Enhancing the Spectrum Sensing Performance of Cluster-Based Cooperative Cognitive Radio Networks via Sequential Multiple Reporting Channels

In cluster-based cooperative cognitive radio networks (CCRNs), spectrum sensing and decision making processes to determine whether the primary user (PU) signal is present or absent in the network are very important and vital issues to the utilisation of the idle spectrum. The reporting time delay is a very important matter to make quick and effective global decisions for the fusion center (FC) in a cluster-based CCRNs. In this paper, we propose the concept of multiple reporting channels (MRC) for cluster-based CCRNs to better utilize the reporting time slot by extending the sensing time of secondary users (SUs). A multiple reporting channels concept is proposed based on frequency division multiple access to enhance the spectrum sensing performance and reduce the reporting time delay of all cluster heads (CHs). In this approach, we assign an individual reporting channel to each cluster for reporting purposes. All the SUs in each cluster sequentially pass their sensing results to the corresponding cluster head (CH) via the assigned single reporting channel, which extends the sensing time duration of SUs. Each CH uses the dedicated reporting channel to forward the cluster decision to the FC that makes a final decision by using the “K-out-of-N” rule to identify the presence of the PU signal. This approach significantly enhances the sensing time for all SUs than the non-sequential as well as minimize the reporting time delay of all CHs than sequential single channel reporting approach. These two features of our proposed approach increase the decision accuracy of the FC more than the conventional approach. Simulation results prove that our proposed approach significantly enhances the sensing accuracy and mitigate the reporting time delay of CH compared to the conventional approach.

[1]  Sumit Kundu,et al.  Defense Against Spectrum Sensing Data Falsification Attacker in Cognitive Radio Networks , 2020, Wirel. Pers. Commun..

[2]  Insoo Koo,et al.  Reliable Machine Learning Based Spectrum Sensing in Cognitive Radio Networks , 2018, Wirel. Commun. Mob. Comput..

[3]  Mehmet Bilim Some New Results for Integrals Involving Gaussian Q-function and Their Applications to α-µ and η-µ Fading Channels , 2019, Wirel. Pers. Commun..

[4]  Mostafa Zaman Chowdhury,et al.  On demand cell sectoring based fractional frequency reuse in wireless networks , 2014, 2014 9th International Forum on Strategic Technology (IFOST).

[5]  Enda Barrett,et al.  Sensing and throughput analysis of a MU-MIMO based cognitive radio scheme for the Internet of Things , 2020, Comput. Commun..

[6]  Bin Li,et al.  A Novel Spectrum Sensing for Cognitive Radio Networks With Noise Uncertainty , 2017, IEEE Transactions on Vehicular Technology.

[7]  Jorge Torres,et al.  Blind Spectrum Sensing Based on Cyclostationary Feature Detection , 2015, CIARP.

[8]  Garima Mahendru,et al.  A Novel Mathematical Model for Energy Detection Based Spectrum Sensing in Cognitive Radio Networks , 2020, Wirel. Pers. Commun..

[9]  Naixue Xiong,et al.  Dynamic dual threshold cooperative spectrum sensing for cognitive radio under noise power uncertainty , 2019, Human-centric Computing and Information Sciences.

[10]  YauKok-Lim Alvin,et al.  Clustering algorithms for Cognitive Radio networks , 2014 .

[11]  Daniela Mercedes Martínez Plata,et al.  Evaluation of energy detection for spectrum sensing based on the dynamic selection of detection-threshold , 2012 .

[12]  K. S. Vishvaksenan,et al.  Coded downlink MIMO MC-CDMA system for cognitive radio network: performance results , 2018, Cluster Computing.

[13]  Guoyin Zhang,et al.  Cross-layer parallel cooperative spectrum sensing for heterogeneous channels based on iterative KM algorithm , 2019, Cluster Computing.

[14]  Serdar Sezginer,et al.  Full Frequency Reuse in OFDMA-Based Wireless Networks with Sectored Cells , 2009, 2009 IEEE Wireless Communications and Networking Conference.

[15]  Fabrizio Granelli,et al.  Optimizing the K-out-of-N rule for cooperative spectrum sensing in cognitive radio networks , 2013, 2013 IEEE Global Communications Conference (GLOBECOM).

