摘要
在认知无线电网络中,由于深衰落和低信噪比的影响,单个认知用户的宽带频谱检测性能较差,且算法复杂度较高。针对该问题,提出一种基于重加权快速交替方向法的频谱感知算法。利用目标函数的凸性,通过求导简化辅助变量的更新过程。对目标函数进行线性化处理,增加一个二次项,使待估变量更新时部分项线性化的增广拉格朗日函数成为严格凸函数,并使用迭代软阈值算法进行求解。在目标项中增加大权值抑制信号中的非零元素,获得接近于最小?0范数的解。实验结果表明,该算法能有效提高低信噪比环境下的检测概率和检测速度。
To overcome the shortcomings by the existing wideband spectrum compressed sensing by single cognitive node： low effici- ency and high load in low Signal Noise Ratio（SNR） and deep fading, the algorithm based on reweighted fast alternating direction multiplier method for spectrum sensing is proposed. This algorithm can make the update of auxiliary variable simplified through derivation by utilizing convexity of the objective function. As for the update of estimated variables, it makes augmented Lagrangian functions with partial linearization become strictly convex function by linearization of objective function and adding a quadratic term, ultimately solving problems by using iterative soft threshold algorithm. Meanwhile, it adds weight in the target term and suppressing non-zero elements in signal witti large weight to get the solution close to minimum norm. Experimental results show that detection probability and detection speed of the algorithm is improved under＇the environment of low SNR.
出处
《计算机工程》
CAS
CSCD
2014年第1期6-10,共5页
Computer Engineering
基金
国家自然科学基金资助项目(61072075)
中南民族大学研究生创新基金资助项目(chxxyz20022)
关键词
认知无线电
压缩感知
频谱检测
交替方向法
迭代软阈值算法
拉格朗日乘子
cognitive radio
compressive sensing
spectrum detection
alternating direction method
iterative soft threshold algorithm
Lagrange multiplier
