Provided by: Computer Science Journals
Date Added: Nov 2015
In this paper, the authors present an iterative soft decision based complex Multiple Input Multiple Output (MIMO) decoding algorithm, which reduces the complexity of Maximum Likelihood (ML) detector. They develop a novel iterative complex K-best decoder exploiting the techniques of lattice reduction for 8Ã?8 MIMO. Besides list size, a new adjustable variable has been introduced in order to control the on-demand child expansion. Following this method, they obtain 6.9 to 8.0dB improvement over real domain K-best decoder and 1.4 to 2.5dB better performance compared to iterative conventional complex decoder for 4th iteration and 64-QAM modulation scheme.