Low Complexity Soft Detection of High Order QAM with Prior Information

Recently, LTE Release 12 and IEEE 802.11ac adopted 256-quadrature amplitude modulation (QAM) as a tool to accommodate high demand of data throughput in wireless systems. Furthermore, currently developing IEEE 802.11ax considers 1024-QAM to further increase the Wi-Fi throughput. In this paper, we propose low complexity schemes in soft detection of high order QAM symbols in multiple input multiple output (MIMO) channels with or w/o prior information (from decoder output). We focus on 256-QAM with two transmitted layer MIMO with the understanding that the scheme can be generalized to higher order modulation and higher rank MIMO channels. We propose an initial candidate reduction (ICR) scheme with 128 initial candidates (refer to the scheme as ICR-128) to reduce the number of Euclidean distance (ED) calculations by half in comparison with soft maximum likelihood (ML) detection and as a result reduce the total hardware size by almost 50%. For initial candidate set selection we rely on linear minimum mean square error (MMSE) detection. The main advantage of the proposed scheme is in initial candidate set selection where we only need to detect I and Q sign of the target layer which simplifies MMSE detection. We further investigate the use of prior information in initial candidate set selection with MMSE soft interference cancellation (MMSE-SIC) which uses prior information in case of iterative detection and decoding (IDD) and/or hybrid automatic re- transmission request (HARQ) re-transmissions. To avoid computational complexity of MMSE-SIC, we propose a low complexity initial detection with prior information.