Impact of Max-Min Power Control, Channel Estimation and User Grouping Strategies on Uplink Massive MIMO-NOMA Systems

We analyze the uplink (UL) of a non-orthogonal multiple access (NOMA) based massive multiple input multiple output (MIMO) system and deduce new lower bounds on the achievable rate based on zero-forcing (ZF) decoding at the base station. Users are grouped to employ NOMA. In order to cancel the inter-group interference, the ZF decoder is designed as a function of channel estimates acquired based on two low overhead channel estimation schemes, namely, Scheme-I and Scheme-S. Under these estimation schemes, pilots are shared among users in a group while they are orthogonal across groups. User grouping and power allocation are two pivotal ways to regulate the performance of users in a NOMA system. Thus, to ensure uniform quality-of-service to all users, we obtain the max-min power control coefficients which maximize the minimum achievable rate. Furthermore, we investigate two different user grouping strategies, namely, non-scalable near-far grouping and scalable neighbor grouping, and study their impact on the UL max-min achievable rate. We benchmark against the performance obtained with the maximum ratio decoder. Extensive analysis and simulations show that in a substantial portion of the over-loaded regime and the entire under-loaded regime, ZF decoder designed using channel estimates acquired via Scheme-S with near-far grouping gives the highest max-min achievable rate among all the considered decoding and grouping strategies.