Refine your search
Collections
Co-Authors
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Lala, Nisar A.
- Spectrum Handoff in Cognitive Radio Networks:A Survey
Abstract Views :224 |
PDF Views:0
Authors
Affiliations
1 Division of Agricultural Engineering, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir Srinagar, J&K, IN
1 Division of Agricultural Engineering, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir Srinagar, J&K, IN
Source
Oriental Journal of Computer Science and Technology, Vol 10, No 4 (2017), Pagination: 765-772Abstract
Cognitive radio (CR) is a promising solution to improve the spectrum utilization by enabling unlicensed users to exploit the spectrum in an opportunistic manner. Spectrum handoff is a different type of handoff in CR necessitated by the reappearance of primary user (PU) in the licensed band presently occupied by the secondary users (SUs). Spectrum handoff procedures aim to help the SUs to vacate the occupied licensed spectrum and find suitable target channel to resume the unfinished transmission. The purpose of spectrum mobility management in cognitive radio networks is to make sure that the transitions are made smoothly and rapidly such that the applications running on a cognitive user perceive minimum performance degradation during a spectrum handoff. In this paper, we will survey the literature on spectrum handoff in cognitive radio networks.Keywords
Cognitive Radio, Spectrum Handoff, Primary User, Secondary User, Spectrum Mobility.Full Text
References
- Cisco. Scaling the mobile internet. White Paper, 2009.
- Federal Communications Commission (FCC). Notice of proposed rulemaking and order No. 03-222. Dec. 2003.
- Spectrum occupancy measurements (SSC). 1595 Spring Hill Rd, Suite 110, Vienna, VA 22182, USA, Tech Rep.. 2005. [Online]http://www.sharedspectrum.com/
- McHenry M.A., Tenhule P.A., McCloskey D., Roberson D.A., Hood C.S. Chicago spectrum occupancy measurements and analysis and a long term studies proposal. Proceedings of 1st International Workshop on Technology and Pol icy for Accessing Spect rum (TAPAS’ 06) New York, USA (ACM), 2006.
- Lopez-Benitez M., Umbert A., Casadevall F. Evaluation of spectrum occupancy in Spain for cognitive radio applications. Proceedings of IEEE 69th Vehicular Technology Conference (VTC 2009 Spring), 2009; 1-5.
- Islam M.H., Koh C.L., Oh S.W., Qing X., Lai Y.Y., et al,. Spectrum survey in Singapore: Occupancy measurements and analyses. Proceedings of 3rd International Conference on Cognitive Radio Oriented
- Wireless Networks and Communications (CROWNCOM), May 2008;1–7.
- Wellens M., Wu J., Mahonen P. Evaluation of spectrum occupancy in indoor and outdoor scenario in the context of cognitive radio. Proceedings of 2nd International Conference on Cognitive Radio Oriented
- Wireless Networks and Communications (CROWNCOM), Aug 2007; 420-7.
- Harrold T.J., Cepeda R.A., Beach M.A. Long-term measurements of spectrum occupancy characteristics. Proceedings of IEEE International Symposium on Dynamic Spectrum Access Networks (DySpan) Aachen, Germany, May 2011; 83-9.
- Chiang R.I.C., Rowe G.B., Sowerby K.W. A quantitative analysis of spectral occupancy measurements for cognitive radio. Proceedings of IEEE 65th Vehicular Technology Conference (VTC), Dublin, Ireland, April 2007; 3016-20.
- Mehdawi M., Riley N., Paulson K., Fanan A., Ammar M. Spectrum occupancy survey in Hull-UK for cognitive radio applications:Measurement and analysis. J. Scientific and Technology Research, April 2013; 2(4):231-6.
- Ileri O., Samardzija D., Mandayam N.B. Dynamic property rights spectrum access: Flexible ownership based spectrum management. Proceedings of 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Network (DySPAN) Dublin, Ireland, April 2007; 254-65.
- Kim H., Hyon T., Lee Y. Priority and negotiation based dynamic spectrum allocation scheme for multiple radio access network operators. IEICE Transactions on Communications, 2010; E91-B(7):2393-6.
- Akyildiz I.F., Lee W.Y., Vuran M.C., Mohanty S. Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Computer Networks (Elsevier), 2006; 50:2127–59.
- Haykin S. Cognitive radio: Brain empowered wireless communications. IEEE Journal on Selected Areas in Communications, 2005; 23(2):201-20.
- Arslan H.(ed): Cognitive radio, software defined radio, and adaptive wireless systems. Springer, 2007 (e-book).
- Fu X., Zhou W., Xu J., Song J. Extended mobility management challenges over cellular networks combined with cognitive radio by using multi-hop network. Proceedings of International Conference
- on Software Engineering, Artificial Intelligence, Networking, and Parallel/distributed Computing, July 2007; 2:683-8.
- Liu H.J., Wang Z.X., Li S.F., Yi M. Study on the performance of spectrum mobility in cognitive wireless network. Proceedings of 11th IEEE International Conference on Communication Systems (ICCS), 2008; 1010-4.
- Quang B. V., Prasad R. V., Niemegeers I. A survey on handoffs- Lessons for 60 GHz based wireless systems. IEEE Communications Surveys and Tutorials, 2010; 14(1): 64-86.
