An Efficient and Adaptive Bandwidth Allocation Scheme for Mobile Wireless Networks Using an On-Line Local Estimation Technique

Abstract

The next generation of mobile wireless networks has to provide the quality-of-service (QoS) for a variety of applications. One of the key generic QoS parameters is the call dropping probability, which has to be maintained at a predefined level independent of the traffic condition. In the presence of bursty data and the emerging multimedia traffic, an adaptive and dynamic bandwidth allocation is essential in ensuring this QoS. The paradox, however, is that all existing dynamic bandwidth allocation schemes require the prior knowledge of all traffic parameters or/and user mobility parameters. In addition, most proposals require extensive status information exchange among cells in order to dynamically readjust the control parameters, thus making them difficult to be used in actual deployment.

In this paper, we introduce a novel adaptive bandwidth allocation scheme which estimates dynamically the changing traffic parameters through local on-line estimation. Such estimations are restricted to each individual cell, thus completely eliminating the signaling overhead for information exchange among cells. Furthermore, we propose the use of a probabilistic control policy, which achieves a high channel utilization, and leads to an effective and stable control. Through simulations, we show that our proposed adaptive bandwidth allocation scheme can guarantee the predetermined call dropping probability under changing traffic conditions while at the same time achieving a high channel utilization.