Cooperative Compressive Spectrum Sensing in Cognitive Underw ater Acoustic Communication Networks  

作　　者：左加阔 陶文凤 包永强 赵力 邹采荣 

机构地区：[1]School of Internet of Things,Nanjing University of Posts and Telecommunications [2]Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education,Southeast University [3]School of Communication Engineering,Nanjing Institute of Technology

出　　处：《Journal of Donghua University(English Edition)》2015年第4期523-529,共7页东华大学学报（英文版）

基　　金：National Natural Science Foundations of China(Nos.60872073,51075068,60975017,61301219);Doctoral Fund of Ministry of Education,China(No.20110092130004)

摘　　要：Because of the specific of underwater acoustic channel,spectrum sensing entails many difficulties in cognitive underwater acoustic communication( CUAC) networks, such as severe frequency-dependent attenuation and low signal-to-noise ratios. To overcome these problems, two cooperative compressive spectrum sensing( CCSS) schemes are proposed for different scenarios( with and without channel state information). To strengthen collaboration among secondary users( SUs),cognitive central node( CCN) is provided to collect data from SUs. Thus,the proposed schemes can obtain spatial diversity gains and exploit joint sparse structure to improve the performance of spectrum sensing. Since the channel occupancy is sparse,we formulate the spectrum sensing problems into sparse vector recovery problems,and then present two CCSS algorithms based on path-wise coordinate optimization( PCO) and multi-task Bayesian compressive sensing( MT-BCS),respectively.Simulation results corroborate the effectiveness of the proposed methods in detecting the spectrum holes in underwater acoustic environment.Because of the specific of underwater acoustic channel,spectrum sensing entails many difficulties in cognitive underwater acoustic communication（ CUAC） networks, such as severe frequency-dependent attenuation and low signal-to-noise ratios. To overcome these problems, two cooperative compressive spectrum sensing（ CCSS） schemes are proposed for different scenarios（ with and without channel state information）. To strengthen collaboration among secondary users（ SUs）,cognitive central node（ CCN） is provided to collect data from SUs. Thus,the proposed schemes can obtain spatial diversity gains and exploit joint sparse structure to improve the performance of spectrum sensing. Since the channel occupancy is sparse,we formulate the spectrum sensing problems into sparse vector recovery problems,and then present two CCSS algorithms based on path-wise coordinate optimization（ PCO） and multi-task Bayesian compressive sensing（ MT-BCS）,respectively.Simulation results corroborate the effectiveness of the proposed methods in detecting the spectrum holes in underwater acoustic environment.

关 键 词：cognitive underwater acoustic communication(CUAC) spectrum sensing compressive sensing path-wise coordinate optimization(PCO) multi-task Bayesian compressive sensing(MT-BCS) 

分 类 号：TN929.3[电子电信—通信与信息系统]