Abstract
In this letter, we propose a new groupwise receive combiner design for multiple-input multiple-output spatial multiplexing systems. The conventional group detection (GD) suffers from a considerable performance loss since the noise components are not taken into account. The output signal-to-interference- plus-noise ratio (SINR) is defined in each subgroup in order to consider both the desired signal and noise statistics. Adopting the real-valued representation, we provide an optimal receive combiner which maximizes the SINR with a general group size. The simulation results show that the proposed scheme achieves a large performance gain over the conventional GD in coded systems. Also, when combining with near-optimal detection algorithms such as sphere decoder, the proposed GD scheme offers a comparable performance with significant reduced complexity.
Original language | English |
---|---|
Article number | 5577800 |
Pages (from-to) | 2511-2515 |
Number of pages | 5 |
Journal | IEEE Transactions on Communications |
Volume | 58 |
Issue number | 9 |
DOIs | |
Publication status | Published - 2010 Sept |
Bibliographical note
Funding Information:Paper approved by D. J. Love, the Editor for MIMO and Adaptive Techniques of the IEEE Communications Society. Manuscript received August 4, 2009; revised January 14, 2010. S.-H. Moon and I. Lee are with the School of Electrical Engineering, Korea University, Seoul, Korea (e-mail: {shmoon, inkyu}@korea.ac.kr). J. Jeong is with Samsung Electronics, Suwon, Korea (e-mail: [email protected]). H. Lee is with the Future IT Research Center, Samsung Advanced Institute of Technology (SAIT), Korea (e-mail: [email protected]). This paper was presented in part at the Vehicular Technology Conference (VTC) in Calgary, Canada, September 2008. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2010-0017909). Digital Object Identifier 10.1109/TCOMM.2010.09.090135
Keywords
- Multiple-input multiple-output (MIMO)
- group detection
- maximum-likelihood (ML) detection
- spatial multiplexing
ASJC Scopus subject areas
- Electrical and Electronic Engineering