{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:01:56Z","timestamp":1775066516926,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61971440"],"award-info":[{"award-number":["61971440"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a cognitive satellite communication based wireless sensor network, which combines the wireless sensor network and the cognitive satellite terrestrial network. To address the conflict between the continuously increasing demand and the spectrum scarcity in the space network, the cognitive satellite terrestrial network becomes a promising candidate for future hybrid wireless networks. With the higher transmit capacity demand in satellite networks, explicit concerns on efficient resource allocation in the cognitive network have gained more attention. In this background, we propose a sensing-based dynamic spectrum sharing scheme for the cognitive satellite user, which is able to maximize the ergodic capacity of the satellite user with the interference of the primary terrestrial user below an acceptable average level. Firstly, the cognitive satellite user monitors the channel allocated to the terrestrial user through the wireless sensor network; then, it adjusts the transmit power based on the sensing results. If a terrestrial user is busy, the satellite user can access the channel with constrained power to avoid deteriorating the communication quality of the terrestrial user. Otherwise, if the terrestrial user is idle, the satellite user allocates the transmit power based on its benefit to enhance the capacity. Since the sensing-based dynamic spectrum sharing optimization problem can be modified into a nonlinear fraction programming problem in perfect\/imperfect sensing conditions, respectively, we solve them by the Lagrange duality method. Computer simulations have shown that, compared with the opportunistic spectrum access, the proposed method can increase the channel capacity more than     20 %     for      P  a v    = 10  dB      in a perfect sensing scenario. In an imperfect sensing scenario,      P  a v   = 15     dB and      Q  a v   = 5     dB, the optimal sensing time achieving the highest ergodic capacity is about 2.34 ms when the frame duration is 10 ms.<\/jats:p>","DOI":"10.3390\/s19235290","type":"journal-article","created":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T10:50:45Z","timestamp":1575283845000},"page":"5290","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Sensing-Based Dynamic Spectrum Sharing in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5567-6911","authenticated-orcid":false,"given":"Jing","family":"Hu","sequence":"first","affiliation":[{"name":"College of Communications Engineering, People Liberation Army Engineering University, No. 2 Biaoying, Qinhuai District, Nanjing 210007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangxia","family":"Li","sequence":"additional","affiliation":[{"name":"College of Communications Engineering, People Liberation Army Engineering University, No. 2 Biaoying, Qinhuai District, Nanjing 210007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongming","family":"Bian","sequence":"additional","affiliation":[{"name":"College of Communications Engineering, People Liberation Army Engineering University, No. 2 Biaoying, Qinhuai District, Nanjing 210007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyu","family":"Tang","sequence":"additional","affiliation":[{"name":"College of Communications Engineering, People Liberation Army Engineering University, No. 2 Biaoying, Qinhuai District, Nanjing 210007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6633-1983","authenticated-orcid":false,"given":"Shengchao","family":"Shi","sequence":"additional","affiliation":[{"name":"Beijing Institute of Information Technology, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1109\/MCOM.2002.1024422","article-title":"A survey on sensor networks","volume":"40","author":"Akyildiz","year":"2002","journal-title":"IEEE Commun. Mag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2812","DOI":"10.1109\/JPROC.2012.2195629","article-title":"Human Sensor Networks for Improved Modeling of Natural Disasters","volume":"100","author":"Aulov","year":"2012","journal-title":"Proc. IEEE"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Astapov, S., Preden, J.S., Ehala, J., and Riid, A. (2014, January 20\u201323). Object Detection for Military Surveillance Using Distributed Multimodal Smart Sensors. Proceedings of the 19th International Conference on Digital Signal Processing, Hong Kong, China.","DOI":"10.1109\/ICDSP.2014.6900688"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.compag.2015.08.011","article-title":"Wireless sensor networks for agriculture: The stateoftheart in practice and future challenges","volume":"118","author":"Ojha","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"970","DOI":"10.1109\/LCOMM.2007.071246","article-title":"Satellite earth station (SeS) selection method for satellite-based sensor networks","volume":"11","author":"Bisio","year":"2007","journal-title":"IEEE Commun. