{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,9]],"date-time":"2024-11-09T05:24:58Z","timestamp":1731129898460,"version":"3.28.0"},"reference-count":69,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,20]],"date-time":"2024-01-20T00:00:00Z","timestamp":1705708800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010607","name":"University of Perugia","doi-asserted-by":"publisher","award":["Fondo di Ricerca di Base 2022 project Energy-Efficient Networking, Signal Processing and Communications (EFESO)"],"id":[{"id":"10.13039\/501100010607","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021856","name":"Ministero dell'Universit\u00e0 e della Ricerca","doi-asserted-by":"publisher","award":["PRIN 2017 project Liquid Edge Computing Based on Distributed Machine Learning and Millimeter-Wave Radio Access (LIQUID_EDGE)"],"id":[{"id":"10.13039\/501100021856","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"This paper presents a performance analysis of centralized spectrum sensing based on compressed measurements. We assume cooperative sensing, where unlicensed users individually perform compressed sensing and send their results to a fusion center, which makes the final decision about the presence or absence of a licensed user signal. Several cooperation schemes are considered, such as and-rule, or-rule, majority voting, soft equal-gain combining (EGC). The proposed analysis provides simplified closed-form expressions that calculate the required number of sensors, the required number of samples, the required compression ratio, and the required signal-to-noise ratio (SNR) as a function of the probability of detection and the probability of the false alarm of the fusion center and of the sensors. The resulting expressions are derived by exploiting some accurate approximations of the test statistics of the fusion center and of the sensors, equipped with energy detectors. The obtained results are useful, especially for a low number of sensors and low sample sizes, where conventional closed-form expressions based on the central limit theorem (CLT) fail to provide accurate approximations. The proposed analysis also allows the self-computation of the performance of each sensor and of the fusion center with reduced complexity.<\/jats:p>","DOI":"10.3390\/s24020661","type":"journal-article","created":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T16:36:41Z","timestamp":1705941401000},"page":"661","source":"Crossref","is-referenced-by-count":0,"title":["Performance Analysis of Centralized Cooperative Schemes for Compressed Sensing"],"prefix":"10.3390","volume":"24","author":[{"given":"Luca","family":"Rugini","sequence":"first","affiliation":[{"name":"Department of Engineering, University of Perugia, 06125 Perugia, Italy"}]},{"given":"Paolo","family":"Banelli","sequence":"additional","affiliation":[{"name":"Department of Engineering, University of Perugia, 06125 Perugia, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.phycom.2010.12.003","article-title":"Cooperative Spectrum Sensing in Cognitive Radio Networks: A Survey","volume":"4","author":"Akyildiz","year":"2011","journal-title":"Phys. Commun."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"11196","DOI":"10.3390\/s130911196","article-title":"Cognitive Radio Wireless Sensor Networks: Applications, Challenges and Research Trends","volume":"13","author":"Joshi","year":"2013","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1861","DOI":"10.1109\/COMST.2016.2553178","article-title":"Energy-Efficient Cooperative Spectrum Sensing: A Survey","volume":"18","author":"Kliks","year":"2016","journal-title":"IEEE Commun. Surv. Tuts."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1109\/JSTSP.2009.2039178","article-title":"Signal Processing with Compressive Measurements","volume":"4","author":"Davenport","year":"2010","journal-title":"IEEE J. Sel. Topics Signal Process."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4225","DOI":"10.1109\/TSP.2022.3198186","article-title":"Approaching Sub-Nyquist Boundary: Optimized Compressed Spectrum Sensing Based on Multicoset Sampler for Multiband Signal","volume":"70","author":"Song","year":"2022","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1109\/SURV.2009.090109","article-title":"A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications","volume":"11","author":"Yucek","year":"2009","journal-title":"IEEE Commun. Surv. Tuts."