Iterative MIMO Detection Based on Dimen-sion Reduction Soft Demodulation

Abstract

Spatial multiplexing (SM) multi-input multi-output (MIMO) technology is con-sidered as core advanced communication technology to achieve more capacity. Although it guarantees more capacity, it gives huge burden on the receiver side to detect each stream which is transmitted from each transmit antenna. The main reason is inter-stream interference caused from streams of other antennas. In this thesis, to reduce inter-stream interference effects we propose dimension reduction soft demodulation (DRSD) with maximum a posteriori (MAP) for iterative detec-tion and decoding (IDD). The DRSD with MAP employs all ordering successive interference cancellation (AOSIC) with slicing MAP criterion for hard detection and also adding one more candidate for AOSIC to improve performance. DRSD can provide low complexity to separate hard streams and soft streams and slicing MAP criterion also provides similar performance to conventional IDD algorithms such as the soft-input soft-output single tree-search based on sphere decoding (SISO-STS-SD) which has better performance than others. Our proposed algorithm can reduce the complexity of iterative soft MIMO detection and give fixed complexity on the variety of SNR. Moreover, receiver performance of pro-posed scheme nearly approaches the performance of SISO-STS-SD. ⓒ 2013 DGIST