Compressão de CSI para MIMO distribuído com processamento centralizado

Abstract

In Distributed-MIMO (D-MIMO), a large number of distributed Antenna Points (APs) are coordinated by a Central Unit (CU) to serve a limited number of users with the same time/frequency resources, which brings improvements in spectral efficiency. The success of D-MIMO depends on precoding and power allocation, which can be performed completely centrally on the CU or distributed across APs. The centralized approach has greater spectral efficiency than the distributed implementation, but requires a significant spike in fronthaul traffic due to the exchange of Channel State Information (CSI) between APs and CU. In this work, CSI compression schemes are proposed to enable practical and centralized implementation of D-MIMO. It is shown that depending on the compression configuration, the spectral efficiency can be as good as in the case without compression. Furthermore, this work explores the implementation of multiple-input multiple-output (MIMO) within the framework of the New Radio (NR) architecture. The study evaluates a distributed MIMO deployment using NR signals with compression and evaluates its performance compared to the uncompressed scenario. Through simulations using the NR physical layer, the results also show that the spectral efficiency can be as good as in the uncompressed case depending on the compression configuration. Finally, the simulations with NR signals highlight important practical aspects and the feasibility of implementing D-MIMO in the 5G architecture and beyond 5G.