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3903","DOI":"10.1109\/JSEN.2014.2356580","article-title":"Integrated Wireless Sensor Systems via Near-Space and Satellite Platforms: A Review","volume":"14","author":"Wang","year":"2014","journal-title":"IEEE Sens. J."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"15398","DOI":"10.3390\/s150715398","article-title":"Diversity Performance Analysis on Multiple HAP Networks","volume":"15","author":"Dong","year":"2015","journal-title":"Sensors"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Li, H., Yin, H., Gong, X., Dong, F., Ren, B., He, Y., and Wang, J. (2016). Performance Analysis of Integrated Wireless Sensor and Multibeam Satellite Networks Under Terrestrial Interference. Sensors, 16.","DOI":"10.3390\/s16101711"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Thompson, P., and Evans, B. (2015, January 8\u201312). Analysis of interference between terrestrial and satellite systems in the Band 17.7 to 19.7 GHz. Proceedings of the IEEE International Conference on Communication Workshop, London, UK.","DOI":"10.1109\/ICCW.2015.7247420"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Kerczewski, R., Mohamed, J., Ngo, D., Spence, R., Stevens, G., Zaman, A., and Svoboda, J. (1996, January 25\u201329). A Study of the Potential Interference Between Satellite and Terrestrial Systems in the 28 GHz Band. Proceedings of the 16th International Communications Satellite Systems Conference, Washington, DC, USA.","DOI":"10.2514\/6.1996-1095"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Cocco, G., Cola, T.D., Angelone, M., and Katona, Z. (2016, January 5\u20137). Radio Resource Management Strategies for DVB-S2 Systems Operated with Flexible Satellite Payloads. Proceedings of the Advanced Satellite Multimedia Systems Conference & the Signal Processing for Space Communications Workshop, Palma de Mallorca, Spain.","DOI":"10.1109\/ASMS-SPSC.2016.7601536"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Sanchez, A.H., Soares, T., Wolahan, A., Sanchez, A.H., Soares, T., Wolahan, A., Sanchez, A.H., Soares, T., and Wolahan, A. (2017, January 23\u201326). Reliability aspects of mega-constellation satellites and their impact on the space debris environment. Proceedings of the Annual Reliability and Maintainability Symposium, Orlando, FL, USA.","DOI":"10.1109\/RAM.2017.7889671"},{"key":"ref_13","unstructured":"Dimitrov, S., Erl, S., Barth, B., Jaeckel, S., Kyrgiazos, A., and Evans, B.G. (July, January 29). Radio Resource Management Techniques for High Throughput Satellite Communication Systems. Proceedings of the European Conference on Networks and Communications, Paris, France."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1002\/sat.1169","article-title":"Joint cooperative spectrum sensing and channel selection optimization for satellite communication systems based on cognitive radio","volume":"35","author":"Jia","year":"2017","journal-title":"Int. J. Satell. Commun. Netw."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1002\/sat.1197","article-title":"Cognitive approaches to enhance spectrum availability for satellite systems","volume":"35","author":"Chatzinotas","year":"2016","journal-title":"Int. J. Satell. Commun. Netw."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/MWC.2018.1700113","article-title":"State of the Art, Taxonomy, and Open Issues on Cognitive Radio Networks with NOMA","volume":"25","author":"Zhou","year":"2018","journal-title":"IEEE Wirel. Commun."},{"key":"ref_17","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_18","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_19","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1109\/JSAC.2004.839380","article-title":"Cognitive radio: Brain-empowered wireless communications","volume":"23","author":"Haykin","year":"2005","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Sharma, S.K., Chatzinotas, S., and Ottersten, B. (2012, January 5\u20137). Satellite cognitive communications: Interference modeling and techniques selection. Proceedings of the 6th Advanced Satellite Multimedia Systems Conference and 12th Signal Processing for Space Communications Workshop, Baiona, Spain.","DOI":"10.1109\/ASMS-SPSC.2012.6333061"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1326","DOI":"10.1109\/TWC.2008.060869","article-title":"Sensing-Throughput Tradeoff for Cognitive Radio Networks","volume":"7","author":"Liang","year":"2008","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2361","DOI":"10.1109\/JSYST.2017.2698502","article-title":"Robust Max-Min Fairness Resource Allocation in Sensing-Based Wideband Cognitive Radio With SWIPT: Imperfect Channel Sensing","volume":"12","author":"Zhou","year":"2017","journal-title":"IEEE Syst. J."