Operation-reduced enumeration technique for soft-input soft-output iterative sphere decoding

Using the Schnorr-Euchner (SE) enumeration for soft-input soft-output (SISO) sphere decoding is inefficient to implementation, because it calculates and sorts partial metrics of all constellation points exhaustively. In order to solve this problem, we use a low-complexity method which can be applied to the channel information and a-priori information enumerations for the SISO iterative K-best sphere decoding. In this paper, we present an algorithm that combines these two enumerations to reduce the operation complexity and do not need to sacrifice too much bit error rate (BER) performance.