一种加权均方误差最小化的鲁棒性干扰对齐算法

李宁; 王思文; 翟立君; 刘允

doi:10.11999/JEIT150648

一种加权均方误差最小化的鲁棒性干扰对齐算法

doi: 10.11999/JEIT150648

基金项目:

国家863计划项目(2015AA01A705)，中电五十四所发展基金(X1228156)

计量
- 文章访问数: 2110
- HTML全文浏览量: 344
- PDF下载量: 419
- 被引次数: 0
出版历程
- 收稿日期: 2015-06-01
- 修回日期: 2015-11-10
- 刊出日期: 2016-03-19

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

Funds:

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

摘要

摘要: 线性干扰对齐的一个常见优化目标是总传输速率最大化，但因为和速率函数的非凸特性而难以直接求解。加权均方误差最小化算法借助均方误差与和速率之间的等价关系解决了这一问题。这一方法需要获得准确的信道状态信息，在实际应用中，通道估计误差的存在会导致算法性能的下降。该文提出一种改进算法，在干扰对齐预编码矩阵与接收矩阵的优化求解过程中将通道估计误差的统计特性考虑在内。仿真结果表明，相比以往的加权均方误差最小化算法，该文算法对信道估计误差具有较高的鲁棒性，可以有效提高总的传输速率。
- 干扰对齐 /
- MIMO /
- 预编码 /
- 通道估计误差
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

HTML全文

参考文献(17)

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.

施引文献

资源附件(0)

访问统计