Urgency-aware scheduling algorithm for downlink cognitive long term evolution-advanced - Mohd Ramli, Huda Adibah; Mohd. Isa, Farah Nadia; Asnawi, Ani Liza; Jusoh, Ahmad Zamani; Azman, Amelia Wong (IEEE, 2019)
Long Term Evolution-Advanced experiences an increasing demand for more radio spectrums to support the escalating demands of Real-Time (RT) and Non Real-Time (NRT) multimedia contents. However most usable radio spectrums have already been licensed. A number of studies reported that some portions of licensed radio spectrums are underutilized. To support the demand for more radio spectrums, cognitive LTE-Advanced that aggregates the LTE-Advanced current radio spectrums with the underutilized licensed radio spectrums from another system via cognitive radio is introduced. Given that packet scheduling is important in meeting the required Quality of Service (QoS) of multimedia contents, this paper proposes an Urgency-Aware Scheduling (UAS) algorithm for use in the downlink cognitive LTE-Advanced. The UAS algorithm takes the required QoS of a user, urgency of each packet, average achievable data rate and average throughput when selecting users to receive packets. Simulation results demonstrate that the proposed algorithm can significantly optimize the number of cognitive LTE-Advanced users with satisfactory RT QoS whilst having acceptable QoS for the NRT packets