Unified Channel Management for Cognitive Radio Sensor Networks Aided Internet of Things

Cognitive capabilities are indispensable for the Internet of Things (IoT) not only to equip them with learning, thinking, and decision-making capabilities but also to cater to their unprecedented huge spectrum requirements due to their gigantic numbers and heterogeneity. Therefore, in this paper, a novel unified channel management framework (CMF) is introduced for cognitive radio sensor networks (CRSNs), which comprises an (1) opportunity detector (ODR), (2) opportunity scheduler (OSR), and (3) opportunity ranker (ORR) to specifically address the immense and diverse spectrum requirements of CRSN-aided IoT. The unified CMF is unique for its type as it covers all three angles of spectrum management. The ODR is a double threshold based multichannel spectrum sensor that allows an IoT device to concurrently sense multiple channels to maximize spectrum opportunities. OSR is an integer linear programming (ILP) based channel allocation mechanism that assigns channels to heterogeneous IoT devices based on their minimal quality of service (QoS) requirements. ORR collects feedback from IoT devices about their transmission experience and generates special channel-sensing order (CSO) for each IoT device based on the data rate and idle-time probabilities. The simulation results demonstrate that the proposed CMF outperforms the existing ones in terms of collision probability, detection probability, blocking probability, idle-time probability, and data rate.

[1]  Xuemin Shen,et al.  Dynamic Channel Access to Improve Energy Efficiency in Cognitive Radio Sensor Networks , 2016, IEEE Transactions on Wireless Communications.

[2]  Tao Luo,et al.  An Energy Detection Algorithm Based on Double-Threshold in Cognitive Radio Systems , 2009, 2009 First International Conference on Information Science and Engineering.

[3]  Kyung-Geun Lee,et al.  Spectrum sharing optimization with QoS guarantee in cognitive radio networks , 2013, Comput. Electr. Eng..

[4]  Jin Chen,et al.  The predictability study of channel state duration based on Hurst index , 2014, 2014 IEEE/CIC International Conference on Communications in China (ICCC).

[5]  Ghaith Hattab,et al.  Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks , 2014, Proceedings of the IEEE.

[6]  H. S. Byun,et al.  A decision support system for the selection of a rapid prototyping process using the modified TOPSIS method , 2005 .

[7]  Jun Wang,et al.  Cooperative Spectrum Sensing in Heterogeneous Cognitive Radio Networks Based on Normalized Energy Detection , 2016, IEEE Transactions on Vehicular Technology.

[8]  Moe Z. Win,et al.  MRC performance for M-ary modulation in arbitrarily correlated Nakagami fading channels , 2000, IEEE Communications Letters.

[9]  J. I. Mararm,et al.  Energy Detection of Unknown Deterministic Signals , 2022 .

[10]  Kyung-Geun Lee,et al.  Optimized Energy Harvesting, Cluster-Head Selection and Channel Allocation for IoTs in Smart Cities , 2016, Sensors.

[11]  Taimur Hassan,et al.  Fully Automated Multi-Resolution Channels and Multithreaded Spectrum Allocation Protocol for IoT Based Sensor Nets , 2018, IEEE Access.

[12]  Laurie Cuthbert,et al.  Qos-aware resource allocation for multimedia users in a multi-cell spectrum sharing radio network , 2012, PM2HW2N '12.

[13]  Mohammad Javad Saber,et al.  Multiband Cooperative Spectrum Sensing for Cognitive Radio in the Presence of Malicious Users , 2016, IEEE Communications Letters.

[14]  R. M. A. P. Rajatheva,et al.  On the energy detection of unknown deterministic signal over Nakagami channelswith selection combining , 2009, 2009 Canadian Conference on Electrical and Computer Engineering.

[15]  K. J. Ray Liu,et al.  Joint Spectrum Sensing and Access Evolutionary Game in Cognitive Radio Networks , 2013, IEEE Transactions on Wireless Communications.

[16]  Mohamed Ibnkahla,et al.  Energy and Spectral Efficient Cognitive Radio Sensor Networks for Internet of Things , 2018, IEEE Internet of Things Journal.

[17]  Mohamed Ibnkahla,et al.  Optimized node classification and channel pairing scheme for RF energy harvesting based cognitive radio sensor networks , 2015, 2015 IEEE 12th International Multi-Conference on Systems, Signals & Devices (SSD15).

[18]  Erik G. Larsson,et al.  Spectrum Sensing for Cognitive Radio : State-of-the-Art and Recent Advances , 2012, IEEE Signal Processing Magazine.

