Adaptive Resource Management in Mobile Wireless Networks Using Feedback Control Theory

Abstract

Emerging mobile wireless networks are characterized by significant uncertainties in mobile user population and system resource state. Such networks require adaptive resource management that continuously monitor the system and dynamically adjust resource allocations for adherence to the desired system performance requirements. We propose adaptive resource management technique based on control theory. The controller dynamically solves resource allocation problem using feedback control laws. In the base algorithm, the number of guard channels is dynamically adjusted by feeding back the current handoff call dropping probability. The base algorithm is then enhanced in two ways: feeding back the instantaneous number of handoff calls and by probabilistically implementing a fractional number of guard channels. We study the effects of parameter choices on the performance of the proposed algorithms using discrete event simulation. Simulation results indicate that the feedback controllers can guarantee the predetermined call dropping probability under a variety of traffic conditions, and so can utilize the scarce wireless resource efficiently by accepting more new calls.