{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T10:32:45Z","timestamp":1763202765833,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2023,9,25]],"date-time":"2023-09-25T00:00:00Z","timestamp":1695600000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["9194830"],"award-info":[{"award-number":["9194830"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Realizing the distributed adaptive network construction of multi-UAV networks is an urgent challenge, as they lack a reliable common control channel and can only maintain a limited sensing range in crowded electromagnetic environments. Multi-unmanned aerial vehicle (UAV) networks are gaining popularity in many fields. In order to address these issues, this paper proposes a multi-UAV network channel rendezvous algorithm based on average consistency. The goal of the algorithm is to adjust the communication channels of each UAV to converge on the same channel, since the communication link of the multi-UAV network is broken due to interference. The proposed memory-based average consistency (MAC) algorithm utilizes the network adjacency matrix as prior information. Furthermore, for the case where the adjacency matrix is unknown, this paper also proposes the Multi-Radio Average Consensus (MRAC) algorithm, which achieves a beneficial trade-off between rendezvous performance and hardware cost. Simulation results demonstrate that the proposed MAC and MRAC algorithms provide superior network convergence time and scalability in networks of different densities. Finally, a hardware simulation platform based on a multi-UAV network was designed using a software-defined radio platform, and experimental simulations were performed to prove the effectiveness of the MAC algorithm in a real environment.<\/jats:p>","DOI":"10.3390\/s23198076","type":"journal-article","created":{"date-parts":[[2023,9,26]],"date-time":"2023-09-26T03:45:23Z","timestamp":1695699923000},"page":"8076","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Channel Rendezvous Algorithm for Multi-Unmanned Aerial Vehicle Networks Based on Average Consensus"],"prefix":"10.3390","volume":"23","author":[{"given":"Yunlu","family":"Wang","sequence":"first","affiliation":[{"name":"National Defense Innovation Institute, Fengtai District, No. 53 East Street Courtyard, Beijing 100071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Defense Innovation Institute, Fengtai District, No. 53 East Street Courtyard, Beijing 100071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shan","family":"Qin","sequence":"additional","affiliation":[{"name":"National Defense Innovation Institute, Fengtai District, No. 53 East Street Courtyard, Beijing 100071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinlin","family":"Peng","sequence":"additional","affiliation":[{"name":"National Defense Innovation Institute, Fengtai District, No. 53 East Street Courtyard, Beijing 100071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3340","DOI":"10.1109\/COMST.2019.2924143","article-title":"Design Challenges of Multi-UAV Systems in Cyber-Physical Applications: A Comprehensive Survey and Future Directions","volume":"21","author":"Shakeri","year":"2019","journal-title":"IEEE Commun. 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