깊이 우선과 너비 우선 탐색 기법의 결합과 트리 분할을 이용한 다중 입출력 신호를 위한 새로운 최우도 복호 기법

Abstract

In this paper, we propose a novel ML decoding scheme based on the combination of depth- and breadth-first search methods on a partitioned tree for multiple input multiple output systems. The proposed scheme first partitions the searching tree into several stages, each of which is then searched by a depth- or breadth-first search method, possibly exploiting the advantages of both the depth- and breadth-first search methods in an organized way. Numerical results indicate that, when the depth- and breadth-first search algorithms are adopted appropriately, the proposed scheme exhibits substantially lower computational complexity than conventional ML decoders while maintaining the ML bit error performance.