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The Long Term Evolution (LTE) as a mobile broadband technology supports awide domain of communication services with different requirements. Therefore,scheduling of all flows from various applications in overload states in whichthe requested amount of bandwidth exceeds the limited available spectrumresources is a challenging issue. Accordingly, in this paper, a greedyalgorithm is presented to evaluate user candidates which are waiting forscheduling and select an optimal set of the users to maximize systemperformance, without exceeding available bandwidth capacity. Thegreedy-knapsack algorithm is defined as an optimal solution to the resourceallocation problem, formulated based on the fractional knapsack problem. Acompromise between throughput and QoS provisioning is obtained by proposing aclass-based ranking function, which is a combination of throughput and QoSrelated parameters defined for each application. The simulation results showthat the proposed method provides high performance in terms of throughput, lossand delay for different classes of QoS over the existing ones, especially underoverload traffic.

Greedy-Knapsack Algorithm for Optimal Downlink Resource Allocation in LTE Networks