Spectrum sharing for multi-user massive MIMO networks

Abstract

In this dissertation, we propose a creative approach to advance 5G network technologies by investigating the impact of employing an underlay spectrum sharing (USS) scheme on the performance of two massive multi-input-multi-output (MIMO) networks. We explore an USS approach where a multi-user massive MIMO network (primary network (PN)), i.e., the owner of the frequency spectrum, allows another multi-user massive MIMO network, the secondary network (SN), to utilize its allocated spectrum to serve secondary users (SUs). Within this context, we devise joint power allocation and beamforming techniques at the SN for both conventional time-division duplexing (C-TDD) and reverse time-division duplexing (R-TDD) protocols. In the C-TDD approach, both the PN and SN operate concurrently in either the uplink (UL) or downlink (DL) modes. In the R-TDD protocol, the PN and SN do not simultaneously operate in the UL or DL modes. It is worth noting that, during the training phase of the PN (learning phase of the SN), all the SN’s nodes remain silent and listen to the PN to acquire as much information as possible about the PN. The optimization problems aim to maximize the SN’s achievable sum-rate in both UL and DL, while guaranteeing the minimum acceptable individual rate for each primary user (PU) and satisfying the SN’s power constraints. Effective solutions are proposed for both the C-TDD and R-TDD protocols, including novel methods to mitigate interference caused by the SN’s nodes to the PN’s nodes during UL and DL phases. We assume that the PN parameters are set by the PN independently, without considering the presence of the SN, to minimize the SN’s potential impact on the PN’s frame structure and system design. Our simulation results demonstrate that for a moderate-scale SN coverage area, both C-TDD and R-TDD approaches reveal almost comparable performance. Additionally, changes in the SN’s settings have a small effect on the total sum-rate of the PN when our proposed method is employed. Finally, for all tested values of the number of antennas at the secondary base stations (SBS), the R-TDD approach outperforms the C-TDD approach when the SN coverage area is large, and vice versa.