Robust resource allocation scheme under channel uncertainties for LTE-A systems

Nowadays, resource allocation is one of the major problems in the cellular networks. Due to the increasing number of autonomous heterogeneous devices in future mobile networks, a proper scheduling scheme is required to provide the adequate resources for the service flow. However, provisioning quality-of-service (QoS) for real-time applications with the constraint on transporting delay is hard to achieve without compromising other QoS parameters. In this paper, an intelligent QoS-aware bandwidth allocation solution is proposed for the uplink traffic when the channel condition is uncertain. The system is designed based on a specific maximum latency assurance for real-time applications as well as considering fairness to the throughput of non-real-time services. The scheduling system employs a channel-aware Kalman filter based interval type-2 fuzzy logic controller to estimate channel uncertainty as well as satisfying the QoS requirements for user equipment. Through simulations, the performance of the proposed system in terms of optimal bandwidth allocation, bandwidth wastage, fairness, jitters, various delays and throughputs for delay sensitive and delay tolerant services is analyzed. The numerical results show that the proposed scheme provides reliable scheduling for real-time services without harming the performance of non-real-time QoS parameters.