A Robust Interference Alignment Algorithm Based on Weighted Mean Square Error Minimization

LI Ning; WANG Siwen; ZHAI Lijun; LIU Yun

doi:10.11999/JEIT150648

Volume 38 Issue 3

Mar. 2016

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(3): 643-648

LI Ning, WANG Siwen, ZHAI Lijun, LIU Yun. A Robust Interference Alignment Algorithm Based on Weighted Mean Square Error Minimization[J]. Journal of Electronics & Information Technology, 2016, 38(3): 643-648. doi: 10.11999/JEIT150648

Citation:

LI Ning, WANG Siwen, ZHAI Lijun, LIU Yun. A Robust Interference Alignment Algorithm Based on Weighted Mean Square Error Minimization[J]. Journal of Electronics & Information Technology, 2016, 38(3): 643-648. doi: 10.11999/JEIT150648

Citation:

PDF( 877 KB)

A Robust Interference Alignment Algorithm Based on Weighted Mean Square Error Minimization

doi: 10.11999/JEIT150648

Funds:

The National 863 Program of China (2015AA01A705), The Development Fundation of CETC 54 (X1228156)

Received Date: 2015-06-01
Rev Recd Date: 2015-11-10
Publish Date: 2016-03-19

Abstract

Abstract

Sum rate maximization is often used as the target of linear Interference Alignment (IA). However, the sum rate function is non-convex and hard to be solved. This problem is solved according to the relationship of mean square error and sum rate which is known as the Weighted Minimum Mean Square Error (WMMSE). This method relies on the knowledge of channel state information. In real systems, the channel estimation error may cause significant descent to the sum rate performance. This paper proposes an improved algorithm, which considers the statistical character of channel estimation error. Simulation results show that the proposed algorithm is robust to channel estimation error and improves the sum-rate efficiently, compared with the usual WMMSE method.
- Interference Alignment (IA),
- MIMO,
- Pre-coding,
- Channel estimation error

FullText(HTML)

References(17)

References

CADAMBE V R and JAFAR S A. Interference alignment and degrees of freedom of the K-user interference channel[J]. IEEE Transactions on Information Theory, 2008, 54(8): 3425-3441. doi: 10.1109/TIT.2008.926344.

JAFAR S A. Interference alignmentA new look at signal dimensions in a communication network[J]. Foundations and Trends in Communications and Information Theory, 2011, 7(1): 1-134. doi: 10.1561/0100000047.

RATHEESH M and DAVID M J. System-level performance of interference alignment[J]. IEEE Transactions on Wireless Communications, 2015, 14(2): 1060-1070. doi: 10.1109/TWC. 2014.2363677.

GOMADAM K, CADAMBE V R, and JAFAR S A. Approaching the capacity of wireless networks through distributed interference alignment[C]. IEEE Global Telecommunications Conference, New Orleans, 2008: 1-6. doi: 10.1109/GLOCOM.2008.ECP.817.

GOMADAM K, CADAMBE V R, and JAFAR S A. A distributed numerical approach to interference alignment and applications to wireless interference networks[J]. IEEE Transactions on Information Theory, 2011, 57(6): 3309-3322. doi: 10.1109/TIT.2011.2142270.

SHRESTHA R, BAE I, and KIM J M. A leakage-based solution for interference alignment in MIMO interference channel networks[J]. KSII Transactions on Internet and Information Systems, 2014, 8(2): 424-442. doi: 10.3837/ tiis.2014.02.006.

王勤民, 张忠培, 常青美, 等. 干扰通道中一种权值可调的迭代算法[J]. 电子与信息学报, 2012, 34(12): 2851-2854. doi: 10.3724/ SP.J.1146.2012.00670.

WANG Qinmin, ZHANG Zhongpei, CHANG Qingmei, et al. An iterative algorithm with adjustable weight for inference channel[J]. Journal of Electronics Information Technology, 2012, 34(12): 2851-2854. doi: 10.3724/SP.J.1146.2012.00670.

章扬, 周正, 石磊, 等. 蜂窝网络下行链路单回馈干扰对齐算法研究[J]. 电子与信息学报, 2012, 34(12): 2817-2822. doi: 10.3724/SP.J.1146.2012.00583.

ZHANG Yang, ZHOU Zheng, SHI Lei, et al. Interference alignment with single feedback for downlink cellular networks [J]. Journal of Electronics Information Technology, 2012, 34(12): 2817-2822. doi: 10.3724/SP.J.1146.2012.00583.

PATCHARAMANEEPAKRON P and DOUFEXI A. Weighted sum capacity maximization using a modified leakage-based transmit filter design[J]. IEEE Transactions on Vehicular Technology, 2013, 62(3): 1177-1188. doi: 10.1109/TVT.2012.2230202.

PATCHARAMANEEPAKRON P, ARMOUR S, and DOUFEXI A. Coordinated beamforming schemes based on modified signal-to- leakage-plus-noise ratio precoding designs[J]. IET Communications, 2015, 9(4): 558-567. doi: 10.1049/iet-com. 2014.0256.

LIU H, DING Z G, FAN P Z, et al. Precoding design for interference suppression in multi-cell multi-user networks [J]. IET Communications, 2014, 8(9): 1534-1540. doi: 10. 1049/iet-com.2013.0757.

SHI Q, RAZAVIYAYN M, LUO Z Q, et al. An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel[J]. IEEE Transactions on Signal Processing, 2011, 59(9): 4331-4340. doi: 10.1109/ICASSP.2011.5946304.

CHRISTENSEN S S, AGARWAL R, CARVALHO E, et al. Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design[J]. IEEE Transactions on Wireless Communications, 2008, 7(12): 4792-4799. doi: 10.1109/T-WC.2008.070851.

KALEVA J, TOLLI A, and JUNTTI M. Weighted sum rate maximization for interfering broadcast channel via successive convex approximation[C]. IEEE Global Communications Conference, Anaheim, 2012: 3838-3843. doi: 10.1109/ GLOCOM.2012.6503715.

SUN F and DE CARVALHO E. Weighted MMSE beamforming design for weighted sum-rate maximization in coordinated multi-cell MIMO systems[C]. IEEE Vehicular Technology Conference, Quebec, 2012: 1-5. doi: 10.1109/ VTCFall.2012.6399004.

Relative Articles

Supplements(0)

Cited By

Proportional views