Bit-Metric Decoding Rate in Multi-User MIMO Systems: Applications
This work addresses performance optimization in wireless communication systems, specifically for multi-user MIMO, but is incremental as it builds on prior concepts from a two-part series.
The paper tackles link-adaptation and physical layer abstraction for multi-user MIMO systems with non-linear receivers by proposing novel algorithms based on a bit-metric decoding rate metric, with extensive simulations demonstrating their efficacy.
This is the second part of a two-part paper that focuses on link-adaptation (LA) and physical layer (PHY) abstraction for multi-user MIMO (MU-MIMO) systems with non-linear receivers. The first part proposes a new metric, called bit-metric decoding rate (BMDR) for a detector, as being the equivalent of post-equalization signal-to-interference-noise ratio (SINR) for non-linear receivers. Since this BMDR does not have a closed form expression, a machine-learning based approach to estimate it effectively is presented. In this part, the concepts developed in the first part are utilized to develop novel algorithms for LA, dynamic detector selection from a list of available detectors, and PHY abstraction in MU-MIMO systems with arbitrary receivers. Extensive simulation results that substantiate the efficacy of the proposed algorithms are presented.