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Development of Coverage Based Cell Selection Algorithm For WiMAX

Publication Type : Journal Article

Publisher : Journal of Theoretical and Applied Information Technology (JTAIT)

Source : Journal of Theoretical and Applied Information Technology (JTAIT), 10th August 2014, Vol. 66, No.1, ISSN: 1992-8645 E-ISSN: 1817-3195.

Url : https://www.researchgate.net/publication/289654640_Development_of_coverage_based_cell_selection_algorithm_for_WiMAX

Campus : Coimbatore

School : School of Physical Sciences

Department : Mathematics

Year : 2014

Abstract : Fourth generation (4G) mobile systems focus on effortlessly incorporating the existing wireless technologies like GSM, wireless LAN, and Bluetooth. This contrasts with third generation (3G), which simply focuses on developing new standards and hardware. WiMAX have been rapidly emerging in the last few years. The mobile subscriber and traffic volume have been largely increased in WiMAX. During the stage of network planning, a cell capacity and size are typically fixed depends on the calculation of peak traffic load. Cell planning is one of the most basic problems in network design. In this paper, a development of Coverage Based Cell Selection (CBCS) algorithm for 4G is introduced. The proposed model utilizes the cell selection algorithm. The best coverage base station can be selected based on three criteria: i.e. demand, profit and capacities. The performance of the proposed CBCS algorithm is compared with the four existing approaches like greedy algorithm, Bounded Greedy Weighted Algorithm (BGWA), Call Admission Control (CAC) and Joint Scheduling & Resource Allocation (JSRA). The proposed CBCS algorithm results better network throughput and also provides better bandwidth consumption ratio than the existing approaches.

Cite this Research Publication : Kavitha P., R. Uma Rani, "Development of Coverage Based Cell Selection Algorithm For WiMAX," Journal of Theoretical and Applied Information Technology (JTAIT), 10th August 2014, Vol. 66, No.1, ISSN: 1992-8645 E-ISSN: 1817-3195.

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