Abstract

Spectral efficiency has improved significantly with the deployment of beyond third generation (3G) cellular air interfaces. However, the scarcity of unallocated radio spectrum bands, coupled with the need to provide ubiquitous wireless data services with different Quality of Service (QoS) requirements to a large number of users, has continued to drive extensive research efforts in radio resource management (RRM). In order to adapt to the changing wireless channel conditions and meet the varying and diverse QoS requirements, much of the published work in RRM has focused on exploiting multi-user and multi-channel diversities and more recently on exploiting multi-application diversity to take advantage of the mechanisms and optimization features introduced in the air interfaces. In this paper, we propose a bitQoS-aware resource allocation framework to increase the flexibility and granularity of the resource allocation algorithms by adaptively matching the QoS requirements of the user application bits to the characteristics of the Orthogonal Frequency Division Multiplexing (OFDM) subcarriers in a mixed-traffic environment. We show through an adaptive joint subcarrier, power and bit allocation algorithm, that with the finesse control of bitQoS-aware scheduling, it is possible to simultaneously achieve both an increase in user throughput and a reduction in user packet drop probability by accepting a within scheduling delay threshold increase in user latency. The performance gains obtainable are quantified in terms of system throughput, user throughput, user latency, user jitter and user packet drop probability for systems under different traffic loads.

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