In this letter, we propose lattice-reduction (LR)-aided partial marginalization (PM) for soft output multiple-input multiple-output (MIMO) detection. PM has the advantages of a fully predictable runtime and convenience in parallelization while offering a well-defined tradeoff between the performance and the computational complexity. However, the computational complexity of PM to achieve a high level of performance is considerably high. In order to reduce the complexity of PM, the proposed scheme performs low-complexity LR-aided marginalization instead of exact marginalization (EM) to avoid the exhaustive approach of the EM, which mainly increases the overall complexity. The experimental results demonstrate that the computational complexity of the proposed scheme is considerably lower with negligible performance degradation compared to conventional PM.
Bibliographical noteFunding Information:
This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (no. NRF-2015R1A2A2A01004883), and in part by the System LSI Division on Samsung Electronics Co., LTD.
© 2016 IEEE.
All Science Journal Classification (ASJC) codes
- Modelling and Simulation
- Computer Science Applications
- Electrical and Electronic Engineering