ACTA AERONAUTICAET ASTRONAUTICA SINICA >
A Near-optimal Lattice Reduction Aided Linear Parallel Detection Algorithm Based on MMSE
Received date: 2012-10-23
Revised date: 2013-01-21
Online published: 2013-03-01
Supported by
National Natural Science Foundation of China (60902054);China Postdoctoral Science Foundation (20090460114, 201003758);The Special Foundation Program for Taishan Mountain Scholars
Existing multiple-input multiple-output (MIMO) detection algorithms based on Lattice Reduction (LR) can effectively improve the bit error rate (BER) performance. However, these detection algorithms have a large signal to noise ratio (SNR) gap when compared with the optimal maximum likelihood (ML) algorithm. In order to solve this problem, a new Lattice Reduction aided detection algorithm based on channel partition is proposed in this paper. In this algorithm, the signals through the worse conditional sub-channels are first detected with an ML algorithm. After cancelling the impact of these signals, the remaining are detected in parallel with the optimized sub-channels using Lattice Reduction. The simulation results show that, under 16QAM (Quadrature Amplitude Modulation) and 64QAM, the BER performance of the proposed algorithm can achieve the optimal result for a 4×4 MIMO system and have less than 0.5 dB SNR gap as compared with the ML algorithm for a 6×6 MIMO system.
Key words： MIMO system; Lattice Reduction; minimum mean square error; linearity; parallel
RUI Guosheng , ZHANG Haibo , TIAN Wenbiao , DENG Bing , LI Tingjun . A Near-optimal Lattice Reduction Aided Linear Parallel Detection Algorithm Based on MMSE[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2013 , 34(8) : 1898 -1905 . DOI: 10.7527/S1000-6893.2013.0116
[1] Foschini G J, Golden G D, Valenzuela R A, et al. Simplified processing for high spectral efficiency wireless communication employing multi-element arrays. IEEE Journal on Selected Areas in Communications, 1999, 17(11): 1841-1852.
[2] Proakis J G, Salehi M. Digital communications. 5th ed. New York: McGraw-Hill, 2007.
[3] Won-Joon C, Negi R, Cioffi J M. Combined ML and DFE decoding for the V-BLAST system. Proceedings of IEEE International Conference on Communications. New Orleans, LA: IEEE, 2000: 1243-1248.
[4] Luo Z, Zhao M, Liu S, et al. Generalized parallel interference cancellation with near-optimal detection performance. IEEE Transactions on Signal Processing, 2008, 56(1): 304-312.
[5] Wubben D, Bohnke R, Kuhn V, et al. MMSE-based lattice-reduction for near-ML detection of MIMO systems. ITG Workshop on Smart Antennas. Germany: IEEE, 2004: 106-113.
[6] Ma X, Zhang W. Performance analysis for MIMO systems with lattice-reduction. IEEE Transaction Communcation, 2008, 56(2): 309-318.
[7] Wübben D, Seethaler D, Jaldén J, et al. Lattice reduction. IEEE Signal Processing Magazine, 2011, 28(3): 70-91.
[8] Taherzadeh M, Mobasher A, Khandani A K. LLL reduction achieves the receive diversity in MIMO decoding. IEEE Transactions on Information Theory, 2007, 53(12): 4801-4805.
[9] Jaehyun P, Joohwan C. Improved lattice reduction-aided MIMO successive interference cancellation under imperfect channel estimation. IEEE Transactions on Signal Processing, 2012, 60(6): 3346-3351.
[10] Zhang W, Qiao S, Wei Y. A diagonal lattice reduction algorithm for MIMO detection. IEEE Signal Processing Letters, 2012, 5(19): 311-314.
[11] Bai L, Chen C, Choi J, et al. Greedy user selection using a lattice reduction updating method for multiuser MIMO systems. IEEE Transactions on Vehicular Technology, 2011, 60(1): 136-147.
[12] Chen C, Sheen W. A new lattice reduction algorithm for LR-aided MIMO linear detection. IEEE Transactions on Wireless Communications, 2011, 10(8): 2417-2422.
[13] Liu S, Ling C, Stehlé D. Decoding by sampling-a randomized lattice algorithm for bounded distance decoding. IEEE Transactions on Information Theory, 2011, 57(9): 5933-5945.
[14] Ling C. On the proximity factors of lattice reduction-aided decoding. IEEE Transactions on Signal Processing, 2011, 59(6): 2795-2808.
[15] Hung G, Ling C, Ho M. Complex lattice reduction algorithm for low-complexity full-diversity MIMO detection. IEEE Transactions on Signal Processing, 2009, 57(7): 2701-2710.
[16] Sun Y H, Wang H, Zhang Y H. MIMO detection algorithm of complex lattice reduction. Journal of University of Electronic Science and Technology of China, 2010, 39(5): 670-675. (in Chinese) 孙艳华, 王浩, 张延华. 复数域格缩减的MIMO检测算法研究. 电子科技大学学报, 2010, 39(5): 670-675.
[17] Bremner M R. Lattice basis reduction. New York: CRC Press, 2011: 5-6.
[18] Huang M, Zhou S D, Wang J. Analysis of Tomlinson-Harashima precoding in multiuser MIMO systems with imperfect channel state information. IEEE Transactions on Vehicular Technology, 2008, 57(5): 2856-2867.
/
| 〈 |
|
〉 |
CJA