COOPERATIVE WIDEBAND SPECTRUM SENSING BASED ON SEQUENTIAL COMPRESSED SENSING  

作　　者：Gu Bin Yang Zhen Hu Haifeng 

机构地区：[1]Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunications, Nanjing 210003, China [2]Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

出　　处：《Journal of Electronics(China)》2011年第3期313-319,共7页电子科学学刊（英文版）

基　　金：Supported by the National High Technology Research and Development Program(No.2009AA01Z241);the National Natural Science Foundation(No.60971129,No.61071092)

摘　　要：Compressed sensing offers a new wideband spectrum sensing scheme in Cognitive Radio (CR). A major challenge of this scheme is how to determinate the required measurements while the signal sparsity is not known a priori. This paper presents a cooperative sensing scheme based on se-quential compressed sensing where sequential measurements are collected from the analog-to-information converters. A novel cooperative compressed sensing recovery algorithm named Simul-taneous Sparsity Adaptive Matching Pursuit (SSAMP) is utilized for sequential compressed sensing in order to estimate the reconstruction errors and determinate the minimal number of required meas-urements. Once the fusion center obtains enough measurements, the reconstruction spectrum sparse vectors are then used to make a decision on spectrum occupancy. Simulations corroborate the effec-tiveness of the estimation and sensing performance of our cooperative scheme. Meanwhile, the per-formance of SSAMP and Simultaneous Orthogonal Matching Pursuit (SOMP) is evaluated by Mean-Square estimation Errors (MSE) and sensing time.Compressed sensing offers a new wideband spectrum sensing scheme in Cognitive Radio （CR）. A major challenge of this scheme is how to determinate the required measurements while the signal sparsity is not known a priori. This paper presents a cooperative sensing scheme based on se-quential compressed sensing where sequential measurements are collected from the analog-to-information converters. A novel cooperative compressed sensing recovery algorithm named Simul-taneous Sparsity Adaptive Matching Pursuit （SSAMP） is utilized for sequential compressed sensing in order to estimate the reconstruction errors and determinate the minimal number of required meas-urements. Once the fusion center obtains enough measurements, the reconstruction spectrum sparse vectors are then used to make a decision on spectrum occupancy. Simulations corroborate the effec-tiveness of the estimation and sensing performance of our cooperative scheme. Meanwhile, the per-formance of SSAMP and Simultaneous Orthogonal Matching Pursuit （SOMP） is evaluated by Mean-Square estimation Errors （MSE） and sensing time.b

关 键 词：Cognitive Radio (CR) Wideband spectrum sensing Sequential compressed sensing Matching pursuit 

分 类 号：TN92[电子电信—通信与信息系统]