MOGATE: Multi-Order Greedy Method-Aided Tree Search Receiver for Polar-Coded MIMO Systems

The upcoming 6G necessitates more stringent performance requirements than those in 5G. Polar-coded MIMO systems, benefiting from polar codes’ capacity-achieving properties, offer high-reliability potential. To fulfill these stringent reliability requirements, tree search receivers demonstrated satisfactory error rates. However, this enhanced performance raises complexity, hindering latency and energy efficiency goals. Identifying metric calculation and path sorting as the main contributors to complexity, this paper aims to reduce it without impacting performance. The former can be reduced by fine-tuning the list sizes, and the latter by omitting sorting in specific layers – a new insight. This paper delineates the relationship between parameters and complexities, and then formulates these relationships into integer programming (IP), highlighting their intrinsic link. To address these problems, we present a multi-order greedy method-based solver and propose a multi-order greedy method-aided tree search (MOGATE) receiver. Using multi-order greedy techniques reduces the complexity of solving problems by 36% compared to genetic algorithms. The effectiveness of the MOGATE has been proven in both separated detection and decoding (SDD) and joint detection and decoding (JDD) scenarios. Compared to its genetic counterparts, MOGATE achieves a notable reduction in complexity – up to 33% less in metric calculation and 10% less in path sorting – without compromising on error rate.