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Arjoune, Y., and Kaabouch, N. (2019). A Comprehensive Survey on Spectrum Sensing in Cognitive Radio Networks: Recent Advances, New Challenges, and Future Research Directions. Sensors, 19.","DOI":"10.3390\/s19010126"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Nasser, A., Al Haj Hassan, H., Abou Chaaya, J., Mansour, A., and Yao, K. (2021). Spectrum Sensing for Cognitive Radio: Recent Advances and Future Challenge. Sensors, 21.","DOI":"10.3390\/s21072408"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Lorincz, J., Ramljak, I., and Begu\u0161i\u0107, D. (2021). A Survey on the Energy Detection of OFDM Signals with Dynamic Threshold Adaptation: Open Issues and Future Challenges. Sensors, 21.","DOI":"10.3390\/s21093080"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Men, S., Charg\u00e9, P., and Fu, Z. (2023). Dynamic Robust Spectrum Sensing Based on Goodness-of-Fit Test Using Bilateral Hypotheses. Drones, 7.","DOI":"10.3390\/drones7010018"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Guimar\u00e3es, D. (2023). Modified Gini Index Detector for Cooperative Spectrum Sensing over Line-of-Sight Channels. Sensors, 23.","DOI":"10.3390\/s23125403"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Fernando, X., and L\u0103z\u0103roiu, G. (2023). Spectrum Sensing, Clustering Algorithms, and Energy-Harvesting Technology for Cognitive-Radio-Based Internet-of-Things Networks. Sensors, 23.","DOI":"10.3390\/s23187792"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1109\/MSP.2012.2183771","article-title":"Spectrum Sensing for Cognitive Radio: State-of-the-art and Recent Advances","volume":"29","author":"Axell","year":"2012","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5761","DOI":"10.1109\/TWC.2009.12.081710","article-title":"Optimization of Cooperative Spectrum Sensing with Energy Detection in Cognitive Radio Networks","volume":"8","author":"Zhang","year":"2009","journal-title":"IEEE Trans. Wireless Commun."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1109\/SURV.2013.081313.00054","article-title":"Unveiling the Hidden Assumptions of Energy Detector Based Spectrum Sensing for Cognitive Radios","volume":"16","author":"Umar","year":"2013","journal-title":"IEEE Commun. Surv. Tuts."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1232","DOI":"10.1109\/TWC.2011.012411.100611","article-title":"Energy Detection Based Cooperative Spectrum Sensing in Cognitive Radio Networks","volume":"10","author":"Atapattu","year":"2011","journal-title":"IEEE Trans. Wireless Commun."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1678","DOI":"10.1109\/LCOMM.2015.2466105","article-title":"Approximations for Performance of Energy Detector and p-norm Detector","volume":"19","author":"Banjade","year":"2015","journal-title":"IEEE Commun. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1109\/TCOMM.2015.2394436","article-title":"Energy Detection Technique for Adaptive Spectrum Sensing","volume":"63","author":"Sobron","year":"2015","journal-title":"IEEE Trans. Commun."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1109\/LWC.2015.2457895","article-title":"Performance Analysis of Cooperative Spectrum Sensing Over \u03ba-\u03bc Shadowed Fading","volume":"4","author":"Chandrasekaran","year":"2015","journal-title":"IEEE Wireless Commun. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Lesnikov, V., Naumovich, T., Chastikov, A., and Dubovcev, D. (2016, January 14\u201317). Approximation of the Central Chi-Squared Distribution for On-Line Computation of the Threshold for Energy Detector. Proceedings of the 2016 IEEE East\u2013West Design and Test Symposium (EWDTS), Yerevan, Armenia.","DOI":"10.1109\/EWDTS.2016.7807710"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lesnikov, V., Naumovich, T., and Chastikov, A. (October, January 29). Computation of the Energy Detector Threshold for Various Approximations of Noise Power Distribution. Proceedings of the 2017 IEEE East\u2013West Design and Test Symposium (EWDTS), Novi Sad, Serbia.","DOI":"10.1109\/EWDTS.2017.8110033"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Sobron, I., Eizmendi, I., Martins, W., Diniz, P., Ordiales, J., and Velez, M. (2017). Implementation Issues of Adaptive Energy Detection in Heterogeneous Wireless Networks. Sensors, 17.","DOI":"10.3390\/s17040932"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.aeue.2017.05.026","article-title":"Performance Analysis of Cooperative Spectrum Sensing over Large and Small Scale Fading Channels","volume":"78","author":"Li","year":"2017","journal-title":"AE\u00dc Intl. J. Electron. Commun."