[16]  Erry Gunawan,et al.  Improper Gaussian signaling for the K-user SISO interference channel , 2013, 2013 IEEE International Conference on Communications (ICC).

[17]  B. Suseela,et al.  Non-cooperative spectrum sensing techniques in cognitive radio-a survey , 2015, 2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR).

[18]  Caijun Zhong,et al.  On the Performance of Eigenvalue-Based Cooperative Spectrum Sensing for Cognitive Radio , 2011, IEEE Journal of Selected Topics in Signal Processing.

[19]  P. Venkatesan,et al.  Group Based Multi-Channel Synchronized Spectrum Sensing in Cognitive Radio Network with 5G , 2018, Mobile Networks and Applications.

[20]  Debasish Bera,et al.  Modelling of Cooperative Spectrum Sensing over Rayleigh Fading Without CSI in Cognitive Radio Networks , 2016, Wirel. Pers. Commun..

[21]  Md Mahbubur Rahman,et al.  An Eigenvalue and superposition approach based cooperative spectrum sensing in cognitive radio networks , 2014, 2014 International Conference on Electrical Engineering and Information & Communication Technology.

[22]  Chhagan Charan,et al.  Two stage spectrum sensing for cognitive radio networks using ED and AIC under noise uncertainty , 2016, 2016 International Conference on Recent Trends in Information Technology (ICRTIT).

[23]  Mahmoud A. Smadi,et al.  Exact Error Rate Analysis of MIMO-MRC System under Cochannel Interference and Imperfect Channel State Information , 2014, Wirel. Pers. Commun..

[24]  Manobendu Sarker Energy detector based spectrum sensing by adaptive threshold for low SNR in CR networks , 2015, 2015 24th Wireless and Optical Communication Conference (WOCC).

[25]  Zhai Xuping,et al.  Energy-detection based spectrum sensing for cognitive radio , 2007 .

[26]  Md. Khairul Islam,et al.  Automatic Human Brain Tumor Detection in MRI Image Using Template-Based K Means and Improved Fuzzy C Means Clustering Algorithm , 2019, Big Data Cogn. Comput..

[27]  Santi P. Maity,et al.  On optimal fuzzy c-means clustering for energy efficient cooperative spectrum sensing in cognitive radio networks , 2016, Digit. Signal Process..

[28]  K. Kalimuthu,et al.  An adaptive decision threshold scheme for the matched filter method of spectrum sensing in cognitive radio using artificial neural networks , 2016, 2016 1st India International Conference on Information Processing (IICIP).

[29]  Hong Wen,et al.  Adaptive Threshold Control for Energy Detection Based Spectrum Sensing in Cognitive Radios , 2012, IEEE Wireless Communications Letters.

[30]  Walaa Hamouda,et al.  Advances on Spectrum Sensing for Cognitive Radio Networks: Theory and Applications , 2017, IEEE Communications Surveys & Tutorials.

[31]  Heejung Yu,et al.  Enhanced Sensing and Sum-Rate Analysis in a Cognitive Radio-Based Internet of Things , 2020, Sensors.

[32]  Ramanarayanan Viswanathan,et al.  A Review of Cooperative Spectrum Sensing in Cognitive Radios , 2013 .

[33]  Wahidah Hashim,et al.  Clustering algorithms for Cognitive Radio networks: A survey , 2014, J. Netw. Comput. Appl..

[34]  Umesh Chandra Samal,et al.  Sensing performance of energy detector in cognitive radio networks , 2019 .

[35]  Rajesh Kumar,et al.  Realisation of a cluster-based protocol using fuzzy C-means algorithm for wireless sensor networks , 2013, IET Wirel. Sens. Syst..

[36]  M. A. Bhagyaveni,et al.  A Method to Enhance the Throughput of Cognitive Radio Network Using Kullback Leibler Divergence with Optimized Sensing Time (KLDOST) , 2019, Wireless Personal Communications.

[37]  Hatem Boujemaa,et al.  Multihop Multibranch Spectrum Sensing for Cognitive Radio Networks , 2018 .

