Optimizing Spectrum Sensing Time With Adaptive Sensing Interval for Energy-Efficient CRSNs

The cognitive radio (CR) technology allows secondary users (SUs) to occupy the licensed bands opportunistically without causing interferences to primary users (PUs). SUs perform spectrum sensing to detect whether PUs are busy or idle. Therefore, spectrum sensing directly affects the performance of the PU protection and the secondary throughput. The sensing time is a critical parameter for spectrum sensing performance, and the optimum sensing time is a tradeoff between the spectrum sensing performance and the secondary throughput. In this paper, a novel spectrum sensing scheme is proposed to maximize both sensing accuracy and network energy efficiency. In order to provide a better protection for the PU, another spectrum sensing is adaptively performed according to the first sensing result. In other words, SU will perform spectrum sensing again to confirm that the PU is indeed idle when the first sensing result indicates the PU is idle. Due to the energy constraint in CR sensor networks, this adaptive sensing interval can also be adjusted according to the varying activity of the PU to maximize the network energy efficiency. Finally, our simulation study validates that the proposed scheme improves both the spectrum sensing performance and the energy efficiency compared with other existing methods.

[1]  Keivan Navaie,et al.  On the Sensing Time and Achievable Throughput in Sensor-Enabled Cognitive Radio Networks , 2013, ISWCS.

[2]  Hossam M. Farag,et al.  An efficient dynamic thresholds energy detection technique for Cognitive Radio spectrum sensing , 2014, 2014 10th International Computer Engineering Conference (ICENCO).

[3]  Hai Jiang,et al.  Analysis of area under the ROC curve of energy detection , 2010, IEEE Transactions on Wireless Communications.

[4]  Li Yi,et al.  The energy efficiency optimization based on dynamic spectrum sensing and nodes scheduling in cognitive radio sensor networks , 2015, The 27th Chinese Control and Decision Conference (2015 CCDC).

[5]  Ahmed E. Kamal,et al.  Spectrum decision for efficient routing in cognitive radio network , 2012, 2012 IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS 2012).

[6]  Victor C. M. Leung,et al.  Sensing Time Optimization and Power Control for Energy Efficient Cognitive Small Cell With Imperfect Hybrid Spectrum Sensing , 2017, IEEE Transactions on Wireless Communications.

[7]  Rausley A. A. de Souza,et al.  On the throughput of cognitive radio networks using eigenvalue-based cooperative spectrum sensing under complex Nakagami-m fading , 2016, 2016 International Symposium on Networks, Computers and Communications (ISNCC).

[8]  Tamer A. ElBatt,et al.  Optimization of channel sensing time and order for cognitive radios , 2011, 2011 IEEE Wireless Communications and Networking Conference.

[9]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[10]  Taieb Znati,et al.  Optimal Spectrum Sensing Interval in Cognitive Radio Networks , 2014, IEEE Transactions on Parallel and Distributed Systems.

[11]  Wenxiao Wang,et al.  Frequency spectrum sensing of cognitive radio based on Bayesian network , 2015, 2015 8th International Congress on Image and Signal Processing (CISP).

[12]  Yongqiang Hei,et al.  Energy efficient techniques with sensing time optimization in cognitive radio networks , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[13]  H. Urkowitz Energy detection of unknown deterministic signals , 1967 .

[14]  Yiyang Pei,et al.  Energy-Efficient Design of Sequential Channel Sensing in Cognitive Radio Networks: Optimal Sensing Strategy, Power Allocation, and Sensing Order , 2011, IEEE Journal on Selected Areas in Communications.

[15]  Mohamed-Slim Alouini,et al.  On the Energy Detection of Unknown Signals Over Fading Channels , 2007, IEEE Transactions on Communications.

[16]  Fuhui Zhou,et al.  Optimal sensing interval in cognitive radio networks with imperfect spectrum sensing , 2016, IET Commun..

[17]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[18]  Dong-Jun Lee,et al.  Adaptive Random Access for Cooperative Spectrum Sensing in Cognitive Radio Networks , 2015, IEEE Transactions on Wireless Communications.

[19]  Linda Doyle,et al.  Cyclostationary Signatures in Practical Cognitive Radio Applications , 2008, IEEE Journal on Selected Areas in Communications.

[20]  Ahmed E. Kamal,et al.  On-Demand Multicast Routing in Cognitive Radio Mesh Networks , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[21]  Avtar Singh Buttar,et al.  Cyclostationary feature based detection using window method in SIMO cognitive radio system , 2016, 2016 International Conference on Computing, Communication and Automation (ICCCA).

[22]  Pasquale Pace,et al.  OpenBTS: A Step Forward in the Cognitive Direction , 2012, 2012 21st International Conference on Computer Communications and Networks (ICCCN).

[23]  Zhongding Lei,et al.  IEEE 802.22: The first cognitive radio wireless regional area network standard , 2009, IEEE Communications Magazine.

[25]  Majid Ahmadi,et al.  Joint Optimal Transmission Power and Sensing Time for Energy Efficient Spectrum Sensing in Cognitive Radio System , 2017, IEEE Sensors Journal.

[26]  Dharma P. Agrawal,et al.  Markov chain existence and Hidden Markov models in spectrum sensing , 2009, 2009 IEEE International Conference on Pervasive Computing and Communications.

[27]  R.W. Brodersen,et al.  Spectrum Sensing Measurements of Pilot, Energy, and Collaborative Detection , 2006, MILCOM 2006 - 2006 IEEE Military Communications conference.

[28]  Hao He,et al.  Adaptive Spectrum Sensing for Time-Varying Channels in Cognitive Radios , 2013, IEEE Wireless Communications Letters.

[29]  Ling Luo,et al.  Efficient Spectrum Sensing for Cognitive Radio Networks via Joint Optimization of Sensing Threshold and Duration , 2012, IEEE Transactions on Communications.

[30]  Sheetal Ashish Jain,et al.  Performance analysis of energy and eigenvalue based detection for spectrum sensing in Cognitive Radio network , 2015, 2015 International Conference on Pervasive Computing (ICPC).

[31]  Maryan Kyryk,et al.  Performance comparison of cognitive radio networks spectrum sensing methods , 2016, 2016 13th International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET).

[32]  M. Nasiri-Kenari,et al.  Learning-based spectrum sensing time optimization in cognitive radio systems , 2012, 6th International Symposium on Telecommunications (IST).

[33]  Xin Liu,et al.  Joint optimal energy-efficient cooperative spectrum sensing and transmission in cognitive radio , 2017, China Communications.

[34]  Habib F. Rashvand,et al.  A channel assignment algorithm for Cognitive Radio wireless sensor networks , 2012 .