Robust interference alignment algorithm for cognitive MIMO interference network

Shi-lei ZHU; You ZHOU; Xiu-kun REN; Han-ying HU

doi:10.11959/j.issn.1000-436x.2016063

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Robust interference alignment algorithm for cognitive MIMO interference network

Academic paper | 更新时间：2024-06-05

- Robust interference alignment algorithm for cognitive MIMO interference network
- Journal on Communications Vol. 37, Issue 3, Pages: 157-164(2016)
- 作者机构：
  
  1. 解放军信息工程大学导航与空天目标工程学院，河南郑州450002
  2. 解放军信息工程大学解放军信息技术研究所，河南郑州450002
- 作者简介：
- 基金信息：
  
  The Important National Science＆Technology Specific Project(2011ZX03003-003-02);The National High Technology Research and Development Program of China (863 Program)(2012AA01A502);The National High Technology Research and Development Program of China (863 Program)(2012AA01A505)
- DOI：10.11959/j.issn.1000-436x.2016063
  CLC： TN92
- Online First：2016-03，
  
  Published：25 March 2016
- 稿件说明：
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Shi-lei ZHU, You ZHOU, Xiu-kun REN, et al. Robust interference alignment algorithm for cognitive MIMO interference network[J]. Journal on Communications, 2016, 37(3): 157-164.
DOI：

Shi-lei ZHU, You ZHOU, Xiu-kun REN, et al. Robust interference alignment algorithm for cognitive MIMO interference network[J]. Journal on Communications, 2016, 37(3): 157-164. DOI： 10.11959/j.issn.1000-436x.2016063.

摘要

针对重叠式认知 MIMO 干扰信道状态信息(CSI)非理想的问题，提出一种顽健干扰对齐算法。首先通过欧几里得球形不确定性刻画非理想CSI，以最小化用户干扰泄漏为目标，构建非理想CSI条件下发送预编码和接收干扰子空间矩阵的优化模型；然后利用矩阵范数的不等式性质，推导了最差条件下的主用户干扰温度约束；最后采用拉格朗日部分对偶及次梯度更新方法，推导出收发矩阵之间的迭代关系，并从理论上分析了顽健算法的适用条件和可达自由度范围。仿真结果表明，所提算法具有较好的顽健性，且获得的次用户网络性能优于已有算法。

Abstract

A robust interference alignment algorithm was proposed for underlay cognitive MIMO interference network with imperfect channel-state information (CSI).Firstly

imperfect CSI was characterized by Euclidean ball-shaped uncer-tainty

based on which the optimization model of transmitting precoding and receiving interference subspace matrix was constructed with aimed of minimizing interference leak Then

primary users' interference temperature constraint un-der the worst-case condition was derived according to the matrix norm inequality.Finally

alternate iteration expressions of transceiver matrixes were obtained exploiting Lagrange partial dual-decomposition theory and sub-gradient update method.Moreover

the proposed algorithm's application condition and degrees of freedom range were theoretically ana-lyzed.Simulation results show that the proposed algor m is robust and its secondary users' network performance out-performs existing algorithms'.

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references

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