Performance evaluation of LTE scheduling techniques for heterogeneous traffic and different mobility scenarios

In this paper five scheduling algorithms were investigated and their performance was evaluated in terms of Fairness Index, Peak Throughput, Average Throughput and Edge Cell User Throughput. A system level MATLAB simulator was used. The simulation takes into account different types of traffic for several mobility scenarios and propagation channel models. Results indicate that the scheduling algorithms showed some quality in certain parameter of evaluation but lack in other terms. While some scheduling algorithm take the moderate path but still be lacking especially in Edge Cell User Throughput necessitating the use of Relays or femtocells

Enhanced exponential rule scheduling algorithm for real-time traffic in LTE network

Nowadays, mobile communication is growing rapidly and become an everyday commodity. The vast deployment of real-time services in Long Term Evolution (LTE) network demands for the scheduling techniques that support the Quality of Service (QoS) requirements. LTE is designed and implemented to fulfill the users’ QoS. However, 3GPP does not define the specific scheduling technique for resource distribution which leads to vast research and development of the scheduling techniques. In this context, a review of the recent scheduling algorithm is reported in the literature. These schedulers in the literature cause high Packet Loss Rate (PLR), low fairness, and high delay. To cope with these disadvantages, we propose an enhanced EXPRULE (eEXPRULE) scheduler to improve the radio resource utilization in the LTE network. Extensive simulation works are carried out and the proposed scheduler provides a significant performance improvement for video application without sacrificing the VoIP performance. The eEXPRULE scheduler increases video throughput, spectrum efficiency, and fairness by 50%, 13%, and 11%, respectively, and reduces the video PLR by 11%

Planning and optimisation of 4G/5G mobile networks and beyond

As mobile networks continue to evolve, two major problems have always existed that greatly affect the quality of service that users experience. These problems are (1) efficient resource management for users at the edge of the network and those in a network coverage hole. (2) network coverage such that improves the quality of service for users while keeping the cost of deployment very low. In this study, two novel algorithms (Collaborative Resource Allocation Algorithm and Memetic-Bee-Swarm Site Location-Allocation Algorithm) are proposed to solve these problems. The Collaborative Resource Allocation Algorithm (CRAA) is inspired by lending and welfare system from the field of political economy and developed as a Market Game. The CRAA allows users to collaborate through coalition formation for cell edge users and users with less than the required Signal-to-Noise-plus-Interference-Ratio to transmit at satisfactory Quality of Service, which is a result of the payoff, achieved and distributed using the Shapley value computed using the Owens Multi Linear Extension function. The Memetic-Bee-Swarm Site Location-Allocation Algorithm (MBSSLAA) is inspired by the behaviour of the Memetic algorithm and Bee Swarm Algorithm for site location. Series of System-level simulations and numerical evaluations were run to evaluate the performance of the algorithms. Numerical evaluation and simulations results show that the Collaborative Resource Allocation Algorithm compared with two popular Long Term Evolution-Advanced algorithms performs higher in comparison when assessed using throughput, spectral efficiency and fairness. Also, results from the simulation of MBSSLAA using realistic network design parameter values show significant higher performance for users in the coverage region of interest and signifies the importance of the ultra-dense small cells network in the future of telecommunications’ services to support the Internet of Things. The results from the proposed algorithms show that following from the existing solutions in the literature; these algorithms give higher performance than existing works done on these problems. On the performance scale, the CRAA achieved an average of 30% improvement on throughput and spectral efficiency for the users of the network. The results also show that the MBSSLAA is capable of reducing the number of small cells in an ultra-dense small cell network while providing the requisite high data coverage. It also indicates that this can be achieved while maintaining high SINR values and throughput for the users, therefore giving them a satisfactory level of quality of service which is a significant requirement in the Fifth Generation network’s specification