{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T00:08:08Z","timestamp":1766966888207,"version":"3.48.0"},"reference-count":32,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T00:00:00Z","timestamp":1766707200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union\u2014Next Generation EU under the Italian National Recovery and Resilience Plan (NRRP), Mission 4, Component 2, Investment 1.3","award":["CUP B83C22004870007"],"award-info":[{"award-number":["CUP B83C22004870007"]}]},{"name":"Telecommunications of the Future","award":["PE00000001"],"award-info":[{"award-number":["PE00000001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>The integration of terrestrial and aerial components in future wireless networks is a key enabler for achieving wide-area coverage and providing ubiquitous services. In this context, and with the goal of enhancing spectral efficiency through opportunistic spectrum reuse, this paper investigates a cooperative spectrum sensing approach in which cognitive UAVs equipped with full-duplex (FD) MIMO technology operate as aerial base stations (ABS). Each UAV performs local detection using the sphericity test, then a push\u2013sum consensus protocol is employed to fuse local test statistics without relying on a fusion center. Unlike conventional unweighted consensus or centralized hard-decision fusion, the proposed approach accounts for the heterogeneity introduced by residual self-interference in FD transceivers. Specifically, multipath in the self-interference channel induces temporal correlation, increasing the variance of the local test statistic and, consequently, the false-alarm probability. To mitigate this effect, we design variance-aware consensus weights proportional to the inverse of the sphericity test variance enhancing robustness to RSI-induced variability. Numerical results demonstrate that the proposed scheme outperforms both unweighted consensus and centralized OR-rule fusion in user capacity, while maintaining negligible communication overhead. Moreover, the operational altitude of the UAVs is evaluated to balance the coverage provided to users and the primary signal detection capability.<\/jats:p>","DOI":"10.3390\/fi18010010","type":"journal-article","created":{"date-parts":[[2025,12,28]],"date-time":"2025-12-28T23:54:36Z","timestamp":1766966076000},"page":"10","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Distributed Cooperative Spectrum Sensing via Push\u2013Sum Consensus for Full-Duplex Cognitive Aerial Base Stations"],"prefix":"10.3390","volume":"18","author":[{"given":"Andrea","family":"Tani","sequence":"first","affiliation":[{"name":"Department of Information Engineering, University of Florence, Via di S. Marta, 3, 50139 Florence, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7075-3556","authenticated-orcid":false,"given":"Dania","family":"Marabissi","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Florence, Via di S. Marta, 3, 50139 Florence, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Gupta, A., Gupta, S.K., Rashid, M., Khan, A., and Manjul, M. (2022). Unmanned aerial vehicles integrated HetNet for smart dense urban area. Trans. Emerg. Telecommun. Technol., 33.","DOI":"10.1002\/ett.4123"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Tani, A., and Marabissi, D. (2023, January 2\u20134). Adaptive blind spectrum sensing for mmWave full duplex cognitive aerial BS. Proceedings of the European Wireless 2023\u201428th European Wireless Conference, Rome, Italy.","DOI":"10.36227\/techrxiv.170327222.23350804\/v1"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4117","DOI":"10.1109\/JIOT.2022.3230786","article-title":"Unmanned-aerial-vehicle-assisted wireless networks: Advancements, challenges, and solutions","volume":"10","author":"Dai","year":"2023","journal-title":"IEEE Internet Things J."},{"key":"ref_4","unstructured":"Zhou, S., Xiang, L., Yang, K., Wong, K.K., Wu, D.O., and Chae, C.B. (2025). Beamforming-based achievable rate maximization in ISAC system for multi-UAV networking. arXiv."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2303","DOI":"10.1109\/TCCN.2024.3520126","article-title":"Low-Complexity Adaptive Blind Spectrum Sensing for mmWave Full Duplex Cognitive Radio over Time-Varying Channels","volume":"11","author":"Tani","year":"2024","journal-title":"IEEE Trans. Cogn. Commun. Netw."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1109\/TWC.2022.3198665","article-title":"When UAVs meet cognitive radio: Offloading traffic under uncertain spectrum environment via deep reinforcement learning","volume":"22","author":"Li","year":"2023","journal-title":"IEEE Trans. Wireless Commun."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1109\/TCCN.2025.3571916","article-title":"UAV Covert Communications in Interweave Cognitive Radio Network","volume":"12","author":"Wei","year":"2026","journal-title":"IEEE Trans. Cogn. Commun. Netw."},{"key":"ref_8","first-page":"1","article-title":"Efficient cooperative spectrum sensing in UAV-assisted cognitive wireless sensor networks","volume":"8","author":"Liang","year":"2024","journal-title":"IEEE Sens. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Sboui, L., Ghazzai, H., and Massoud, Y. (2022, January 16\u201318). Integrating Cognitive Radio MIMO UAVs in Cellular Networks for 5G and Beyond. Proceedings of the 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), Mal\u00e9, Maldives.","DOI":"10.1109\/ICECCME55909.2022.9988381"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2259","DOI":"10.1049\/iet-com.2019.1158","article-title":"Multi-cycle spectrum sensing for OFDM signals under cyclic frequency offsets in cognitive vehicular networks","volume":"14","author":"Tani","year":"2020","journal-title":"IET Commun."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1109\/TCCN.2021.3085769","article-title":"Cooperative Sensing With Heterogeneous Spectrum Availability in Cognitive Radio","volume":"8","author":"Wu","year":"2022","journal-title":"IEEE Trans. Cogn. Commun. Netw."