LEADER 04436nam 22006015 450 001 9910337601703321 005 20251204110854.0 010 $a3-030-15416-5 024 7 $a10.1007/978-3-030-15416-5 035 $a(CKB)4100000008103803 035 $a(MiAaPQ)EBC5776215 035 $a(DE-He213)978-3-030-15416-5 035 $a(PPN)236524534 035 $a(EXLCZ)994100000008103803 100 $a20190502d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIntelligent Spectrum Handovers in Cognitive Radio Networks /$fby Anandakumar Haldorai, Umamaheswari Kandaswamy 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (230 pages) 225 1 $aEAI/Springer Innovations in Communication and Computing,$x2522-8609 311 08$a3-030-15415-7 327 $aChapter1: Cooperative Spectrum Handovers in Cognitive Radio Networks -- Chapter2: Intelligent Cognitive Radio Communication ? A Detailed Approach -- Chapter3: Energy Efficient Spectrum Handovers in Cognitive Network Selection -- Chapter4: Software Radio Architecture: A Mathematical Perspective -- Chapter5: Distributed Algorithms for Learning and Cognitive Medium -- Chapter6: Dynamic Spectrum Handovers in Cognitive Radio Networks -- Chapter7: Supervised Machine Learning Techniques in Cognitive Radio Network Handovers -- Chapter8: Green Wireless Communications via Cognitive Handover -- Chapter9: Secure Distributed Spectrum Sensing in Cognitive Radio Networks -- Chapter10: Applications and Services of Intelligent Spectrum Handover. 330 $aThis book highlights the need for an efficient Handover Decision (HD) mechanism to perform switches from one network to another and to provide unified and continuous mobile services that include seamless connectivity and ubiquitous service access. The author shows how the HD involves efficiently combining handover initiation and network selection process. The author describes how the network selection decision is a challenging task that is a central component to making HD for any mobile user in a heterogeneous environment that involves a number of static and dynamic parameters. The author also discusses prevailing technical challenges like Dynamic Spectrum Allocation (DSA) methods, spectrum sensing, cooperative communications, cognitive network architecture protocol design, cognitive network security challenges and dynamic adaptation algorithms for cognitive system and the evolving behavior of systems in general. The book allows the reader to optimize the sensing time for maximizing the spectrum utilization, improve the lifetime of the cognitive radio network (CRN) using active scan spectrum sensing techniques, analyze energy efficiency of CRN, find a secondary user spectrum allocation, perform dynamic handovers, and use efficient data communication in the cognitive networks. Identifies energy efficient spectrum sensing techniques for Cooperative Cognitive Radio Networks (CRN); Shows how to maximize the energy capacity by minimizing the outage probability; Features end-of-chapter summaries, performance measures, and case studies. 410 0$aEAI/Springer Innovations in Communication and Computing,$x2522-8609 606 $aTelecommunication 606 $aSignal processing 606 $aComputer networks 606 $aComputational intelligence 606 $aCommunications Engineering, Networks 606 $aSignal, Speech and Image Processing 606 $aComputer Communication Networks 606 $aComputational Intelligence 615 0$aTelecommunication. 615 0$aSignal processing. 615 0$aComputer networks. 615 0$aComputational intelligence. 615 14$aCommunications Engineering, Networks. 615 24$aSignal, Speech and Image Processing. 615 24$aComputer Communication Networks. 615 24$aComputational Intelligence. 676 $a621.384 676 $a004.685 700 $aHaldorai$b Anandakumar$4aut$4http://id.loc.gov/vocabulary/relators/aut$0867177 702 $aKandaswamy$b Umamaheswari$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910337601703321 996 $aIntelligent Spectrum Handovers in Cognitive Radio Networks$91935498 997 $aUNINA