- Cavdar D., Yilmaz H.B., Tugcu T., Alagoz F. Analytical modeling and performance evaluation of cognitive radio networks. Proceedings of 6th Advanced International Conference on Telecommunications (AICT), IEEE Computer Society, 2010; 35-40.
- Wang L.C., Wang C.W., Chang C.J. Modeling and analysis for spectrum handoffs in cognitive radio networks. Proceedings of IEEE Transactions on Mobile Computing, 2011; 11(9): 1499-1513.
- Wang L.C., Wang C.W., Feng K.T. A queuingtheoretical framework for QoS-enabled spectrum management in cognitive radio networks. IEEE Wireless Communications Magazine, 2011; 18(6):18-26.
- Zheng S., Yang X., Chen S., Lou C. Target channel sequence selection scheme for proactive- decision spectrum handoff. IEEE Communications Letters, 2011; 15(12):1332-4.
- Srinivasa S., Jafar S.A. The throughput potential of cognitive radio: A theoretical perspective. Proceedings of 40th Asilomer Conference on Signals, Systems and Computers, 2006; 221-5.
- Shi Q., Taubenheim D., Kyperountas S., Gorday P., Correal N. Link maintenance protocol for cognitive radio system with OFDM PHY. Proceedings of 2nd IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2007; 440-3.
- Wang C.W., Wang L.C. Modeling and analysis for proactive decision spectrum handoff in cognitive radio networks. Proceedings of IEEE International Conference on Communications (ICC), 2009;1-6.
- Willkomm D., Gross J., Wolisz A. Reliable link maintenance in cognitive radio systems. Proceedings of 1st IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2005; 371-8.
- Tian J., Bi G. A new link maintenance and compensation model for cognitive UWB radio systems. Proceedings of 6th International Conference on ITS Telecommunications, 2006; 254-7.
- Wang C.W., Wang L.C., Adachi F. Modeling and analysis for reactive decision spectrum handoff in cognitive radio networks. Proceedings of IEEE Global Telecommunications Conference (GLOBECOM), 2010; 1-6.
- Wang L.C., Wang C.W. Spectrum handoff for cognitive radio networks: reactive sensing or proactive sensing? Proceedings of IEEE International Conference on Performance, Computing and Communications (IPCCC), 2008; 343-8.
- Lala N.A., Moin Uddin, Sheikh N.A. Novel hybrid spectrum handoff for cognitive radio networks. International Journal of Wireless and Microwave Technologies, Sep. 2013; 3(1):1-10.
- Zhang Y. Spectrum handoff in cognitive radio networks: opportunistic and negotiated situations. Proceedings of IEEE International Conference on Communications (ICC), 2009; 1-6.
- Zhu X., Shen L., Yum T.S.P. Analysis of cognitive radio spectrum access with optimal channel reservation. Proceedings of IEEE Communications Letters, 2007; 11(4):304-6.
- Zhang Y. Dynamic spectrum access in cognitive radio wireless networks. Proceedings of IEEE International Conference on Communications (ICC), 2008, 4927-32.
- Ahmed W., Gao J., Faulkner M. Performance evaluation of cognitive radio network with exponential and truncated usage models. Proceedings of IEEE International Symposium on Wireless Pervasive Computing (ISWPC), 2009; 1-5.
- Wang L.C., Wang C.W. Spectrum management techniques with QoS provisioning in cognitive radio networks. Proceedings of 5th IEEE International Symposium on Wireless Pervasive Computing (ISWPC), 2010; 116-21.
- Mitola J. Cognitive radio for flexible mobile multimedia communications. Proceedings of IEEE International Workshop on Mobile Multimedia Communications (MoMUC), 1999; 3-10.
- Liu H.J., Li S.F., Wang Z.X., Hong W.J., Yi M. Strategy of dynamic spectrum access strategy based on spectrum pool. Proceedings of 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), 2008; 1-6.
- Han H., Wu Q., Yin H. Spectrum sensing for real-time spectrum handoff in CRNs. Proceedings of 3rd IEEE International Conference on Advanced Computer Theory and Engineering (ICACTE), 2010; 480-4.
- Qiao X., Tan Z., Li J. Combined optimization of spectrum handoff and spectrum sensing for cognitive radio systems. Proceedings of 7th IEEE International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), 2011; 1-4.
- Wu C., He C., Jiang L., Chen Y. A novel spectrum handoff scheme with spectrum admission control in cognitive radio networks. Proceedings of IEEE Global Telecommunications Conference (GLOBECOM), 2011; 1-5.
- Yoon S., Ekici E. Voluntary spectrum handoff: A novel approach to spectrum management in CRNs. Proceedings of IEEE International Conference on Communications (ICC), 2010;1-5.
- Zheng S., Yang X., Chen S., Lou C. Target channel sequence selection scheme for proactive-decision spectrum handoff. IEEE Communications Letters, 2011;15(12):1332-4.
- Li L., Shen Y., Li K., Lin K. TPSH: A novel spectrum handoff approach based on time estimation in dynamic spectrum networks. Proceedings of IEEE International Conference on Computational Science and Engineering (CSE), 2011; 345-50.
- Ma R.T., Hsu Y.P., Feng K.T. A POMDP-based spectrum handoff protocol for partially observable cognitive radio networks. Proceedings of IEEE Wireless Communications and Networking Conference (WCNC), 2009;1-6.
