{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T05:04:25Z","timestamp":1764997465803,"version":"build-2065373602"},"reference-count":16,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,5,5]],"date-time":"2022-05-05T00:00:00Z","timestamp":1651708800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Institute of Radiocommunications","award":["0312\/SBAD\/8161"],"award-info":[{"award-number":["0312\/SBAD\/8161"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Bearing in mind the stringent problem of limited and inefficiently used radio resources, a multi-source mechanism for the dynamic adjustment of occupied frequency bands is proposed. Instead of relying only on radio-related information, the system that collects data from various sources is discussed. Mainly, using the ubiquitous sources of information about the presence of users (such as city monitoring), it is possible to identify areas that have high or low expected traffic with high probabilities. Consequently, in low-traffic areas, it is not necessary to allocate all available spectrum resources while maintaining the quality of service. This leads to the improved spectral efficiency of the network. As the level of trust in certain information sources may differ among various operators, we propose to implement such functionality in the form of an application. Our contribution is a proposal for an algorithm that limits the use of radio resources through fuzzy and soft connections of multiple sources of contextual information. The simulation results presented in this paper show that it is possible to reduce the spectrum used with a slight and simultaneous reduction in user bitrate, which increases the spectral efficiency of the entire system. Hence, following the concept of an open radio access network, various policies for information merging may be specified.<\/jats:p>","DOI":"10.3390\/s22093515","type":"journal-article","created":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T02:46:39Z","timestamp":1651805199000},"page":"3515","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Dynamic Spectrum Allocation Using Multi-Source Context Information in OpenRAN Networks"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3434-1917","authenticated-orcid":false,"given":"\u0141ukasz","family":"Ku\u0142acz","sequence":"first","affiliation":[{"name":"Institute of Radiocommunications, Poznan University of Technology, 60-965 Poznan, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6766-7836","authenticated-orcid":false,"given":"Adrian","family":"Kliks","sequence":"additional","affiliation":[{"name":"Institute of Radiocommunications, Poznan University of Technology, 60-965 Poznan, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"92","DOI":"10.23919\/JCC.2020.09.008","article-title":"Vision, requirements and network architecture of 6G mobile network beyond 2030","volume":"17","author":"Liu","year":"2020","journal-title":"China Commun."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/OJVT.2020.3044569","article-title":"6G Massive Radio Access Networks: Key Applications, Requirements and Challenges","volume":"2","author":"Lee","year":"2021","journal-title":"IEEE Open J. Veh. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"894","DOI":"10.1109\/JPROC.2009.2015717","article-title":"Breaking Spectrum Gridlock with Cognitive Radios: An Information Theoretic Perspective","volume":"97","author":"Goldsmith","year":"2009","journal-title":"Proc. IEEE"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1109\/TWC.2021.3095342","article-title":"3D Compressed Spectrum Mapping with Sampling Locations Optimization in Spectrum-Heterogeneous Environment","volume":"21","author":"Shen","year":"2021","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1109\/98.788210","article-title":"Cognitive radio: Making software radios more personal","volume":"6","author":"Mitola","year":"1999","journal-title":"IEEE Pers. Commun."},{"key":"ref_6","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_7","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1109\/MCOM.2015.7158264","article-title":"Spectrum and license flexibility for 5G networks","volume":"53","author":"Kliks","year":"2015","journal-title":"IEEE Commun. Mag."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Hossain, M.F., Munasinghe, K.S., and Jamalipour, A. (2017, January 4\u20137). BS Switching for Green Cellular Networks Using Energy-Aware Dynamic Traffic Offloading Schemes. Proceedings of the 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), Sydney, Australia.","DOI":"10.1109\/VTCSpring.2017.8108509"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1109\/JSAC.2015.2393496","article-title":"Energy-Efficiency Oriented Traffic Offloading in Wireless Networks: A Brief Survey and a Learning Approach for Heterogeneous Cellular Networks","volume":"33","author":"Chen","year":"2015","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1394","DOI":"10.1109\/LCOMM.2015.2443810","article-title":"Minimizing Energy Consumption Through Traffic Offloading in HetNets With Two-Class Traffic","volume":"19","author":"Song","year":"2015","journal-title":"IEEE Commun. Lett."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1109\/TFUZZ.2013.2272585","article-title":"Intuitionistic Fuzzy Analytic Hierarchy Process","volume":"22","author":"Xu","year":"2014","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Dryja\u0144ski, M., Ku\u0142acz, \u0141., and Kliks, A. (2021). Toward Modular and Flexible Open RAN Implementations in 6G Networks: Traffic Steering Use Case and O-RAN xApps. Sensors, 21.","DOI":"10.3390\/s21248173"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Singh, S.K., Singh, R., and Kumbhani, B. (2020, January 25\u201328). The Evolution of Radio Access Network towards Open-RAN: Challenges and Opportunities. Proceedings of the 2020 IEEE WCNCW, Seoul, Korea.","DOI":"10.1109\/WCNCW48565.2020.9124820"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Pamuklu, T., Erol-Kantarci, M., and Ersoy, C. (2021, January 14\u201323). Reinforcement Learning Based Dynamic Function Splitting in Disaggregated Green Open RANs. Proceedings of the ICC 2021\u2014IEEE International Conference on Communications, Montreal, QC, Canada.","DOI":"10.1109\/ICC42927.2021.9500721"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.1007\/s11277-020-07231-3","article-title":"From Cloud RAN to Open RAN","volume":"113","author":"Gavrilovska","year":"2020","journal-title":"Wirel. Pers. Commun."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/MCOM.101.2001120","article-title":"Intelligence and Learning in O-RAN for Data-Driven NextG Cellular Networks","volume":"59","author":"Bonati","year":"2021","journal-title":"IEEE Commun. Mag."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/9\/3515\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:06:26Z","timestamp":1760137586000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/9\/3515"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,5]]},"references-count":16,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,5]]}},"alternative-id":["s22093515"],"URL":"https:\/\/doi.org\/10.3390\/s22093515","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2022,5,5]]}}}