An Adaptive Reduced Complexity K-Best Decoding Algorithm with Early Termination

This paper presents a K-Best decoding algorithm that requires a much smaller K while preserving advantages of the sphere decoding algorithm such as branch pruning and an adaptively updated pruning threshold. The proposed approach results in examining a much smaller set of modulation points with a significantly reduced complexity. Simulations are presented that quantify the BER performance and complexity in terms of the number of visited nodes. The variability in the required operations (hence run-time) due to branch pruning is studied and compared with the sphere decoding algorithm.