- Yuan G., Grammenos R.C., Yang Y., Wang W. Selective spectrum sensing and access based on traffic prediction. Proceedings of 20th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2009; 1078-82.
- Xie X., Yang G., Ma B. Spectrum handoff decision algorithm with dynamic weights in cognitive radio networks. Proceedings of IEEE Global Mobile Congress (GMC), 2011;1-6.
- Lertsinsrubtavee A., Malouch N., Fdida S. Spectrum handoff strategy using cumulative probability in cognitive radio networks. Proceedings of 3rd International Congress on Ultramodern Telecommunications and Control Systems Workshop (ICUMT), 2011;1-7.
- Giupponi L., Perez-Neira A.I. Fuzzy based spectrum handoff in cognitive radio networks. Proceedings of 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom), 2008;1-6.
- Kaur P., Moin Uddin, Khosla A. An efficient spectrum mobility management strategy in cognitive radio networks. Proceedings of 1st UK-India International Workshop on Cognitive Wireless Systems (UKIWCWS), 2009;1-6.
- Lala N.A., Moin Uddin, Sheikh N.A. Novel spectrum handoff in cognitive radio networks using fuzzy logic. International Journal of Information Technology and computer Science, Oct. 2013; 5(11):103-10.
- Baroudi U., Alfadhly A. Effects of mobility and primary appearance probability on spectrum handoff. Proceedings of 73rd IEEE Vehicular Technology Conference (VTC spring), 2011;1-6.
- Song Y., Xie J. Common hopping based proactive spectrum handoff in cognitive radio adhoc networks. Proceedings of IEEE Global Telecommunication Conference (GLOBECOM), 2010;1-5.
- Song Y., Xie J. Proactive spectrum handoff in cognitive radio adhoc networks based on common hopping coordination. Proceedings of IEEE Workshop on Computer Communications (INFOCOM), 2010;1-2.
- Song Y., Xie J. ProSpect: A proactive spectrum handoff framework for cognitive radio adhoc networks without common control channel. IEEE Transactions on Mobile Computing, 2012; 11(7):1127-39.
- Song Y., Xie J. Performance analysis of spectrum handoff for cognitive radio adhoc networks without common control channel under homogeneous primary traffic. Proceedings of IEEE INFOCOM, 2011; 3011-9.
- Quality of Service Provisioning in Cognitive Radio Network
Abstract Views :218 |
PDF Views:0
Authors
Affiliations
1 College of Agricultural Engineering and Technology, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir Srinagar, J&K, IN
2 Department of Electronics, Gandhi Memorial College Srinagar, J&K, IN
1 College of Agricultural Engineering and Technology, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir Srinagar, J&K, IN
2 Department of Electronics, Gandhi Memorial College Srinagar, J&K, IN
Source
Oriental Journal of Computer Science and Technology, Vol 10, No 4 (2017), Pagination: 780-787Abstract
Cognitive radio is a future technology coined for increasing the utilization of otherwise under-utilized spectrum channels. Providing quality of service (QoS) to diverse flows as per their requirements is a very difficult job as there is no dedicated allocation of wireless channels in cognitive radio (CR) network. The paper selects few critical QoS parameters such as signal-strength, bandwidth and user-mobility that assess the influence on quality of communication between users using rule-based fuzzy inference system. The analytical results show the influence of those QoS parameters on the quality of communicating channels and open new issues in designing protocol structure for CR.Keywords
Cognitive Radio, Quality of Service (QoS), Fuzzy Logic.Full Text
References
- FCC, Notice of proposed rule making and order, No. 03-222 , Dec. 2003.
- Mitola J. Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio. Ph.D. Dissertation: KTH Royal Institute of Technology; 2000.
- Mitola J. and Maguire G.Q. Cognitive Radio: Making Software Radios more Personal. IEEE Personal Communications,1999; 6(4): 13-8.
- Haykin S. Cognitive Radio: Brain Empowered Wireless Communications. IEEE Journal on Selected Areas in Communications,2005; 23(2): 201-20.
- ITU-T Recommendation. Terms and definitions related to quality of service and network performance Including dependability. E.800, 1994.
- ETSI, Network aspects (NA). General aspects of quality of service (QoS) and network performance (NP). ETSI Technical report, ETR 003, 2nd edition, 1994.
- Chen S. Routing Support for Providing Guaranteed End to End Quality of Service. University of Illinois at Urbana-Champaign.
- Kickert W.J.M. and Lemke H.R. Applications of a Fuzzy Controller in a Warm Water Plant. Automatica, 1976;12(4):301-8.
- King P.J. and Mamdani E.H. The Application of Fuzzy Control Systems to Industrial Processes. Automatica, 1977;13(3):235-42.
- Ghosh S., Razouqi Q., Schumacher H.J. and Celmins A. A Survey of Recent Advances in Fuzzy Logic in Telecommunication Networks and New Challenges. IEEE Transactions on fuzzy systems, 1998, 6(3).
- Chemovil P., Khalfet J. and Lebourges M. A Fuzzy Control Approach for Adaptive Traffic Routing. IEEE Communications magazine, 1995; 70-76.
- Mendel J.M. Fuzzy Logic Systems for Engineers: A tutorial. Proceeding of IEEE,1995; 83(3):345-77.
- Ma Y., Hu X., Zhang Y., and Zhao E. A Fuzzy Call Admission Control Scheme in Cellular Multimedia Networks. International Conference on Wireless Communications, Networking and Mobile Computing, 2005;844-7.
