一种平衡策略下网络多输入多输出系统的预编码方案

计算机应用 ›› 2012, Vol. 32 ›› Issue (05): 1224-1227.

一种平衡策略下网络多输入多输出系统的预编码方案

张红¹,郝东来²

1. 陕西职业技术学院计算机科学系，西安710100
2. 西安通信学院通信指挥系，西安710106

收稿日期:2011-11-04 修回日期:2011-12-27 发布日期:2012-05-01 出版日期:2012-05-01
通讯作者: 张红
作者简介:张红（1977-），女，陕西西安人，讲师，硕士，主要研究方向：计算机网络通信；郝东来（1974-），男，陕西咸阳人，讲师，博士，主要研究方向：无线通信。

Equilibrium precoding scheme for network multiple-input multiple-output system

ZHANG Hong¹,HAO Dong-lai²

1. Department of Computer Science, Shaanxi Vocational Technical College， Xi'an Shaanxi 710100， China
2. Department of Communication Command, Xi'an Communication Institute, Xi'an Shaanxi 710106, China

Received:2011-11-04 Revised:2011-12-27 Online:2012-05-01 Published:2012-05-01
Contact: ZHANG Hong

摘要/Abstract

摘要： 针对在多小区多输入多输出（MIMO）系统预处理中，最大化目标用户信干噪比与最小化干扰泄露之间存在的相互矛盾，提出一种基于平衡策略的预编码算法，构建预编码算法数学模型，引入干扰代价函数，并借助拉格朗日方程对所提算法的预编码向量进行求解，同时对算法的实现步骤进行了说明。最后在仿真中，对效用函数的收敛速度与迭代次数的关系进行了仿真，并基于系统最大和速率对该算法与现有算法的性能进行了比较，仿真结果验证了该算法在收敛速度与系统吞吐量方面的优越性能。

关键词: 网络, 多输入多输出, 预编码, 平衡

Abstract: Maximizing the user's signal interference noise ratio and minimizing interference leakage is a contradiction in preprocessing for network Multiple-Input Multiple-Output (MIMO) system. Therefore, an equilibrium precoding algorithm based on equilibrium strategy was proposed. Mathematic model for precoding algorithm was constructed and interference pricing function was also introduced to obtain the precoding vector by Lagrange equation. Implementation procedure of the proposed algorithm was also summarized. Finally the proposed algorithm was compared with conventional algorithms and convergence of utility function was discussed by simulation. The results show that the proposed algorithm performs better than 〖BP(〗other schemes.〖BP)〗those existing schemes in convergence and throughput.

Key words: network, Multiple-Input Multiple-Output (MIMO), precoding, equilibrium

中图分类号:

TP393.03

张红郝东来. 一种平衡策略下网络多输入多输出系统的预编码方案[J]. 计算机应用, 2012, 32(05): 1224-1227.

ZHANG Hong HAO Dong-lai. Equilibrium precoding scheme for network multiple-input multiple-output system[J]. Journal of Computer Applications, 2012, 32(05): 1224-1227.

参考文献

［1］VENKATESAN S, LOZANO A, VALENZUELA R. Network MIMO: Overcoming intercell interference in indoor wireless systems［C］ // Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers, 2007. Washington, DC: IEEE Computer Society， 2007: 83-87.

［2］ANDREWS J G, CHOI W, HEATH R W. Overcoming interference in spatial multiplexing MIMO cellular networks［J］. IEEE Transactions on Wireless Communications,2007, 14(6): 95-104.

［3］SHIM S, KWAK J S, HEATH R W, et al. Block diagonalization for multi-user MIMO with other-cell interference［J］. IEEE Transactions on Wireless Communications, 2008,7(7): 2671-2681.

［4］SHAMAI S， ZAIDEL B M. Enhancing the cellular downlink capacity via co-processing at the transmitting end［C］// Proceedings IEEE Vehicular Technology Conference. Washington, DC: IEEE Computer Society，2001,3: 1745-1749.

［5］JAFAR S A, FOSCHINI G J, GOLDSMITH A J. PhantomNet: Exploring optimal multicellular multiple antenna systems［C］// 2002 IEEE 56th Conference on Vehicular Technology.Washington, DC: IEEE Computer Society,2002,1(1): 261-265.

［6］GOMADAM K S, CADAMBE R V, JAFAR S A. Approaching the capacity of wireless networks through distributed interference alignment［EB/OL］.［2011-09-18］.http://arxiv.org/abs/0803.3816.

［7］PETERS S W, HEATH R W. Interference alignment via alternation minimization［C］// Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing. Washington, DC: IEEE Computer Society， 2009: 2445-2448.

［8］TELATAR I E.Capacity of multi-antenna Gaussian channels［J］. European Transactions on Telecommunications, 1999,10(11): 585-595.

［9］JINDAL N, ANDREWS J G, WEBER S. Rethinking MIMO for wireless networks: Linear throughput increases with multiple receive antennas［C］// IEEE International Conference on Communications. Washington, DC: IEEE Computer Society, 2009: 1-6.

［10］HUANG J, BERRY R, HONIG M L. Distributed interference compensation for wireless networks［J］.IEEE Journal on Selected Areas in Communications, 2006,24(5):1074-1084.

［11］BERTSEKAS D P. Nonlinear programming［M］.2nd ed. Belmont,MA,USA: Athena Scientific, 1999.

［12］3GPP TR 25.814 V7.1.0 Physical layer aspects for evolved Universal Terrestrial Radio Access (UTRA) (Release 7) ［S］.2006.

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