Joint Linear Precoding and DFT Beamforming Design for Massive MIMO Satellite Communication

Autor: Vu Nguyen Ha, Zaid Abdullah, Geoffrey Eappen, Juan Carlos Merlano Duncan, Rakesh Palisetty, Jorge Luis Gonzalez Rios, Wallace Alves Martins, Hong-Fu Chou, Juan Andres Vasquez, Luis Manuel Garces-Socarras, Haythem Chaker, Symeon Chatzinotas
Rok vydání: 2022
Předmět:
DOI: 10.48550/arxiv.2211.08757
Popis: This paper jointly designs linear precoding (LP) and codebook-based beamforming implemented in a satellite with massive multiple-input multiple-output (mMIMO) antenna technology. The codebook of beamforming weights is built using the columns of the discrete Fourier transform (DFT) matrix, and the resulting joint design maximizes the achievable throughput under limited transmission power. The corresponding optimization problem is first formulated as a mixed integer non-linear programming (MINP). To adequately address this challenging problem, an efficient LP and DFT-based beamforming algorithm are developed by utilizing several optimization tools, such as the weighted minimum mean square error transformation, duality method, and Hungarian algorithm. In addition, a greedy algorithm is proposed for benchmarking. A complexity analysis of these solutions is provided along with a comprehensive set of Monte Carlo simulations demonstrating the efficiency of our proposed algorithms.
Comment: Globecom 2022
Databáze: OpenAIRE