- Zhang R. and Long K. A Fuzzy Routing Mechanism in Next Generation Networks. IASTED International Conference on Intelligent Systems and Control (ISC), 2002;86-91.
- Le H-S. T. and Liang Q. An Efficient Power Control Scheme for Cognitive Radios. Proceedings of Wireless Communications & Networks Conference (WCNC), 2007; 2559-63.
- Baldo N. and Zorzi M. Fuzzy Logic for Cross Layer Optimization in Cognitive Radio Networks. IEEE Communication Magazine,2008; 64-72.
- Le H-S T. and Ly H.D. Opportunistic Spectrum Access using Fuzzy Logic for Cognitive Radio Networks. 2nd International Conference on Communications and Electronics (ICCE),2008; 240-5.
- Kaur P., Moin Uddin and Khosla A. Fuzzy Based Adaptive Bandwidth Allocation Scheme in Cognitive Radio Networks. International Conference on ICT and Knowledge Engineering, 2010; 41-5.
- Giupponi L. and Perez-Neira A.I. Fuzzy Based Spectrum Handoff in Cognitive Radio Networks. 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications Crown Com, 2008;1-6.
- Lala Nisar A., Moin Uddin and Sheikh N. A.Novel Spectrum Handoffin Cognitive Radio Networks Using Fuzzy Logic. International Journal of Information Technology and computer Science, 2013; 5(11): 103-10.
- Wanbin T. and Dong P. Spectrum Handoff in Cognitive Radio with Fuzzy Logic Control. Journal of Electronics (China), 2010; 708-14.
- Lala Nisar A., Moin Uddin and Sheikh N. A. Identification and Integration of QoS parameters in Cognitive Radio Networks using Fuzzy Logic. International Journal of Emerging Sciences,2013; 3(3): 279-88.
- Lala Nisar A., Moin Uddin and Sheikh N. A. A Novel Algorithm for Estimation of QoS in Cognitive Radio Using Fuzzy Logic.International Journal of Information Technology and Electrical Engineering,2013; 2(5):1-5.
- Hong D. and Rappaport S. S. Traffic model and performance analysis for cellular mobile radio telephone systems with prioritized and non-prioritized handoff procedure. IEEE Transactions on Vehicular Technology, 1986; VT-35(3): 448-61.
- Stojmenovic I.Handoff of Wireless Networks and Mobile Computing. Wiley India Edition, 2002.
- Realisation of Cognitive Radio:Issues and Challenges
Abstract Views :197 |
PDF Views:0
Authors
Affiliations
1 Division of Agricultural Engineering, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir Srinagar, J&K, IN
1 Division of Agricultural Engineering, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir Srinagar, J&K, IN
Source
Oriental Journal of Computer Science and Technology, Vol 10, No 4 (2017), Pagination: 802-809Abstract
For last two decades, the demand for wireless spectrum has been increasing rapidly with tremendous developments in the telecom industry. There also has been huge growth in flow of multimedia traffic over the last decade. Thus, the demand for additional bandwidth is increasing exponentially despite the fact that the electromagnetic spectrum is a finite resource. On the other hand, spectrum occupancy is found to be quiet low in most of the allocated bands. Thus, the under-utilization of the precious spectrum is unaffordable if persistent growth of new and existing wireless services are to be sustained. Cognitive radio (CR) is a future technology initiated by many research organizations and academic institutions to increase the spectrum utilization of underutilized spectrum channels to ameliorate scarcity problem of valuable electromagnetic spectrum. There exists number of issues and challenges in designing and implementation of the cognitive radio. These issues need to be rigorously resolved before a cognitive radio is realised.Keywords
Cognitive Radio, Spectrum Sensing, Spectrum Management, Spectrum Mobility, Spectrum Sharing, Primary User, Secondary User.Full Text
References
- Cisco. Scaling the mobile internet. White Paper, 2009.
- Federal Communications Commission (FCC), Notice of proposed rulemaking and order No. 03-222 , Dec. 2003.
- S. S. C. Spectrum occupancy measurements, SSC. 1595 Spring Hill Rd, Suite 110, Vienna, VA 22182, USA, Tech Rep., 2005.[Online] http://www.sharedspectrum.com/
- Mc Henry M. A., Tenhule P. A., McCloskey D., Roberson D. A. and Hood C. S.Chicago spectrum occupancy measurements and analysis and a long term studies proposal. 1stInternational Workshop on Technology and Policy for Accessing Spectrum (TAPAS’ 06), New York, USA (ACM), 2006.
- Lopez-Benitez M., Umbert A. and Casadevall F.Evaluation of spectrum occupancy in Spain for cognitive radio applications.IEEE 69th Vehicular Technology Conference (VTC 2009 Spring), Apr. 2009, 1-5.
- Islam M.H., Tan G. L., Chin F. et.al. Spectrum survey in Singapore: Occupancy measurements and analyses. 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), May 2008, 1–7.
- Wellens M., Wu J. and Mahonen P. Evaluation of spectrum occupancy in indoor and outdoor scenario in the context of cognitive radio.2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), Aug 2007, 420-7.
- Harrold T. J., Cepeda R. A., and Beach M. A. Long-term measurements of spectrum occupancy characteristics. IEEE International Symposium on Dynamic Spectrum Access Networks(DySpan),Aachen, Germany, May 2011, 83-9.
