摘要
针对传统干扰对齐算法需要理想的信道状态信息,且对信道误差敏感的问题,基于范数有界信道误差模型,提出了三种最坏情况逼近的鲁棒干扰对齐算法.首先,为减少干扰和信号泄漏,提出了最小化最大泄漏功率的鲁棒算法;其次,为增大子空间内的干扰和信号,提出了最大化最小子空间投影的鲁棒算法;最后,将前两种方法结合,提出了联合优化的鲁棒算法.仿真结果表明,在信道误差范数有界时,三种算法性能均优于传统的干扰对齐算法,验证了所提算法具有较好的鲁棒性.
Conventional interference alignment （IA） requires perfect channel state infromation and is sensitive to channel uncertainties. Based on the norm-bounded channel uncertainties model, this paper proposes three worst-case approach robust IA algorithms. First, to decrease the interference and signal leakage, a robust algorithm is proposed to minimize the maximum leakage power; Second, to increase the interference and signal in the corresponding subspace, another robust algorithm is proposed to maximize the minimun subspace projection; finally, a united robust algorithm is proposed by uniting the two algorithms above. Simulation results show that the proposed algorithms can outperform the conventional algorithms when channel uncertainties are norm-bounded, which affirms the robustness of the proposed algorithm.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2017年第1期134-139,181,共7页
Journal of Xidian University
基金
国家"863"计划资助项目(2012AA01A502
2012AA01A505)
关键词
干扰对齐
干扰抑制
鲁棒性
范数有界信道误差
信道容量
半正定规划
interference alignment
interference suppression
robustness
norm-bounded channeluncertainties
channel capacity
semidefinite programming