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.aeue.2018.07.014","article-title":"A Unified Performance Analysis of Energy Detector over \u03b1-\u03b7-\u03bc\/Lognormal and \u03b1-\u03ba-\u03bc\/Lognormal Composite Fading Channels with Diversity and Cooperative Spectrum Sensing","volume":"94","author":"Bhatt","year":"2018","journal-title":"AE\u00dc Intl. J. Electron. Commun."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Cao, K., Qian, P., An, J., and Wang, L. (2020). Accurate and Practical Energy Detection over \u03b1-\u03bc Fading Channels. Sensors, 20.","DOI":"10.3390\/s20030754"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Lopez-Benitez, M., Toma, O.H., Patel, D.K., and Umebayashi, K. (2020, January 25\u201328). Sample Size Analysis of Energy Detection under Fading Channels. Proceedings of the 2020 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), Seoul, Republic of Korea.","DOI":"10.1109\/WCNCW48565.2020.9124845"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Lorincz, J., Ramljak, I., and Begu\u0161i\u0107, D. (2021). Algorithm for Evaluating Energy Detection Spectrum Sensing Performance of Cognitive Radio MIMO-OFDM Systems. Sensors, 21.","DOI":"10.3390\/s21206881"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1109\/JSAC.2013.130304","article-title":"Censored Truncated Sequential Spectrum Sensing for Cognitive Radio Networks","volume":"31","author":"Maleki","year":"2013","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.phycom.2012.07.003","article-title":"Optimization of Hard Fusion Based Spectrum Sensing for Energy-Constrained Cognitive Radio Networks","volume":"9","author":"Maleki","year":"2013","journal-title":"Phys. Commun."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1242","DOI":"10.1109\/TCOMM.2013.13.110594","article-title":"Generalized Mean Detector for Collaborative Spectrum Sensing","volume":"61","author":"Shakir","year":"2013","journal-title":"IEEE Trans. Commun."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"4334","DOI":"10.1109\/TWC.2014.2317788","article-title":"Equal Gain Combining for Cooperative Spectrum Sensing in Cognitive Radio Networks","volume":"13","author":"Hamza","year":"2014","journal-title":"IEEE Trans. Wireless Commun."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.dsp.2015.04.007","article-title":"A Novel Multistage Decision Fusion for Cognitive Sensor Networks Using AND and OR Rules","volume":"42","author":"Gupta","year":"2015","journal-title":"Digital Signal Process."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1007\/s11277-015-2666-x","article-title":"Globally Optimal Cooperation in Dense Cognitive Radio Networks","volume":"84","author":"Alaa","year":"2015","journal-title":"Wireless Pers. Commun."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Duan, M., Zeng, Z., Guo, C., and Liu, F. (2015, January 2\u20134). User Selection for Cooperative Spectrum Sensing in Mobile Cognitive Radios. Proceedings of the 2015 IEEE\/CIC International Conference on Communications in China (ICCC), Shenzhen, China.","DOI":"10.1109\/ICCChina.2015.7448595"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"4388","DOI":"10.3390\/s150204388","article-title":"A Soft-Hard Combination-Based Cooperative Spectrum Sensing Scheme for Cognitive Radio Networks","volume":"15","author":"Do","year":"2015","journal-title":"Sensors"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1007\/s11277-016-3645-6","article-title":"Information Combining Schemes for Cooperative Spectrum Sensing: A Survey and Comparative Performance Analysis","volume":"94","author":"Pradhan","year":"2017","journal-title":"Wireless Pers. Commun."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1871","DOI":"10.1007\/s11277-017-4273-5","article-title":"Cooperative Spectrum Sensing with Small Sample Size in Cognitive Wireless Sensor Networks","volume":"96","author":"Men","year":"2017","journal-title":"Wireless Pers. Commun."