Multiple QoS provisioning with pre-emptive priority schedulers in multi-resource OFDMA networks

Abstract

In this paper, we present an analytical framework for the performance evaluation of a pre-emptive priority scheduler in multi-resource networks, like those using Orthogonal Frequency Division Multiple Access (OFDMA). We focus on Quality of Service (QoS)-guaranteed traffic for which QoS is guaranteed to individual users by restricting the number of admitted users. For this, the QoS-constrained capacity, in terms of the number of supported users, needs to be ascertained a priori. The QoS-constrained capacity is a function of users’ QoS requirements, channel conditions, and radio resource allocation algorithms, which in this work is the pre-emptive priority scheduler. It is, thus, a variable quantity and mostly obtained using time-consuming offline computer simulations. Mathematical models, on the other hand, are timely and accurate, allowing the capacity to be derived in real-time as a function of the current network configuration. Existing works on mathematical modelling of pre-emptive priority schedulers have mostly focussed on single servers or multiple servers where a single server is assigned to each user. In contrast, OFDMA networks have multiple radio resources, i.e., multiple servers and each user may need more than one radio resource for a single packet transmission, i.e. it is a multi-resource system, which has been accounted for in this paper. We classify the users based on their resource requirements and model the pre-emptive priority scheduler as a multi-class, multi-server, multi-resource, non-work conserving queueing system. We derive its QoS metrics like average delay, packet drop probability, throughput, etc., from its continuous-time Markov Chain. We then use the derived QoS metrics to obtain the QoS-constrained capacity and design a threshold based predictive call admission control unit. We have validated the results using extensive discrete event simulations.