GRAND-AM in uplink MIMO NOMA systems

Multiple input multiple output (MIMO) systems and nonorthogonal multiple access (NOMA) methods are both valuable techniques for modern and future communication systems. MIMO is commonly used in scenarios such as mobile communications and the Internet of Things in order to improve signal quality or increase channel capacity, while NOMA is important as its methods can be used to service the growing number of users. A combination of the two techniques should thus be investigated. We integrate MIMO methods such as the Alamouti space time block code (STBC) with Guessing Random Additive Noise Decoding Aided Macrosymbol (GRAND-AM), which was previously proposed for single input single output (SISO) systems. Originally, GRAND-AM handled the multiple access interference (MAI) using multiple access channel (MAC) codes assigned to each user, along with joint multiuser detection and decoding. We consider how using the Alamouti STBC as a replacement of the MAC codes performs with GRAND-AM. We show that GRAND-AM is able to outperform the multiuser Vertical-Bell Laboratories Layered Space-Time (V-BLAST) receiver by ∼ 2.5dB when used to handle two users using the Alamouti STBC. We show how GRAND-AM with Alamouti STBCs outperforms the V-BLAST receiver, even when there is a larger number of users in the MIMO NOMA system. We additionally investigate methods of reducing the complexity of GRAND-AM, as the MIMO NOMA problem is more complex than the SISO NOMA problem. We then show that the complexity reducing measures do not lead to large losses and can still outperform V-BLAST receivers, giving incentive to use GRAND-AM for MIMO NOMA systems.