Robust Cognitive Beamforming With Bounded Channel Uncertainties
Robust Cognitive Beamforming With Bounded Channel Uncertainties
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DOI：
10.1109/tsp.2009.2027462
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发表时间：
2009-12
影响因子：
5.4
通讯作者：
G. Zheng;Kai‐Kit Wong;B. Ottersten
中科院分区：
文献类型：
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作者：
G. Zheng;Kai‐Kit Wong;B. Ottersten
本文研究了多个Antenna认知无线电（CR）网络的稳健波束形成设计，该网络将传输到多个二级用户（SUS），并与多个用户的主要网络共存。我们的目标是通过基于不完美的通道状态信息（CSI）优化SU发射用户（PUS）的SU传输功率（PUS）的总限制，从而最大程度地利用SU传输功率和接收的干扰功率（PUS）的最小值SU传输功率和接收到的干扰功率的限制。为了建模CSI的不确定性，我们考虑了通道矩阵和通道协方差矩阵的一个有界区域。因此，在满足所有可能的CSI错误实现的干扰约束的同时，进行了优化。我们将首先得出干扰约束的等效条件，然后将问题转换为半明确编程（SDP）的形式，借助秩松弛，这导致了迭代算法，以获得可靠的最佳最佳光束形成解决方案。结果表明，与常规方法相比，实现的鲁棒性和性能增长，并且所提出的算法可以以高概率获得确切的鲁棒最佳解决方案。
This paper studies the robust beamforming design for a multi-antenna cognitive radio (CR) network, which transmits to multiple secondary users (SUs) and coexists with a primary network of multiple users. We aim to maximize the minimum of the received signal-to-interference-plus-noise ratios (SINRs) of the SUs, subject to the constraints of the total SU transmit power and the received interference power at the primary users (PUs) by optimizing the beamforming vectors at the SU transmitter based on imperfect channel state information (CSI). To model the uncertainty in CSI, we consider a bounded region for both cases of channel matrices and channel covariance matrices. As such, the optimization is done while satisfying the interference constraints for all possible CSI error realizations. We shall first derive equivalent conditions for the interference constraints and then convert the problems into the form of semi-definite programming (SDP) with the aid of rank relaxation, which leads to iterative algorithms for obtaining the robust optimal beamforming solution. Results demonstrate the achieved robustness and the performance gain over conventional approaches and that the proposed algorithms can obtain the exact robust optimal solution with high probability.