- Chiang R. I. C., Rowe G. B. and Sowerby K. W. A quantitative analysis of spectral occupancy measurements for cognitive radio. IEEE 65thVehicular Technology Conference (VTC), Dublin, Ireland, 2007, 3016-20.
- Mehdawi M., Riley N., Paulson K., Fanan A.and Ammar M. Spectrum occupancy survey in Hull-UK for cognitive radio applications: Measurement and analysis.International Journalof Scientific and Technology Research, 2013, 2(4):231-6.
- Patil K., Prasad R and Skouby K. A survey of worldwide spectrum occupancy measurements campaigns for cognitive radio. International Conference on Devices and Communication (ICDecom), 2011, 1-5.
- Ileri O., Samardzija D., and Mandayam N. B. Dynamic property rights spectrum access: Flexible ownership based spectrum management. 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Network (DySPAN), Dublin, Ireland, April 2007,254-65.
- Kim H., HyonT., and Lee Y. Priority and negotiation based dynamic spectrum allocation scheme for multiple radio access network operators. IEICE Transactions on Communications, 2010, E91-B(7): 2393-6.
- Akyildiz I. F., Lee W.-Y., Vuran M. C. and Mohanty S.Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey.Computer Networks (Elsevier), 2006, 50: 2127–59.
- Mitola J. Cognitive radio: an integrated agent architecture for software definedradio. Ph. D. Dissertation: Royal Institute of Technology (KTH), Stockholm, Swedan, 2000.
- Telecom Spectrum Allocation in India, Article. [Online]http://www.indiatelecomonline.com
- Khalid L and Anpalagan A. Emerging cognitive radio technology: principles,challenges and opportunities. Computers and Electrical Engineering (Elsevier), 2010, 36 (2): 358-66.
- Akyildiz I. F., Lee W.-Y., Vuran M. C and Mohanty S.A survey on spectrum management in cognitive radio networks.IEEE Communications Magazine, 2008, 46(4): 40-8.
- Arslan H.Cognitive Radio,Software defined Radio, and Adaptive Wirelessm Systems. Netherlands, Springer, 2007.
- Tandra R. and Sahai A. Some fundamental limits on detection in low SNR under noise uncertainty. IEEE International Conference on Wireless Networks, Communications and Mobile Computing, 2005, Vol. 1, 464-9.
- Digham F., Alouini M. and Simon M. On the energy detection of unknown signals over fading channels. IEEE International Conference on Communications, 2003,Vol. 5: 3575-9.
- Cabric D., Mishra S.M. and Brodersen R.W. Implementation issues in spectrum sensing for cognitive radio. 38th Asilomar Conference on Signals, Systems and Computers, 2004, Vol. 1: 772-6.
- Cabric D. and Brodersen R. W. Physical layer design issues unique to cognitive radio systems. 16th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications,2005, Vol. 2: 759-63.
- Tang H. Some physical layer issues of wide-band cognitive radio system. IEEE 1st International Symposium on New Frontiers in Dynamic Spectrum Access Network (DySPAN), 2005, 151-9.
- Ghasemi A. and Sousa E. S. Collaborative spectrum sensing for opportunistic access in fading environment. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Network (DySPAN), 2005,131-6.
- Ganesan G. and Li Y. Cooperative spectrum sensing in cognitive radio networks. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Network (DySPAN), 2005, 137-43.
- Haykin S. Cognitive radio: Brain empowered wireless communications. IEEE Journal on Selected Areas in Communications, 2005, 23(2): 201-20.
- Kanodia V., Sabharwal A. and Knightly. MOAR: A multichannel opportunistic auto-rate media access protocol for ad-hoc networks. 1st IEEE International Conference on Broadband Networks, 2004, 600-10.
- Fu X., Zhou W., Xu J. and Song J. Extended mobility management challenges over cellular networks combined with cognitive radio by using multi-hop network. International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/distributed Computing, 2007, Vol. 2: 683-8.
- Liu H.-J., Wang Z.-X., Li S.-F.and Yi M.Study on the performance of spectrum mobility in cognitive wireless network. 11th IEEE International Conference on Communication Systems (ICCS), 2008, 1010-4.
- Peng C., Zheng H. and Zhao B. Utilization and fairness in spectrum assignment for opportunistic spectrum access. ACM Mobile Networks Applications, 2006, 555-76.
- Cao L. and Zheng H. Distributed spectrum allocation via local bargaining. 2nd IEEE Conference on Sensor and Ad Hoc Communications and Networks (SECON), 2005, 475-86.
- Huang J., Berry R. A. and Honig M. L. Spectrum sharing with distributed interference compensation. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Network (DySPAN), 2005, 88-93.
- Sankaranarayanan S., Papadimitratos P., Mishra A. and Hershey S. A bandwidth sharing approach to improve licensed spectrum utilization. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Network (DySPAN), 2005, 279-88.
- Zhao J., Zheng H. and Yang G.-H. Distributed coordination in dynamic spectrum allocation networks. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Network (DySPAN), 2005, 259-68.
- Zhao Q.,Tong L. and Swami A. Decentralized cognitive MAC for dynamic spectrum access.IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Network (DySPAN), 2005, 224-32.
