Predictive schemes for handoff prioritization in cellular networks based on mobile positioning

    Authors

    M. H. Chiu;M. A. Bassiouni

    Comments

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    Abbreviated Journal Title

    IEEE J. Sel. Areas Commun.

    Keywords

    cellular networks; channel allocation; handoff blocking; handoff; prioritization; simulation of cellular networks; CHANNEL ASSIGNMENT; PERFORMANCE; SYSTEMS; MANAGEMENT; Engineering, Electrical & Electronic; Telecommunications

    Abstract

    In this paper, we propose and evaluate new schemes For channel reservation motivated by the rapidly evolving technology of mobile positioning, The schemes, called predictive channel reservation (PCR), work by sending reservation requests to neighboring cells based on extrapolating the motion of mobile stations (MS's), A number of design enhancements are incorporated to minimize the effect of false reservations and to improve the throughput of the cellular system. These enhancements include: 1) reservation pooling; 2) queuing of reservation requests; 3) hybrid approach for integrating guard channels (GC's); and 4) using a threshold distance (TD) to control the timing of reservation requests. The design enhancements have produced a set of highly efficient schemes that achieve significant reduction in handoff blocking rates while only incurring remarkably small increases in the new call blocking rates. The PCR approach has also been used to solve the MINBLOCK optimization problem and has given significant improvement over the fractional guard channel (FGC) protocol. Detailed performance results of the different variations of the PCR scheme and comparisons with conventional channel reservation schemes are presented. An analytical Markov model for the hybrid predictive version of the scheme is developed and its applicability and numerical results are discussed.

    Journal Title

    Ieee Journal on Selected Areas in Communications

    Volume

    18

    Issue/Number

    3

    Publication Date

    1-1-2000

    Document Type

    Article

    Language

    English

    First Page

    510

    Last Page

    522

    WOS Identifier

    WOS:000086706800019

    ISSN

    0733-8716

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