An intelligent scheduling architecture for mixed traffic in LTE-Advanced

In this paper an intelligent scheduling architecture is presented for LTE-Advanced downlink transmission, to enhance the Quality of Service (QoS) provision to different traffic types while maintaining system level performance in such as system throughput. Hebbian learning process and K-mean clustering algorithm are integrated in the Time Domain (TD) of scheduling architecture, to intelligently allocate available radio resources to Real Time (RT) and Non Real Time (NRT) traffic, and to prioritise RT users based on their Packet Drop Rate (PDR) feedback. The integration of these algorithms allows just enough resource allocation to RT traffic and diverts extra resources to NRT traffic, to fulfill its minimum throughput requirements. System level simulation is set up for system level performance evaluation. Simulation results show that the proposed architecture reduces average delay, delay violation probability and average Packet Drop Rate (PDR) of RT traffic while guaranteeing the support of minimum throughput to NRT traffic and maintains system throughput at good level.