Journal on Communications ›› 2021, Vol. 42 ›› Issue (12): 182-191.doi: 10.11959/j.issn.1000-436x.2021220
• Papers • Previous Articles Next Articles
Jianxin GAI, Xianfeng XUE, Ruixiang NAN, Jingyi WU
Revised:
2021-11-04
Online:
2021-12-01
Published:
2021-12-01
Supported by:
CLC Number:
Jianxin GAI, Xianfeng XUE, Ruixiang NAN, Jingyi WU. Spectrum sensing method based on residual dense network[J]. Journal on Communications, 2021, 42(12): 182-191.
[1] | DIGHAM F F , ALOUINI M S , SIMON M K . On the energy detection of unknown signals over fading channels[J]. IEEE Transactions on Communications, 2007,55(1): 21-24. |
[2] | WU J Y , WANG C H , WANG T Y . Performance analysis of energy detection based spectrum sensing with unknown primary signal arrival time[J]. IEEE Transactions on Communications, 2011,59(7): 199-206. |
[3] | OH H , NAM H . Energy detection scheme in the presence of burst signals[J]. IEEE Signal Processing Letters, 2019,26(4): 582-586. |
[4] | YANG M C , LI Y , LIU X F ,et al. Cyclostationary feature detection based spectrum sensing algorithm under complicated electromagnetic environment in cognitive radio networks[J]. China Communications, 2015,12(9): 35-44. |
[5] | SHEN J C , ALSUSA E . Joint cycle frequencies and lags utilization in cyclostationary feature spectrum sensing[J]. IEEE Transactions on Signal Processing, 2013,61(21): 5337-5346. |
[6] | ZHANG X Z , GAO F F , CHAI R ,et al. Matched filter based spectrum sensing when primary user has multiple power levels[J]. China Communications, 2015,12(2): 21-31. |
[7] | LIU C , WANG J , LIU X M ,et al. Maximum eigenvalue-based goodness-of-fit detection for spectrum sensing in cognitive radio[J]. IEEE Transactions on Vehicular Technology, 2019,68(8): 7747-7760. |
[8] | AWE O P , DELIGIANNIS A , LAMBOTHARAN S . Spatio-temporal spectrum sensing in cognitive radio networks using beamformer-aided SVM algorithms[J]. IEEE Access, 2018,6: 25377-25388. |
[9] | BAO J R , NIE J Y , LIU C ,et al. Improved blind spectrum sensing by covariance matrix Cholesky decomposition and RBF-SVM decision classification at low SNRs[J]. IEEE Access, 2019,7: 97117-97129. |
[10] | 陈思吉, 王欣, 申滨 . 一种基于支持向量机的认知无线电频谱感知方案[J]. 重庆邮电大学学报(自然科学版), 2019,31(3): 313-322. |
CHEN S J , WANG X , SHEN B . A support vector machine based spectrum sensing for cognitive radios[J]. Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition), 2019,31(3): 313-322. | |
[11] | TANG Y J , ZHANG Q Y , LIN W . Artificial neural network based spectrum sensing method for cognitive radio[C]// Proceedings of 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM). Piscataway:IEEE Press, 2010: 1-4. |
[12] | VYAS M R , PATEL D K , LOPEZ-BENITEZ M , . Artificial neural network based hybrid spectrum sensing scheme for cognitive radio[C]// Proceedings of 2017 IEEE 28th Annual International Symposium on Personal,Indoor,and Mobile Radio Communications (PIMRC). Piscataway:IEEE Press, 2017: 1-7. |
[13] | 高红民, 曹雪莹, 杨耀 ,等. 基于CNN的双边融合网络在高光谱图像分类中的应用[J]. 通信学报, 2020,41(11): 132-140. |
GAO H M , CAO X Y , YANG Y ,et al. Application of bilateral fusion model based on CNN in hyperspectral image classification[J]. Journal on Communications, 2020,41(11): 132-140. | |
[14] | YU C Y , HAN R , SONG M P ,et al. A simplified 2D-3D CNN architecture for hyperspectral image classification based on spatial-spectral fusion[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020,13: 2485-2501. |
[15] | MAFFEI A , HAUT J M , PAOLETTI M E ,et al. A single model CNN for hyperspectral image denoising[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020,58(4): 2516-2529. |
[16] | CHEN Y S , ZHU K Q , ZHU L ,et al. Automatic design of convolutional neural network for hyperspectral image classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019,57(9): 7048-7066. |
[17] | LIU C , WANG J , LIU X M ,et al. Deep CM-CNN for spectrum sensing in cognitive radio[J]. IEEE Journal on Selected Areas in Communications, 2019,37(10): 2306-2321. |
[18] | LEE W , KIM M , CHO D H . Deep cooperative sensing:cooperative spectrum sensing based on convolutional neural networks[J]. IEEE Transactions on Vehicular Technology, 2019,68(3): 3005-3009. |