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.1109\/TAC.2019.2929206","article-title":"Push-Sum on Random Graphs: Almost Sure Convergence and Convergence Rate","volume":"65","author":"Rezaeinia","year":"2020","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/TPDS.2014.2307951","article-title":"Distributed Consensus-Based Weight Design for Cooperative Spectrum Sensing","volume":"26","author":"Zhang","year":"2015","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zhang, H., Da, X., and Hu, H. (2019, January 15\u201317). Multi-UAV cooperative spectrum sensing in cognitive UAV network. Proceedings of the 5th International Conference on Communication and Information Processing, Chongqing, China.","DOI":"10.1145\/3369985.3370014"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Moliya, R., Patel, D.K., L\u00f3pez-Ben\u00edtez, M., and Fakhrcddine, A. (2025, January 6\u20139). Optimizing UAV Deployment for Enhanced Detection Performance in Multi-UAV Cooperative Sensing. Proceedings of the 2025 National Conference on Communications (NCC), New Delhi, India.","DOI":"10.1109\/NCC63735.2025.10983909"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1109\/JPROC.2024.3366768","article-title":"In-Band Full-Duplex: The Physical Layer","volume":"112","author":"Smida","year":"2024","journal-title":"Proc. IEEE"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1109\/COMST.2017.2773628","article-title":"Dynamic spectrum sharing in 5G wireless networks with full-duplex technology: Recent advances and research challenges","volume":"20","author":"Sharma","year":"2018","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2158","DOI":"10.1109\/COMST.2017.2718618","article-title":"Full-duplex communication in cognitive radio networks: A survey","volume":"19","author":"Amjad","year":"2017","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Tian, L., Shi, C., and Xu, Z. (2023). Digital Self-Interference Cancellation for Full-Duplex UAV Communication System over Time-Varying Channels. Drones, 7.","DOI":"10.3390\/drones7030151"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"9776","DOI":"10.1109\/JIOT.2020.3019065","article-title":"Joint optimization of UAV 3-D placement and path-loss factor for energy-efficient maximal coverage","volume":"8","author":"Shakoor","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"7796","DOI":"10.1109\/TWC.2020.3016024","article-title":"3D UAV trajectory design and frequency band allocation for energy-efficient and fair communication: A deep reinforcement learning approach","volume":"19","author":"Ding","year":"2020","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1109\/TCOMM.2017.2746105","article-title":"Ultra Reliable UAV Communication Using Altitude and Cooperation Diversity","volume":"66","author":"Azari","year":"2018","journal-title":"IEEE Trans. Commun."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Kim, M., and Lee, J. (2018, January 9\u201313). Outage Probability of UAV Communications in the Presence of Interference. Proceedings of the 2018 IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, United Arab Emirates.","DOI":"10.1109\/GLOCOM.2018.8647521"},{"key":"ref_24","unstructured":"3GPP (2020). Study on Channel Model for Frequencies from 0.5 to 100 GHz, ETSI. 3GPP TR 38.901, v16.1.0, Release 16."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Farasat, M., Thalakotuna, D.N., Hu, Z., and Yang, Y. (2021). A Review on 5G Sub-6 GHz Base Station Antenna Design Challenges. Electronics, 10.","DOI":"10.3390\/electronics10162000"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Alexandris, K., Balatsoukas-Stimming, A., and Burg, A. (2014, January 22\u201325). Measurement-based characterization of residual self-interference on a full-duplex MIMO testbed. Proceedings of the 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM), A Coruna, Spain.","DOI":"10.1109\/SAM.2014.6882408"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"6864","DOI":"10.1109\/TVT.2022.3164058","article-title":"Multiantenna Spectrum Sensing for Correlated Signal in Spatially Correlated Noise Environments","volume":"71","author":"Chen","year":"2022","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.1109\/TCCN.2024.3460758","article-title":"Large Array Antenna Spectrum Sensing in Cognitive Radio Networks","volume":"11","author":"Taherpour","year":"2025","journal-title":"IEEE Trans. Cogn. Commun. Netw."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Chen, S., Shen, B., Wang, X., and Yoo, S.-J. (2020). Geo-Location Information Aided Spectrum Sensing in Cellular Cognitive Radio Networks. Sensors, 20.","DOI":"10.3390\/s20010213"},{"key":"ref_30","first-page":"2412","article-title":"Distributed averaging with packet losses","volume":"67","author":"Paschalidis","year":"2022","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"4296","DOI":"10.1109\/TWC.2012.102612.111278","article-title":"Experiment-Driven Characterization of Full-Duplex Wireless Systems","volume":"11","author":"Duarte","year":"2012","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zeng, T., Semiari, O., Mozaffari, M., Chen, M., Saad, W., and Bennis, M. (2020, January 7\u201311). Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms. Proceedings of the 2020 IEEE International Conference on Communications (ICC), Dublin, Ireland.","DOI":"10.1109\/ICC40277.2020.9148776"}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/18\/1\/10\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T00:04:51Z","timestamp":1766966691000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/18\/1\/10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,26]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["fi18010010"],"URL":"https:\/\/doi.org\/10.3390\/fi18010010","relation":{},"ISSN":["1999-5903"],"issn-type":[{"value":"1999-5903","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,26]]}}}