A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 6 Issue 3
May  2019

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Satish Kumar, Rajesh Devaraj and Arnab Sarkar, "A Hybrid Offline-Online Approach to Adaptive Downlink Resource Allocation Over LTE," IEEE/CAA J. Autom. Sinica, vol. 6, no. 3, pp. 766-777, May 2019. doi: 10.1109/JAS.2018.7511105
Citation: Satish Kumar, Rajesh Devaraj and Arnab Sarkar, "A Hybrid Offline-Online Approach to Adaptive Downlink Resource Allocation Over LTE," IEEE/CAA J. Autom. Sinica, vol. 6, no. 3, pp. 766-777, May 2019. doi: 10.1109/JAS.2018.7511105

A Hybrid Offline-Online Approach to Adaptive Downlink Resource Allocation Over LTE

doi: 10.1109/JAS.2018.7511105
Funds:  This work was partially supported by TATA Consultancy Services (TCS), India, through TCS Research Fellowship Program
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  • Radio resource management mechanisms in current and future wireless networks is expected to face an enormous challenge due to the ever increasing demand for bandwidth and latency sensitive applications on mobile devices. This is because an optimal resource allocation scheme which attempts to multiplex the available bandwidth in order to maximize Quality of service (QoS), will pose an exponential computational burden at eNodeB. In order to minimize such computational overhead, this work proposes a hybrid offline-online resource allocation strategy which effectively allocates all the available resources among flows such that their QoS requirements are satisfied. The flows are firstly classified into priority buckets based on real-time criticality factors. During the offline phase, the scheduler attempts to maintain the system load within a pre-specified safe threshold value by selecting an appropriate number of buckets. This offline selection procedure makes use of supervisory control theory of discrete event systems to synthesize an offline scheduler. Next, we have devised an online resource allocation strategy which runs on top of the offline policy and attempts to minimize the impact of the inherent variability in wireless networks. Simulation results show that the proposed scheduling framework is able to provide satisfactory QoS to all end users in most practical scenarios.

     

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