- Brik V., Rozner E., Banarjee S. and Bahl P. DSAP: A protocol for coordinated spectrum access. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Network (DySPAN), 2005, 611-4.
- Federal Communications Commission. FCC first report and order: revision of Part 15 of the commission’s rules regarding ultra-wideband transmission systems.report ET Docket No. 98–153, 2002.
- Quality of Service in Cognitive Radio Network:Issues and Challenges
Abstract Views :166 |
PDF Views:0
Authors
Affiliations
1 College of Agricultural Engineering and Technology, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir, Srinagar, J&K, IN
2 Department of Electronics, Gandhi Memorial College, Srinagar, J&K, IN
1 College of Agricultural Engineering and Technology, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir, Srinagar, J&K, IN
2 Department of Electronics, Gandhi Memorial College, Srinagar, J&K, IN
Source
Oriental Journal of Computer Science and Technology, Vol 11, No 1 (2018), Pagination: 34-39Abstract
Cognitive radio (CR) is a novel technology to resolve the issue of under-utilization of wireless spectrum. There exists number of challenges and issues in designing and implementation of the cognitive radio. Extending quality-of- service (QoS) enabled applications to CR network is even more difficult task due to non-availability of the dedicated allocation of idle spectrum. CR imposes peculiar and unique challenges to guarantee quality of service of diverse flows in contrast to other wireless networks. This paper identifies the issues and challenges of QoS provisioning in cognitive radio networks.Keywords
Cognitive Radio, Quality of Service (QoS), Spectrum Management.Full Text
References
- Cisco. Scaling the mobile internet. White Paper, 2009.
- Federal Communications Commission (FCC). Notice of proposed rulemaking and order No. 03-222. Dec. 2003.
- Spectrum occupancy measurements (SSC). 1595 Spring Hill Rd, Suite 110, Vienna, VA 22182, USA, Tech Rep.. 2005.
- McHenry M.A., Tenhule P.A., McCloskey D., Roberson D.A., Hood C.S. Chicago spectrum occupancy measurements and analysis and a long term studies proposal. Proceedings of 1st International Workshop on Technology and Policy for Accessing Spectrum (TAPAS’ 06) New York, USA (ACM), 2006.
- Lopez-Benitez M., Umbert A., Casadevall F. Evaluation of spectrum occupancy in Spain for cognitive radio applications. Proceedings of IEEE 69th Vehicular Technology Conference (VTC 2009 Spring), 2009; 1-5.
- Islam M.H., Koh C.L., Oh S.W., Qing X., Lai Y.Y., et al., Spectrum survey in Singapore: Occupancy measurements and analyses. Proceedings of 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), May 2008;1–7.
- Wellens M., Wu J., Mahonen P. Evaluation of spectrum occupancy in indoor and outdoor scenario in the context of cognitive radio. Proceedings of 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), Aug 2007; 420-7.
- Harrold T.J., Cepeda R.A., Beach M.A. Long-term measurements of spectrum occupancy characteristics. Proceedings of IEEE International Symposium on Dynamic Spectrum Access Networks (DySpan) Aachen, Germany, May 2011; 83-9.
- Chiang R.I.C., Rowe G.B., Sowerby K.W. A quantitative analysis of spectral occupancy measurements for cognitive radio. Proceedings of IEEE 65th Vehicular Technology Conference (VTC), Dublin, Ireland, April 2007; 3016-20.
- Mehdawi M., Riley N., Paulson K., Fanan A., Ammar M. Spectrum occupancy survey in Hull-UK for cognitive radio applications: Measurement and analysis. J. Scientific and Technology Research, April 2013; 2(4): 231-6.
- Haykin S. Cognitive radio: Brain empowered wireless communications. IEEE Journal on Selected Areas in Communications, 2005; 23(2):201-20.
- Federal Communication Commissi on (FCC). Unlicensed operation in TV broadcast bands. Notice for Proposed Rule Making, ET Docket No. 04-113, May 2004.
- Arslan H. Cognitive radio, software defined radio, and adaptive wireless systems. Springer, 2007(e-book).
- Fu X., Zhou W., Xu J., Song J. Extended mobility management challenges over cellular networks combined with cognitive radio by using multi-hop network. Proceedings of International Conference on Software Engineer ing, Ar tificial Intelligence, Networking, and Parallel/distr ibuted Computing, July 2007; 2:683-8.
- Liu H. J., Wang Z. X., Li S. F., Yi M. Study on the performance of spectrum mobility in cognitive wireless network. Proceedings of 11th IEEE International Conference on Communication Systems (ICCS), 2008: 1010-4.
- ITU-T Recommendations. Terms and definitions related to Quality of Service and network performance including dependability. ITU-T Recommendation E.800, August 1994.
- ETSI. Network aspects (NA): general aspects of Quality of Service and network performance. ETSI Technical Report, ETR 003, 2nd Edition, October 1994.
- ETSI. Satellite earth stations and systems, broadband satellite multimedia IP. IP Internet working over Satellite: Performance, Availability and Quality of Service, March 2003, ETSI Technical Report.
- Hardy W. C. QoS measurement and evaluation of telecommunications Quality of Service. John Wiley and Sons, England, 2001.
- Nguyen D., Tran L., Pirinen P., and Latvaaho M. On the spectral efficiency of full-duplex small cell wireless systems. IEEE Trans. Wireless Communication, Sept. 2014; 13(9): 4896-910.