[38]  Ranjan K. Mallik,et al.  Cooperative Spectrum Sensing in Multiple Antenna Based Cognitive Radio Network Using an Improved Energy Detector , 2012, IEEE Communications Letters.

[39]  Rahul Shrestha,et al.  Cognitive-radio wireless-sensor based on energy detection with improved accuracy: Performance and hardware perspectives , 2016, 2016 20th International Symposium on VLSI Design and Test (VDAT).

[40]  Fadel F. Digham,et al.  Distributed Spectrum Sensing With Sequential Ordered Transmissions to a Cognitive Fusion Center , 2011, IEEE Transactions on Signal Processing.

[41]  Daeyoung Park,et al.  Coordinating transmit power and carrier phase for wireless networks with multi-packet reception capability , 2013, EURASIP J. Wirel. Commun. Netw..

[42]  M. Satya Sai Ram,et al.  Optimization of cooperative secondary users in cognitive radio networks , 2018 .

[43]  Mahbubur Rahman,et al.  Unscented Kalman Filter Based on Spectrum Sensing in a Cognitive Radio Network Using an Adaptive Fuzzy System , 2018, Big Data Cogn. Comput..

[44]  Sanjay Dhar Roy,et al.  Cooperative Spectrum Sensing with Double Threshold and Censoring in Rayleigh Faded Cognitive Radio Network , 2015, Wirel. Pers. Commun..

[45]  S.K. Panda,et al.  Fuzzy C-Means clustering protocol for Wireless Sensor Networks , 2010, 2010 IEEE International Symposium on Industrial Electronics.

[46]  Venkatesan Perumal,et al.  Group Based Multi-Channel Synchronized Spectrum Sensing in Cognitive Radio Network with 5G , 2019, Mob. Networks Appl..

[47]  Enda Barrett,et al.  An enhanced sum rate in the cluster based cognitive radio relay network using the sequential approach for the future Internet of Things , 2018, Hum. centric Comput. Inf. Sci..

[48]  Nhan Nguyen-Thanh,et al.  A cluster-based selective cooperative spectrum sensing scheme in cognitive radio , 2013, EURASIP J. Wirel. Commun. Netw..

[49]  Kai Yang,et al.  A Blind Spectrum Sensing Method Based on Deep Learning , 2019, Sensors.

[50]  Rupali B. Patil,et al.  SDR Based Energy Detection Spectrum Sensing in Cognitive Radio for Real Time Video Transmission , 2018 .

[51]  Santi P. Maity,et al.  Fuzzy C-Means Clustering in Energy Detection for Cooperative Spectrum Sensing in Cognitive Radio System , 2014, MACOM.

[52]  Hong-Fang Yu,et al.  Throughput-Delay Trade-Off for Cognitive Radio Networks: A Convex Optimization Perspective , 2014 .

[53]  Enda Barrett,et al.  Enhancing the Spectrum Utilization in Cellular Mobile Networks by Using Cognitive Radio Technology , 2019, 2019 30th Irish Signals and Systems Conference (ISSC).

[54]  Bub-Joo Kang,et al.  Spectrum sensing issues in cognitive radio networks , 2009, 2009 9th International Symposium on Communications and Information Technology.

[55]  Sangarapillai Lambotharan,et al.  Cooperative spectrum sensing in cognitive radio networks using multi-class support vector machine algorithms , 2015, 2015 9th International Conference on Signal Processing and Communication Systems (ICSPCS).

[56]  Marcharla Anjaneyulu Bhagyaveni,et al.  Energy Efficient Cognitive Radio Sensor Networks with Team-Based Hybrid Sensing , 2019, Wireless Personal Communications.

[57]  Ahmed Tamtaoui,et al.  Spectrum sensing: Enhanced energy detection technique based on noise measurement , 2018, 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC).

[58]  Nasir Saeed,et al.  Fuzzy C-Means Clustering and Energy Efficient Cluster Head Selection for Cooperative Sensor Network , 2016, Sensors.

[59]  Enda Barrett,et al.  Maximization of sum rate in AF-cognitive radio networks using superposition approach and n-out-of-k rule , 2017, 2017 28th Irish Signals and Systems Conference (ISSC).