[19]  Alagan Anpalagan,et al.  Efficient Energy Management for the Internet of Things in Smart Cities , 2017, IEEE Communications Magazine.

[20]  A. Ghasemi,et al.  Collaborative spectrum sensing for opportunistic access in fading environments , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[21]  Özgür B. Akan,et al.  Reliability and congestion control in cognitive radio sensor networks , 2011, Ad Hoc Networks.

[22]  K. J. Ray Liu,et al.  Renewal-theoretical dynamic spectrum access in cognitive radio network with unknown primary behavior , 2011, IEEE Journal on Selected Areas in Communications.

[23]  Amy Nordrum,et al.  The internet of fewer things [News] , 2016 .

[24]  Geoffrey Ye Li,et al.  Cooperative Spectrum Sensing in Cognitive Radio, Part I: Two User Networks , 2007, IEEE Transactions on Wireless Communications.

[25]  Jianwei Huang,et al.  Dynamic Channel Selection in Cognitive Radio Network with Channel Heterogeneity , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[26]  Kyung-Geun Lee,et al.  Joint Sensor-Node Selection and Channel Allocation Scheme for Cognitive Radio Sensor Networks , 2013 .

[27]  Albert H. Nuttall,et al.  Some integrals involving the QM function (Corresp.) , 1975, IEEE Trans. Inf. Theory.

[28]  Chi Harold Liu,et al.  Scalable Channel Allocation and Access Scheduling for Wireless Internet-of-Things , 2013, IEEE Sensors Journal.

[29]  Özgür B. Akan,et al.  Energy-Efficient Packet Size Optimization for Cognitive Radio Sensor Networks , 2012, IEEE Transactions on Wireless Communications.

[30]  Kyung-Geun Lee,et al.  Device Centric Throughput and QoS Optimization for IoTsin a Smart Building Using CRN-Techniques , 2016, Sensors.

[31]  Xiaoyuan Li,et al.  Dynamic spectrum access with packet size adaptation and residual energy balancing for energy-constrained cognitive radio sensor networks , 2014, Journal of Network and Computer Applications.

[32]  Kyung-Geun Lee,et al.  CSPA: Channel Selection and Parameter Adaptation scheme based on genetic algorithm for cognitive radio Ad Hoc networks , 2012, EURASIP J. Wirel. Commun. Netw..

[33]  Gyanendra Prasad Joshi,et al.  Cognitive Radio Wireless Sensor Networks: Applications, Challenges and Research Trends , 2013, Sensors.

[34]  Wei Zhang,et al.  Cluster-Based Cooperative Spectrum Sensing in Cognitive Radio Systems , 2007, 2007 IEEE International Conference on Communications.

[35]  Saqib Saleem,et al.  Performance Evaluation of Energy Detection Based Spectrum Sensing Technique for Wireless Channel , 2012 .

[36]  Henk Wymeersch,et al.  Predictive resource allocation evaluation with real channel measurements , 2017, 2017 IEEE International Conference on Communications (ICC).

[37]  Benxiong Huang,et al.  Double Threshold Energy Detection of Cooperative Spectrum Sensing in Cognitive Radio , 2008, 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008).

[38]  Samrat L. Sabat,et al.  FPGA implementation of spectrum sensing based on energy detection for Cognitive Radio , 2010, 2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES.

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

[40]  Fang Liu,et al.  Multiband Detection for Spectrum Sensing: A Multistage Wiener Filter Perspective , 2015, Wirel. Pers. Commun..

[41]  Benoît Champagne,et al.  Wideband Spectrum Sensing for Cognitive Radios With Correlated Subband Occupancy , 2011, IEEE Signal Processing Letters.

[42]  Ian F. Akyildiz,et al.  Optimal spectrum sensing framework for cognitive radio networks , 2008, IEEE Transactions on Wireless Communications.

[43]  R. M. A. P. Rajatheva,et al.  Analysis of Equal Gain Combining in Energy Detection for Cognitive Radio over Nakagami Channels , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[44]  Kyung-Geun Lee,et al.  Fair, efficient, and power-optimized spectrum sharing scheme for cognitive radio networks , 2011, EURASIP J. Wirel. Commun. Netw..

[45]  Hiroshi Harada,et al.  International standardization of cognitive radio systems , 2011, IEEE Communications Magazine.

[46]  Wei Zhang,et al.  Cooperative Spectrum Sensing for Cognitive Radios under Bandwidth Constraints , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[47]  Yan Feng,et al.  Adaptive Multiband Spectrum Sensing , 2012, IEEE Wireless Communications Letters.