Abstract

This paper presents call admission control and bandwidth reservation schemes in wireless cellular networks that have been developed based on assumptions more realistic than existing proposals. In order to guarantee the handoff dropping probability, we propose to statistically predict user mobility based on the mobility history of users. Our mobility prediction scheme is motivated by computational learning theory, which has shown that prediction is synonymous with data compression. We derive our mobility prediction scheme from data compression techniques that are both theoretically optimal and good in practice. In order to utilize resource more efficiently, we predict not only the cell to which the mobile will handoff but also when the handoff will occur. Based on the mobility prediction, bandwidth is reserved to guarantee some target handoff dropping probability. We also adaptively control the admission threshold to achieve a better balance between guaranteeing handoff dropping probability and maximizing resource utilization. Simulation results show that the proposed schemes meet our design goals and outperform the static-reservation and cell-reservation schemes. Paper submitted to Computer Networks. This paper is based on a paper presented at IEEE Infocom 2001, Anchorage, Alaska, April 2001. Technical subject area: call admission control, bandwidth reservation, mobility prediction. Please address all correspondence to Professor Victor Leung at the above address. This work was supported by a grant from Motorola Canada Ltd., and by the Canadian Natural Sciences and Engineering Research Council under grant CRDPJ 223095. Mobility-Based Predictive Call Admission Control and Bandwidth Reservation in Wireless Cellular Networks Yu 1 I.

Citations