Non-Linear Base-Station Processing Within a 3GPP Compliant Framework

Abstract

MIMO mobile systems, with a large number of antennas at the base-station side, enable the concurrent transmission of multiple, spatially separated information streams, and therefore, enable improved network throughput and connectivity both in uplink and downlink transmissions. Traditionally, such MIMO transmissions adopt linear base-station processing, that translates the MIMO channel into several single-antenna channels. While such approaches are relatively easy to implement, they can leave on the table a significant amount of unexploited MIMO capacity and connectivity capabilities. Recently-proposed non-linear base-station processing methods claim this unexplored capacity and promise substantially increased network throughput and connectivity capabilities. Still, to the best of the authors’ knowledge, non-linear base-station processing methods not only have not yet been adopted by actual systems, but have not even been evaluated in a standard-compliant framework, involving all the necessary algorithmic modules required by a practical system. In this work, for the first time, we incorporate and evaluate non-linear base-station processing in a 3GPP standard environment. We outline the required research platform modifications and we verify that significant throughput gains can be achieved, both in indoor and outdoor settings, even when the number of base-station antennas is much larger than the number of transmitted information streams. Then, we identify missing algorithmic components that need to be developed to make non-linear base-station practical, and discuss future research directions towards potentially transformative next-generation mobile systems and base-stations (i.e., 6G) that explore currently unexploited non-linear processing gains.

Keywords

• Multi-user (MU)-MIMO
• signal detection
• precoding
• non-linear signal processing