THz信道的性能不佳、高度复杂和强健而受到损害。在本文件中,我们提议在宽带Thz大型MIMO系统中采用新型的DPP方法。首先,优化问题被转换成压缩感测(CS)形式,可以通过扩展的空间稀疏预编码(SSP)算法加以解决。为了弥补分解,引入了依赖频率的测量矩阵,这可以通过可行的阶段和延迟代码库实现。随后,开发了几种高效的原子选择技术,以进一步降低扩展的SSP复杂性。在模拟中,仅采用强势的DPP方法,或者通过现有的组合实现高性性。