Alternating Hybrid Beamforming Design using GMD Decomposition for mmWave MIMO-OFDM Systems

Baghdad Hadji, A. Aïssa-El-Bey, L. Fergani, M. Djeddou
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Abstract

Since millimeter wave (mmWave) communications have wideband channels, mmWave signal corruptions increase due to radio-channel frequency selectivity. In this case, the combination of the orthogonal frequency division multiplexing (OFDM) with the mmWave MIMO system is envisioned as a candidate technique to address the degradation of communication. As hybrid analog/digital architecture offers potential energy and spectral efficiency for the mmWave MIMO device. Matrix factorization formulation with singular value decomposition (SVD) is the most used method for designing the hybrid precoder/combiner. However, using SVD decomposition in pre- coding/combining designing requires power allocation schemes due to the different signal-to-noise ratios (SNRs) of different sub- channels. To achieve a high wireless communications capacity, we propose in this work, a manifold optimization-based alternating minimization algorithm using the geometric mean decomposition (GMD) (called MO-AltMin-GMD) to derive unconstrained optimal precoders and combiners from the channel state information (CSI). The principal objective is that the proposed hybrid design avoids any allocation schemes to maintain the hybrid architecture complexity low. According to the obtained numecal results, the proposed hybrid design provides high results compared to existing methods in terms of spectral efficiency.
基于GMD分解的毫米波MIMO-OFDM系统交变混合波束形成设计
由于毫米波(mmWave)通信具有宽带信道,由于无线电信道频率选择性,毫米波信号损坏增加。在这种情况下,正交频分复用(OFDM)与毫米波MIMO系统的组合被设想为解决通信退化的候选技术。由于模拟/数字混合架构为毫米波MIMO设备提供了潜在的能量和频谱效率。基于奇异值分解(SVD)的矩阵分解公式是设计混合预编码器/组合器最常用的方法。然而,由于不同子信道的信噪比不同,在预编码/组合设计中使用奇异值分解需要功率分配方案。为了实现高无线通信容量,我们在这项工作中提出了一种基于流形优化的交替最小化算法,该算法使用几何平均分解(GMD)(称为MO-AltMin-GMD)从信道状态信息(CSI)中导出无约束的最优预编码器和组合器。提出的混合设计的主要目标是避免任何分配方案,以保持混合体系结构的低复杂度。根据得到的数值结果,与现有方法相比,所提出的混合设计在频谱效率方面具有较高的结果。
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