Stochastic Approach Optimization Algorithm for Cognitive Radio Spectrum Sensing Estimation Delay Time

JIANG Xianyang; XIA Kaili; TANG Xianghong

doi:10.11999/JEIT170122

Volume 39 Issue 11

Nov. 2017

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(11): 2548-2555

Li Tonghong, Liao Jianxin, Chen Junliang. THE STUDY OF SCP OVERLOAD CONTROL IN MULTI-SERVICE ENVIRONMENT[J]. Journal of Electronics & Information Technology, 1999, 21(1): 1-7.

Citation:

JIANG Xianyang, XIA Kaili, TANG Xianghong. Stochastic Approach Optimization Algorithm for Cognitive Radio Spectrum Sensing Estimation Delay Time[J]. Journal of Electronics & Information Technology, 2017, 39(11): 2548-2555. doi: 10.11999/JEIT170122

Li Tonghong, Liao Jianxin, Chen Junliang. THE STUDY OF SCP OVERLOAD CONTROL IN MULTI-SERVICE ENVIRONMENT[J]. Journal of Electronics & Information Technology, 1999, 21(1): 1-7.

Citation:

PDF( 398 KB)

Stochastic Approach Optimization Algorithm for Cognitive Radio Spectrum Sensing Estimation Delay Time

doi: 10.11999/JEIT170122

Funds:

Zhejiang Province Science and Technology Plan Public Welfare Technology Application Research Project (2017C31055), 2017 Open Research Foundation of Electronics Science and Technology for Top-ranking Discipline A Class in Zhejiang Province

Received Date: 2017-02-15
Rev Recd Date: 2017-08-17
Publish Date: 2017-11-19

Abstract

Abstract

In order to improve the spectrum efficiency in the cognitive radio networks, the optimization algorithm of the spectrum sensing estimation time is presented. The longer sensing time will bring two aspects of the consequences. On the one hand, the channel parameters are estimated more accurate so as to reduce the interference to the authorized users and to improve the throughput of the cognitive users. On the other hand, it shortens the transmission time so as to decease the system throughput. In this time, it exists an optimal sensing time to maximize the throughput. It is considered that the channel state information of sub-bands is exponentially distributed, so a stochastic programming method is proposed to optimize the sensing time of the cognitive radio networks. The computer simulation results show that the algorithm is effective and has a certain engineering application value.
- Cognitive radio networks,
- Spectrum sensing,
- Stochastic approach

FullText(HTML)

References(18)

References

MITOLA J and MAGUIRE G Q J. Cognitive radio: Making software radios more personal[J]. IEEE Personal Communications, 1999, 6(4): 13-18. doi: 10.1109/98.788210.

ASTAIZA E, JOJOA P, and BERMUDEZ H. Compressive local wideband spectrum sensing algorithm for multiantenna cognitive radios[C]. 2016 8th IEEE Latin-American Conference on Communications (LATINCOM), Medellin, Colombia, 2016: 1-6. doi: 10.1109/LATINCOM.2016. 7811577.

FEBRIANTO T and SHIKH-BAHAEI M. Optimal full- duplex cooperative spectrum sensing in asynchronous cognitive networks[C]. 2016 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob), Bandung, Indonesia, 2016: 1-6. doi: 10.1109/APWiMob.2016.7811446.

OZCAN G, GURSOY M C, TRAN N, et al. Energy-efficient power allocation in cognitive radio systems with imperfect spectrum sensing[J]. IEEE Journal on Selected Areas in Communications, 2016, 34(12): 3466-3481. doi: 10.1109/ JSAC.2016.2621399.

GIWELI Nabil, SHAHRESTANI Seyed, and CHEUNG Hon. QoS-aware spectrum sensing in White-Fi cognitive radio networks[C]. 2016 10th International Conference on Signal Processing and Communication Systems (ICSPCS), Surfers Paradise, Gold Coaat, Australia, 2016: 1-8. doi: 10.1109/ ICSPCS.2016.7843376.

WANG Xinyu, JIA Min, GUO Qing et al. Reputation-based cooperative spectrum sensing algorithm for mobile cognitive radio networks[J]. China Communications, 2017, 14(1): 124-134. doi: 10.1109/CC.2017.7839763.

党小宇, 李阿明, 虞湘宾. 基于空间谱的频谱感知算法及性能分析[J]. 电子与信息学报, 2016, 38(5): 1179-1185. doi: 10.11999/JEIT150823.

DANG Xiaoyu, LI Aming, and YU Xiangbin. Spatial spectrum based spectrum sensing algorithm and performance analysis[J]. Journal of Electronics Information Technology, 2016, 38(5): 1179-1185. doi: 10.11999/JEIT150823.

WANG Yifan and LI Husheng. Universal quickest spectrum sensing[C]. 2016 IEEE Global Communications Conference (GLOBECOM), Washington, DC, USA, 2016: 1-6. doi: 10.1109/GLOCOM.2016.7842360.

SHAIKH Bushra, SHAH S M Z, and UMRANI F. An unsigned autocorrelation based blind spectrum sensing approach for cognitive radio[C]. 2016 International Conference on Open Source Systems Technologies (ICOSST), Lahore, Pakistan, 2016: 48-53. doi: 10.1109/ ICOSST.2016.7838576.

刘玉磊, 梁俊, 肖楠, 等. 基于马尔科夫模型的认知无线电动态双门限能量检测策略[J]. 电子与信息学报, 2016, 38(10): 2590-2597. doi: 10.11999/JEIT151400.

LIU Yulei, LIANG Jun, XIAO Nan et al. Dynamic double threshold energy detection based on markov model in cognitive radio[J]. Journal of Electronics Information Technology, 2016, 38(10): 2590-2597. doi: 10.11999/JEIT 151400.

JIANG Xianyang, SHEN Lei, XU Xiaorong et al. Power allocation optimisation for high throughput with mixed spectrum access based on interference evaluation strategy in cognitive relay networks[J]. IET Communications, 2016, 10(12): 1428-1435. doi: 10.1049/iet-com.2015.0849.

LIU X. A new sensing-throughput tradeoff scheme in cooperative multiband cognitive radio network[J]. International Journal of Network Management, 2014, 24(3): 200-217. doi: 10.1002/nem.1859.

曹龙, 赵杭生, 鲍丽娜, 等. 分层认知无线电网络中基于稳定匹配的资源分配算法[J]. 电子与信息学报, 2016, 38(10): 2605-2611. doi: 10.11999/JEIT151460.

CAO Long, ZHAO Hangsheng, BAO Lina et al. Resource allocation algorithm based on stable matching in hierarchical cognitive radio networks[J]. Journal of Electronics Information Technology, 2016, 38(10): 2605-2611. doi: 10.11999/JEIT151460.

ABDI Y and RISTANIEMI T. Random interruptions in cooperation for spectrum sensing in cognitive radio networks[J]. IEEE Transactions on Communications, 2017, 65(1): 49-65. doi: 10.1109/TCOMM.2016.2620465.

ALMALFOUH S M and STUBER G L. Joint spectrum- sensing design and power control in cognitive radio networks: A stochastic approach[J]. IEEE Transactions on Wireless Communications, 2012, 11(12): 4372-4380. doi: 10.1109/ TWC.2012.100112.111894.

Relative Articles

Supplements(0)

Cited By