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Aquino, G., Guimar\u00e3es, D., Mendes, L., and Pimenta, T. (2017). Combined Pre-Distortion and Censoring for Bandwidth-Efficient and Energy-Efficient Fusion of Spectrum Sensing Information. Sensors, 17.","DOI":"10.3390\/s17030654"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Fu, Y., Yang, F., and He, Z. (2018). A Quantization-Based Multibit Data Fusion Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks. Sensors, 18.","DOI":"10.3390\/s18020473"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Qian, X., Hao, L., Ni, D., and Tran, Q. (2018). Hard Fusion Based Spectrum Sensing over Mobile Fading Channels in Cognitive Vehicular Networks. Sensors, 18.","DOI":"10.3390\/s18020475"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2726","DOI":"10.1109\/TWC.2018.2801833","article-title":"Cooperative Spectrum Sensing: A Blind and Soft Fusion Detector","volume":"17","author":"Tong","year":"2018","journal-title":"IEEE Trans. Wireless Commun."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Costa, L., Guimar\u00e3es, D., De Souza, R., and Bomfin, R. (2019). Cooperative Spectrum Sensing with Coded and Uncoded Decision Fusion under Correlated Shadowed Fading Report Channels. Sensors, 19.","DOI":"10.3390\/s19010051"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Liu, S., Wang, K., Liu, K., and Chen, W. (2019). Noncoherent Decision Fusion over Fading Hybrid MACs in Wireless Sensor Networks. Sensors, 19.","DOI":"10.3390\/s19010120"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Mi, Y., Lu, G., Li, Y., and Bao, Z. (2019). A Novel Semi-Soft Decision Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks. Sensors, 19.","DOI":"10.3390\/s19112522"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3315","DOI":"10.1109\/TVT.2021.3139126","article-title":"Fusion Test Statistics Based Mixture Detector for Spectrum Sensing","volume":"71","author":"Luo","year":"2022","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"104006","DOI":"10.1016\/j.dsp.2023.104006","article-title":"A Geodesic Projection-Based Data Fusion Scheme for Cooperative Spectrum Sensing","volume":"137","author":"Wang","year":"2023","journal-title":"Digital Signal Process."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"104215","DOI":"10.1016\/j.dsp.2023.104215","article-title":"Siegel Distance-Based Fusion Strategy and Differential Evolution Algorithm for Cooperative Spectrum Sensing","volume":"142","author":"Zhuang","year":"2023","journal-title":"Digital Signal Process."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"5251","DOI":"10.3390\/s130405251","article-title":"Optimal Periodic Cooperative Spectrum Sensing Based on Weight Fusion in Cognitive Radio Networks","volume":"13","author":"Liu","year":"2013","journal-title":"Sensors"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"8037","DOI":"10.3390\/s140508037","article-title":"Cooperative Spectrum Sensing Schemes with the Interference Constraint in Cognitive Radio Networks","volume":"14","author":"Do","year":"2014","journal-title":"Sensors"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1861","DOI":"10.3390\/s150101861","article-title":"Resource-Efficient Fusion over Fading and Non-Fading Reporting Channels for Cooperative Spectrum Sensing","volume":"15","author":"Aquino","year":"2015","journal-title":"Sensors"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"10891","DOI":"10.3390\/s150510891","article-title":"Resource-Efficient Fusion with Pre-Compensated Transmissions for Cooperative Spectrum Sensing","volume":"15","author":"Aquino","year":"2015","journal-title":"Sensors"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Banavathu, N.R., and Khan, M.Z.A. (May, January 28). On Throughput Maximization of Cooperative Spectrum Sensing Using the M-out-of-K Rule. Proceedings of the IEEE 89th Vehicular Technology Conference (VTC2019-Spring), Kuala Lumpur, Malaysia.","DOI":"10.1109\/VTCSpring.2019.8746391"},{"key":"ref_53","unstructured":"Abramowitz, M., and Stegun, I.A. (1972). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, Dover."