Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2010
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2010
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2010
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

A Grey-Fuzzy Controller For Optimization Technique In Wireless Networks

Authors: Yao-Tien Wang; Hsiang-Fu Yu; Chiou, Dung Chen;

A Grey-Fuzzy Controller For Optimization Technique In Wireless Networks

Abstract

{"references": ["\"http://www.3gpp.org\", 2002.", "H. Holma and A. Toskala (eds.), WCDMA for UMTS. Wiley, 2000.", "3rd Generation Partnership Project Technical Specification Group Radio\nAccess Network. Working Group 1, \"Physical Layer - Measurements.\"\nTS25.225 v4.0.0. 2001.", "3rd Generation Partnership Project. Technical Specification Group. Radio\nAccess Network \"Radio Interface Protocol Architecture.\" TS25.301\nv4.2.0. 202.", "3rd Generation Partnership Project. Technical Specification Group. Radio\nAccess Network \"Radio Resource Control (RRC); Protocol\nSpecification.\" TS25.331\" 4.4.0, 2002.", "S. K. Das, S. K. Sen and R. Jayaram, A structured channel borrowing\nscheme for dynamic load balancing in cellular networks, IEEE\nDistributed Computing Systems Conference, pages 116-123, 1997.", "J. Kim, T. Lee, and C. S. Hwang, A dynamic channel assignment scheme\nwith two thresholds for load balancing in cellular networks, IEEE Radio\nand Wireless Conference, pages 141-145, 1999.", "X. Dong and T. H. Lai, Distributed dynamic carrier allocations in mobile\ncellular networks: search vs. update, IEEE Distributed Computing\nSystems Conference, pages 108-115, 1997.", "T. Lee, J. Kim, and C. S. Hwang, A dynamic channel assignment scheme\nwith two thresholds for load balancing in cellular networks, IEEE Radio\nand Wireless Conference, pages 141-145, 1999.\n[10] H. Jiang and S. S. Rappaport, CBWL: a new channel assignment and\nsharing method for cellular communication systems, IEEE Transactions\non Vehicular Technology, pages 313 -322, 1994.\n[11] S. Kim and P. K. Varshney, Adaptive Load Balancing with Preemption\nfor Multimedia Cellular Network, IEEE Wireless Communications and\nNetworking Conference, pages 1680-1684, 2003.\n[12] T. S. Yum and M. Zhang, Comparisons of channel-assignment strategies\nin cellular mobile telephone systems, IEEE Transactions on Vehicular\nTechnology, pages 211-215, 1989.\n[13] Y. -T. Wang and J.-P. Sheu, A Dynamic Channel Borrowing Approach\nwith Fuzzy Logic Control in Distributed Cellular Networks, the special\nissue of Simulation Modeling Practice and Theory, Vol. 12, pages 287 -\n303, 2004.\n[14] Y. T. Wang, A Fuzzy-Based Dynamic Channel Borrowing Scheme for\nWireless Cellular Networks, IEEE Vehicular Technology Conference,\npages 1517-1521, 2003.\n[15] L. A. Zadeh, Fuzzy Algorithm. Information and Control, pages 94-102,\n1968.\n[16] Y. Zhang, A new adaptive channel assignment algorithm in cellular\nmobile systems, IEEE Systems Sciences Conference, pages 1-7, 1999.\n[17] J. S. Engel and M. Peritsky, Statistically-optimum dynamic sever\nassignment in systems with interfering severs, IEEE Vehicular\nTechnology Conference, pages 1287-1293, 1973.\n[18] H. Haas and S. McLaughlin, A novel decentralized DCA concept for a\nTDD network applicable for UMTS. IEEE Transactions on Vehicular\nTechnology, pages 881-885, 2001.\n[19] J. Karlsson and B. Eklundh, A cellular mobile telephone system with load\nsharing-an enhancement of directed retry, IEEE Transactions on\nCommunications, pages 530-535, 1989.\n[20] S. Mitra and S. DasBit, A load balancing strategy using dynamic channel\nassignment and channel borrowing in cellular mobile environment, IEEE\nPersonal Wireless Communications Conference, pages 278-282, 2000.\n[21] J. L. Deng , Control problem of grey systems, System and Control Letters,\nVol. 1, pages 288-294, 1982.\n[22] Ren C. Luo and Tse Min Chen , Autonomous Mobile Target Tracking\nSystem Based on Grey-Fuzzy Control Algorithm, IEEE Transactions on\nIndustrial Electronics, VOL. 47, NO. 4, pages 920-931, 2000.\n[23] C.-Y. Kung, K.-T. Hsu, T.-M. Yan and P.-W. Liu, An Application of the\nGrey Prediction Theory to the Annual Medical Expense of Taiwan-s\nNational Health Insurance, Journal of Grey System, Vol. 9, No. 2, pages\n75-86, 2006.\n[24] W.-N. Pi and L.-C. Liou, Electric Power Demand Forecasting in Taiwan\nvia Grey Prediction, Journal of Science and Engineering Technology,\nVol. 3, No. 2, pages 11-18, 2007.\n[25] Y.-T. Wang and K.-M. Hung \"Fuzzy Logic Based Neural Network Model\nfor Load Balancing in Wireless Networks. \" KICS Communications\nSociety, International Journal of Communications and Networks, Vol. 10,\npp.38- 43, 2008."]}

In wireless and mobile communications, this progress provides opportunities for introducing new standards and improving existing services. Supporting multimedia traffic with wireless networks quality of service (QoS). In this paper, a grey-fuzzy controller for radio resource management (GF-RRM) is presented to maximize the number of the served calls and QoS provision in wireless networks. In a wireless network, the call arrival rate, the call duration and the communication overhead between the base stations and the control center are vague and uncertain. In this paper, we develop a method to predict the cell load and to solve the RRM problem based on the GF-RRM, and support the present facility has been built on the application-level of the wireless networks. The GF-RRM exhibits the better adaptability, fault-tolerant capability and performance than other algorithms. Through simulations, we evaluate the blocking rate, update overhead, and channel acquisition delay time of the proposed method. The results demonstrate our algorithm has the lower blocking rate, less updated overhead, and shorter channel acquisition delay.

Keywords

radio resource management, fuzzylogic control, wireless networks, quality of service., grey prediction

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 2
    download downloads 3
  • 2
    views
    3
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
2
3
Green