- Lu X., Wang P., Niyato D., Kim D.I., and Han Z. Wireless Networks with RF Energy Harvesting: A Contemporary Survey. IEEE Communications Surveys & Tutorials, May 2015; 17(2):757-89.
- Hoang D.T., Niyato D., Wang P., and Kim D. I. Opportunistic Channel Access and RF Energy Harvesting in Cognitive Radio Networks. IEEE Trans. on Selected Areas in Communications, Nov. 2014; 32(11): 1-14.
- Akyildiz I.F., Lee W.Y., Vuran M.C., Mohanty S. Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Computer Networks (Elsevier), 2006; 50:2127–59.
- Attar A., Ghorashi S. A., Sooriyabandara M. and Aghvami A.H. Challenges of real-time secondary usage of spectrum. Computer Networks (Elsevier), 2008; 52 (4): 816-30.
- Boulogeorgos A.-A. A., Sofotasios P. C., Selim B., Muhaidat S., Karagiannidis G. K., and Valkama M. Effects of RF impairments in communications over cascaded fading channels. IEEE Transactions on Vehicular Technology, 2016; 65(11): 1-17.
- Li B., Sun M., Li X., Nallanathan A., and Zhao C. Energy Detection based Spectrum Sensing for Cognitive Radios over Time-Frequency Doubly Selective Fading Channels. IEEE Transactions on signal processing, Jan. 2015; 63(2): 402-17.
- Walke B. H. Mobile Radio Networks: Networking and protocols. 2nd Edition, 1999.
- Garg K. Wireless Networks Evolution: 2G to 3G. Reprint 2003.
- Liao Y., Wang T., Song L., Han Z. ListenandTalk: Protocol Design and Analysis for Full-duplex Cognitive Radio Networks. IEEE Trans. on Vehicular Technology, Jan. 2017; 66(1): 656-67.
- Sharma S. K., Bogale T. E., Le L. B., Chatzinotas S., Wang X., Ottersten B. TwoPhase Concurrent Sensing and Transmission Scheme for Full Duplex Cognitive Radio. in Proc. IEEE VTC Spring, Sept. 2016.
- Altrad O., Muhaidat S., Al-Dweik A. S., and Yoo P. Opportunistic spectrum access in cognitive radio networks under imperfect spectrum sensing. IEEE on Vehicular Technology, Feb. 2014; 63(2): 920–5.
- Lee W. Y. and Akyildiz I. F. Optimal spectrum sensing framework for cognitive radio networks. IEEE Transactions on Wireless Communications, 2008; 7(10): 3845-57.
- Qiao X., Tan Z. and Li J. Combined optimization of spectrum handoff and spectrum sensing for cognitive radio systems. 7th IEEE International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), 2011:1-4.
- Ghasemi A. and Sousa E. S. Spectrum sensing in cognitive radio networks: requirements, challenges and design trade-offs.IEEE Communications Magazine, April 2008; 46(4): 32-9.
- Baroudi U. and Alfadhly A. Effects of mobility and primary appearance probability on spectrum handoff. 73rd IEEE Vehicular Technology Conference (VTC spring), 2011: 1-6.
- Li P., Scalabrino N. and Fang Y. How to effectively use multiple channels in wireless mesh networks. IEEE Transactions on Parallel and Distributed Systems, 2009; 20(11): 1641-52.
- Avallone S. and Stasi G. D. An experimental study of the channel switching cost in multichannel wireless mesh networks. IEEE Communications magazine, Sep. 2013; 51(9): 124-34.
- Afifi W. and Krunz M. Incorporating selfinterference suppression for full-duplex operation in opportunistic spectrum access systems. IEEE Trans. Wireless Commun., Apr. 2015;14(4): 2180-91.
- Rabbachin A., Quek T. Q. S., Shin H. and Win M. Z. Cognitive network interference. IEEE Journal on Selected Areas in Communications, 2011; 29(2): 480-93.
- Xing Y. and Chandramouli R. QoS constrained secondary spectrum shar ing. IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), Nov. 2005: 658-61.
- Fuzzy Rule Based Quality of Service Provisioning in Cognitive Radio Network
Abstract Views :150 |
PDF Views:0
Authors
Affiliations
1 College of Agricultural Engineering and Technology, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir, Srinagar, J&K, IN
2 Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir, Srinagar, J&K, IN
1 College of Agricultural Engineering and Technology, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir, Srinagar, J&K, IN
2 Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir, Srinagar, J&K, IN
Source
Oriental Journal of Computer Science and Technology, Vol 11, No 1 (2018), Pagination: 55-63Abstract
Cognitive radio (CR) is a novel technology to resolve the issue of under-utilization of wireless spectrum. Quality of service (QoS) provisioning in CR networks to large number of traffic as per their need is not an easy task since no wireless spectrum is available on permanent basis for its operation. In this paper, few critical QoS parameters namely dynamic-availability-of-idle- channels (avail-idle-channel), expected-holding-time-of-idle-channel (HT-idle-channel) and user-mobility are chosen to analyze their impact over quality of service of the communicating cognitive users using rule-based fuzzy decision-making system. The results indicate the relationship of chosen parameters over the QoS of the communicating cognitive users.Keywords
Cognitive Radio, Quality of Service (QoS), Fuzzy Logic.Full Text
References
- FCC, Notice of proposed rulemaking and order, No. 03-222 , Dec. 2003.