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1080\/01621459.1956.10501329","article-title":"On Approximating the Point Binomial","volume":"51","author":"Raff","year":"1956","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1638","DOI":"10.1080\/01621459.1969.10501083","article-title":"Some Numerical Comparisons of Several Approximations to the Binomial Distribution","volume":"64","author":"Gebhardt","year":"1969","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1214\/aoms\/1177731945","article-title":"Note on an Approximate Formula for the Significance Levels of z","volume":"11","author":"Cochran","year":"1940","journal-title":"Ann. Math. Stat."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"151","DOI":"10.2307\/2332208","article-title":"Tables of Percentage Points of the Incomplete Beta-Function","volume":"32","author":"Thompson","year":"1941","journal-title":"Biometrika"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1093\/biomet\/34.3-4.352","article-title":"Approximation to Percentage Points of the z-Distribution","volume":"34","author":"Carter","year":"1947","journal-title":"Biometrika"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1093\/biomet\/37.3-4.219","article-title":"On the Levels of Significance of the Incomplete Beta Function and the F-Distributions","volume":"37","author":"Aroian","year":"1950","journal-title":"Biometrika"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1073\/pnas.17.12.684","article-title":"The Distribution of Chi-Square","volume":"17","author":"Wilson","year":"1931","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1080\/00031305.1986.10475420","article-title":"A Note on the Transformation of Chi-Squared Variables to Normality","volume":"40","author":"Hawkins","year":"1986","journal-title":"Amer. Stat."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1111\/j.1467-842X.1992.tb01043.x","article-title":"On the Fourth Root Transformation of Chi-Square","volume":"34","author":"Goria","year":"1992","journal-title":"Austral. J. Stat."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1016\/j.csda.2004.04.001","article-title":"A Normal Approximation for the Chi-Square Distribution","volume":"48","author":"Canal","year":"2005","journal-title":"Computat. Stat. Data Analysis"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1814","DOI":"10.1109\/LCOMM.2013.080813.131399","article-title":"Small Sample Size Performance of the Energy Detector","volume":"17","author":"Rugini","year":"2013","journal-title":"IEEE Commun. Lett."},{"key":"ref_65","unstructured":"Rugini, L., Banelli, P., and Leus, G. (September, January 28). Spectrum Sensing Using Energy Detectors with Performance Computation Capabilities. Proceedings of the 24th European Signal Processing Conference (EUSIPCO), Budapest, Hungary."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Lagunas, E., and Rugini, L. (2017, January 8\u201313). Performance of Compressive Sensing Based Energy Detection. Proceedings of the IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Montreal, QC, Canada.","DOI":"10.1109\/PIMRC.2017.8292460"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Maleki, S., Chepuri, S.P., and Leus, G. (2011, January 26\u201329). Energy and Throughput Efficient Strategies for Cooperative Spectrum Sensing in Cognitive Radios. Proceedings of the IEEE 12th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), San Francisco, CA, USA.","DOI":"10.1109\/SPAWC.2011.5990482"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1109\/TCCN.2019.2903503","article-title":"Energy-Spectrum Efficiency Trade-Off in Energy Harvesting Cooperative Cognitive Radio Networks","volume":"5","author":"Chatterjee","year":"2019","journal-title":"IEEE Trans. Cognitive Commun. Netw."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"2078","DOI":"10.1109\/JSYST.2021.3123463","article-title":"QoE-Aware Cross-Layer Adaptation for D2D Video Communication in Cooperative Cognitive Radio Networks","volume":"16","author":"Chatterjee","year":"2022","journal-title":"IEEE Syst. J."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/2\/661\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,8]],"date-time":"2024-11-08T21:11:23Z","timestamp":1731100283000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/2\/661"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,20]]},"references-count":69,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["s24020661"],"URL":"https:\/\/doi.org\/10.3390\/s24020661","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2024,1,20]]}}}