Performance improvement of V-BLAST through an iterative approach
Cong Shen, Hairuo Zhuang, Lin Dai, Shidong Zhou, Yan Yao · 2004
This paper proposes an iterative V-BLAST detection algorithm that improves the error performance over error propagation. Traditional detection algorithm cannot alleviate error propagation because the decision feedbacks from low-diversity substreams are used to decode high-diversity substreams. In our algorithm, we iteratively suppress the interference towards low-diversity substreams by using decisions from high-diversity substreams, and the system performance is highly improved over the traditional one, which is demonstrated via simulation results. Besides, existing algorithms combating error propagation operate in high complexity, while the complexity of our algorithm is proportional to the loop times, providing a tradeoff between performance and complexity.