In LTE, bandwidth resources allocation became a huge burden to be handled, as both of RT and NRT traffic should be processed fairly to satisfy their diverse QoS requirements. To tackle this issue in particular, in this work, we propose a fairness-based resources allocation method named Frame-based Game Theory (FGT), which can be flexibly implemented as an upper level in LTE downlink MAC layer; before the PRBs allocation function. Basically, FGT aim is to allow involved classes with different QoS requirements to fairly gain a part of the available channel resources to transmit their flows. Adhere, on every LTE-frame, a cooperative game scenario is designed. Wherein, Shapley formula is used to distribute the available amount of data within RT and NRT traffic classes. Then, conforming to these assigned resources portions to each traffic class, PRBs allocation process is triggered every TTI for the selected flows. In this work, we adopted some of the recent PRBs allocation methods as a lower level scheduler in order to illustrate a complete idea of MAC layer scheduling functions, and also to effectively evaluate FGT performance. Simulation results on various scenarios show that, fairness index for flows from different classes is increased when FGT is considered. The results also conveyed outperforming QoS indices for FGT on RT and NRT service in terms of throughput, PLR, as well as cell spectrum efficiency.

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Guaranteeing Quality of Service (QoS) for heterogeneous traffic is a major challenge in the Fourth Generation (4G) mobile networks. Therein, the absence of sophisticated resources allocation process at the base station jeopardizes QoS in terms of latency data transfer. It has been observed from the literature that low delay bounds might be ensured, however, at the expense of other QoS aspects; for example, throughput and data loss. Therefore, in this article, we propose an effective Delay-based and QoS-Aware Scheduling (DQAS) scheme with a low complexity overhead as an efficient solution for the resource allocation issue in LTE Medium Access Control (MAC) layer. The ultimate aim of DQAS is to minimize delay for Real-Time (RT) traffic while still offering a good level of QoS. Complying with QoS of different traffic types, we effectively analyze the queue buffer of each user flow by developing an algorithm called Efficient Delay Control (EDC) that weights each flow priority in terms of delay. Then, this weight is utilized as a principle for the scheduling decision on the attending flows. Furthermore, the Least Delay Increase (LDI) algorithm is developed to tune the scheduler behavior to maintain a balance between delay and system throughput. Simulation results considering different user mobility levels reveal that DQAS significantly guarantees a low end-to-end delay trend that is independent of increased RT load, and moreover, a reasonable throughput and data drop levels compared to other existing schedulers.

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