2017/05/31 by Meysam Sadeghi, Emil Björnson, Sadeghi, Meysam +7 · 2 citations
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Network Optimization #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Information Theory (cs.IT)
paper · pdf · doi:10.48550/arxiv.1705.10968
openalex publication_date 2017/05/31 · openalex created_date 2022/10/06 · openalex updated_date 2026/07/28
This paper considers the downlink precoding for physical layer multicasting\nin massive multiple-input-multiple-output (MIMO) systems. We study the max-min\nfairness (MMF) problem, where channel state information (CSI) at the\ntransmitter is used to design precoding vectors that maximize the minimum\nspectral efficiency (SE) of the system, given fixed power budgets for uplink\ntraining and downlink transmission. Our system model accounts for channel\nestimation, pilot contamination, arbitrary pathlosses, and multi-group\nmulticasting. We consider six scenarios with different transmission\ntechnologies (unicast and multicast), different pilot assignment strategies\n(dedicated or shared pilot assignments), and different precoding schemes\n(maximum ratio transmission and zero forcing), and derive achievable spectral\nefficiencies for all possible combinations. Then we solve the MMF problem for\neach of these scenarios and for any given pilot length we find the SE\nmaximizing uplink pilot and downlink data transmission policies, all in\nclosed-forms. We use these results to draw a general guideline for massive MIMO\nmulticasting design, where for a given number of base station antennas, number\nof users, and coherence interval length, we determine the multicasting scheme\nthat shall be used.\n