[19] | 张孟伯, 王伦文, 冯彦卿 . 基于卷积神经网络的OFDM频谱感知方法[J]. 系统工程与电子技术, 2019,41(1): 178-186. |
ZHANG M B , WANG L W , FENG Y Q . OFDM spectrum sensing method based on convolutional neural networks[J]. Systems Engineering and Electronics, 2019,41(1): 178-186. | |
[20] | MARSHALL J A . Neural networks for pattern recognition[J]. Neural Networks, 1995,8(3): 493-494. |
[21] | JAMES D A , VENABLES W N , RIPLEY B D . Modern applied statistics with S-PLUS[J]. Technometrics, 1996,38(1): 77. |
[22] | PHATAK D S , KOREN I . Connectivity and performance tradeoffs in the cascade correlation learning architecture[J]. IEEE Transactions on Neural Networks, 1994,5(6): 930-935. |
[23] | WILAMOWSKI B M , YU H . Neural network learning without backpropagation[J]. IEEE Transactions on Neural Networks, 2010,21(11): 1793-1803. |
[24] | 陈丽, 陈静, 高新涛 ,等. 基于支持向量机与反 K 近邻的分类算法研究[J]. 计算机工程与应用, 2010,46(24): 135-137,188. |
CHEN L , CHEN J , GAO X T ,et al. Classification algorithm research based on support vector machine and reverse K-nearest neighbor[J]. Computer Engineering and Applications, 2010,46(24): 135-137,188. | |
[25] | 孙月驰, 李冠 . 基于卷积神经网络嵌套模型的人群异常行为检测[J]. 计算机应用与软件, 2019,36(3): 196-201,276. |
SUN Y C , LI G . Abnormal behavior detection of crowds based on nested model of convolutional neural network[J]. Computer Applications and Software, 2019,36(3): 196-201,276. |
[1] | Zhihong QIAN, Lin XIAO, Xue WANG. Review on strategic technology of dense connection for the future mobile network [J]. Journal on Communications, 2021, 42(4): 22-43. |
[2] | Zhiguo SUN, Xinyue REN, Zengmao CHEN, Ming DIAO. Cooperative spectrum sensing method and performance analysis based on similarity between evidences [J]. Journal on Communications, 2020, 41(12): 139-147. |
[3] | Wenjing ZHAO,He LI,Minglu JIN. Fusion spectrum sensing algorithm based on eigenvalues [J]. Journal on Communications, 2019, 40(11): 57-64. |
[4] | Yuanhua FU,Zhiming HE. Distance criterion-based quantizer design for cooperative spectrum sensing [J]. Journal on Communications, 2018, 39(9): 49-56. |
[5] | Yu-lei LIU,Jun LIANG,Nan XIAO,Xiao-gang YUAN,Zhen-hao ZHANG. Spectrum sensing method based on past channel sensing information [J]. Journal on Communications, 2017, 38(8): 118-130. |
[6] | Pan YU,Bin LI,Cheng-lin ZHAO. Asynchronous perception algorithm based on energy detection [J]. Journal on Communications, 2017, 38(3): 165-173. |
[7] | Jing-yu FENG,Xu DU,Hong-gang WANG,Wen-hua HUANG. Research on multi-channel routing threats and defense for cognitive ad hoc network [J]. Journal on Communications, 2016, 37(Z1): 92-97. |
[8] | Ming WU,Tie-cheng SONG,Jing HU,Lian-feng SHEN. Novel cooperative global spectrum sensing algorithm based on variational Bayesian inference [J]. Journal on Communications, 2016, 37(2): 116-124. |
[9] | Yang ZHANG,Hua PENG,Ke-xian GONG. Multi scale power spectral density subband gradient-based spectrum sensing algorithm and performance analysis [J]. Journal on Communications, 2016, 37(2): 191-198. |
[10] | Chang LIU,SajjadAli Syed,Rui ZHANG,Si-ying LI,Jie WANG,Ming-lu JIN. Spatial spectrum based blind spectrum sensing for multi-antenna cognitive radio system [J]. Journal on Communications, 2015, 36(4): 115-124. |
[11] | Yin MI,Guang-yue LU. Cooperative spectrum sensing algorithm based on limiting eigenvalue distribution [J]. Journal on Communications, 2015, 36(1): 84-89. |
[12] | Xu-zhou ZUO,Wei-wei XIA,Lian-feng SHEN. Dynamic spectrum access method for femtocells in LTE [J]. Journal on Communications, 2015, 36(1): 111-120. |
[13] | . New spectrum sensing method under time-variant flat fading channels [J]. Journal on Communications, 2014, 35(7): 8-69. |
[14] | Meng-wei SUN,Long ZHAO,Qiao-chun XU,Bin LI,Cheng-lin ZHAO. New spectrum sensing method under time-variant flat fading channels [J]. Journal on Communications, 2014, 35(7): 63-69. |
[15] | . Gerschgorin disk theorem based spectrum sensing for wideband cognitive radio [J]. Journal on Communications, 2014, 35(4): 1-10. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||
|