- Mitola J. Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio. Ph.D. Dissertation: KTH Royal Institute of Technology; 2000.
- Arslan H. Cognitive radio, software defined radio, and adaptive wireless systems. Springer, 2007(e-book).
- Liao Y., Wang T., Song L., Han Z. ListenandTalk: Protocol Design and Analysis for Full-duplex Cognitive Radio Networks. IEEE Trans. on Vehicular Technology, Jan. 2017; 66(1): 656-67.
- Sharma S. K., Bogale T. E., Le L. B., Chatzinotas S., Wang X., Ottersten B. TwoPhase Concurrent Sensing and Transmission Scheme for Full Duplex Cognitive Radio. in Proc. IEEE VTC Spring, Sept. 2016.
- Boulogeorgos A.-A. A., Sofotasios P. C., Selim B., Muhaidat S., Karagiannidis G. K., and Valkama M. Effects of RF impairments in communications over cascaded fading channels. IEEE Transactions on Vehicular Technology, 2016; 65(11): 1-17.
- Li B., Sun M., Li X., Nallanathan A., and Zhao C. Energy Detection based Spectrum Sensing for Cognitive Radios over Time-Frequency Doubly Selective Fading Channels. IEEE Transactions on signal processing, Jan. 2015; 63(2): 402-17.
- Afifi W. and Krunz M. Incorporating selfinterference suppression for full-duplex operation in opportunistic spectrum access systems. IEEE Trans. Wireless Commun., Apr. 2015;14(4): 2180-91.
- Fu X., Zhou W., Xu J., Song J. Extended mobility management challenges over cellular networks combined with cognitive radio by using multi-hop network. Proceedings of International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/distributed Computing, July 2007; 2:683-8.
- Liu H. J., Wang Z.X., Li S.F., Yi M. Study on the performance of spectrum mobility in cognitive wireless network. Proceedings of 11th IEEE International Conference on Communication Systems (ICCS), 2008: 1010-4.
- ITU-T Recommendations. Terms and definitions related to Quality of Service and network performance including dependability. ITU-T Recommendation E.800, August 1994.
- ETSI. Network aspects (NA): general aspects of Quality of Service and network performance. ETSI Technical Report, ETR 003, 2nd Edition, October 1994.
- ETSI. Satellite earth stations and systems, broadband satellite multimedia IP. IP Internetworking over Satellite: Performance, Availability and Quality of Service, March 2003, ETSI Technical Report.
- Hardy W. C. QoS measurement and evaluation of telecommunications Quality of Service. John Wiley and Sons, England, 2001.
- Dahi S, Tabbane S. Radio resource management on the basis of temporal characterization of spectrum holes in cognitive radio networks. Proceedings of 14th International Symposium on Wireless Personal Multimedia Communication (WPMC), 2011: 1-5.
- Le H-S. T. and Liang Q. An Efficient Power Control Scheme for Cognitive Radios. Proceedings of Wireless Communications & Networks Conference (WCNC), 2007; 255963.
- Baldo N. and Zorzi M. Fuzzy Logic for Cross Layer Optimization in Cognitive Radio Networks. EEE Communication Magazine,2008; 64-72.
- Le H-S T. and Ly H. D. Opportunistic Spectrum Access using Fuzzy Logic for Cognitive Radio Networks. 2nd International Conference on Communications and Electronics (ICCE),2008; 240-5.
- Kaur P., Moin Uddin and Khosla A. Fuzzy Based Adaptive Bandwidth Allocation Scheme in Cognitive Radio Networks. International Conference on ICT and Knowledge Engineering, 2010; 41-5.
- Giupponi L. and Perez-Neira A.I. Fuzzy Based Spectrum Handoff in Cognitive Radio Networks. 3rd International Conference. on Cognitive Radio Oriented Wireless Networks and Communications CrownCom, 2008: 1-6.
- Lala Nisar A., Moin Uddin and Sheikh N. A. Novel Spectrum Handoffin Cognitive Radio Networks Using Fuzzy Logic. International Journal of Information Technology and computer Science, 2013; 5(11): 103-10.
- Wanbin T. and Dong P. Spectrum Handoff in Cognitive Radio with Fuzzy Logic Control. Journal of Electronics (China), 2010; 70814.
- Lala Nisar A., Moin Uddin and Sheikh N. A. Identification and Integration of QoS parameters in Cognitive Radio Networks using Fuzzy Logic. International Journal of Emerging Sciences,2013; 3(3): 279-88.
- Lala Nisar A., Moin Uddin and Sheikh N. A. A Novel Algorithm for Estimation of QoS in Cognitive Radio Using Fuzzy Logic.International Journal of Information Technology and Electrical Engineering,2013; 2(5):1-5.
- Lala Nisar A., Balkhi Altaf A., Mir G.M. and Simnani R.A. Quality of Service Provisioning in Cognitive Radio Network. Oriental Journal of Computer Science & Technology, 2017; 10(4): 780-7.
- Hong D. and RappaportS. S. Traffic model and performance analysis for cellular mobile radio telephone systemswith prioritized and non-prioritized handoff procedure. IEEE Transactions on Vehicular Technology, 1986; VT-35(3): 448-61.
- Stojmenovic I. Handoff of Wireless Networks and Mobile Computing. Wiley India Edition, 2002.