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Lagunas, E., Maleki, S., Chatzinotas, S., Soltanalian, M., and Ottersten, B. (2016, January 22\u201327). Power and Rate Allocation in Cognitive Satellite Uplink Networks. Proceedings of the IEEE International Conference on Communications, Kuala Lumpur, Malaysia.","DOI":"10.1109\/ICC.2016.7510839"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"e2945","DOI":"10.1002\/ett.2945","article-title":"Optimal iSINR-based power control for cognitive satellite terrestrial networks","volume":"28","author":"Vassaki","year":"2015","journal-title":"Trans. Emerg. Telecommun. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Shi, S., Li, G., An, K., Gao, B., and Zheng, G. (2017). Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks. Sensors, 17.","DOI":"10.3390\/s17092025"},{"key":"ref_26","first-page":"1815","article-title":"Optimal Power Control for Real-time Applications in Cognitive Satellite Terrestrial Networks","volume":"21","author":"Shi","year":"2017","journal-title":"IEEE Commun. Lett."},{"key":"ref_27","unstructured":"Engelman, R., Abrokwah, K., Dillon, G., Foster, G., Godfrey, G., Hanbury, T., Lagerwerff, C., Leighton, W., Marcus, M., and Noel, P. (2019, December 01). Federal Communications Commission Spectrum Policy Task Force Report of the Spectrum Efficiency Working Group, Available online: https:\/\/transition.fcc.gov\/sptf\/files\/SEWGFinalReport_1.pdf."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"860","DOI":"10.1109\/COMST.2015.2481722","article-title":"Cognitive Radio for Smart Grids: Survey of Architectures, Spectrum Sensing Mechanisms, and Networking Protocols","volume":"18","author":"Khan","year":"2015","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"6586","DOI":"10.1109\/TWC.2017.2725950","article-title":"Performance Analysis of Overlay Spectrum Sharing in Hybrid Satellite-Terrestrial Systems with Secondary Network Selection","volume":"16","author":"Sharma","year":"2017","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"7114","DOI":"10.1109\/TVT.2017.2673861","article-title":"Optimal Spectrum Access and Energy Supply for Cognitive Radio Systems with Opportunistic RF Energy Harvesting","volume":"66","author":"Pratibha","year":"2017","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Boyd, S., and Vandenberghe, L. (2004). Convex Optimization, Cambridge University Press.","DOI":"10.1017\/CBO9780511804441"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1109\/TWC.2003.811182","article-title":"A new simple model for land mobile satellite channels: First- and second-order statistics","volume":"2","author":"Abdi","year":"2003","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1109\/LWC.2015.2411597","article-title":"Cognitive Zone for Broadband Satellite Communication in 17.3\u201317.7 GHz Band","volume":"4","author":"Maleki","year":"2015","journal-title":"IEEE Wirel. Commun. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"918","DOI":"10.1109\/JSAC.2018.2824622","article-title":"Artificial noise aided secure cognitive beamforming for cooperative MISO-NOMA using SWIPT","volume":"36","author":"Zhou","year":"2018","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_35","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. Tutor."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zhang, R., Kang, X., and Liang, Y.C. (2009, January 14\u201318). Protecting primary users in cognitive radio networks: Peak or average interference power constraint?. Proceedings of the IEEE International Conference on Communications, Dresden, Germany.","DOI":"10.1109\/ICC.2009.5199373"},{"key":"ref_37","unstructured":"Stevenson, C.R. (2019, December 01). Functional Requirements for the 802.22 WRAN Standard. Available online: https:\/\/ci.nii.ac.jp\/naid\/10026841909\/."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5290\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:39:03Z","timestamp":1760189943000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5290"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,1]]},"references-count":37,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2019,12]]}},"alternative-id":["s19235290"],"URL":"https:\/\/doi.org\/10.3390\/s19235290","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,12,1]]}}}