Performance improvement of LTE and LTE advanced networks

Abstract

It has been a decade with Long Term Evolution (LTE) as mobile radio access technology (RAT) and in this, period it became the favoured broadband communication technology. LTE, as a 3rd Generation Project Partnership (3GPP) technology, has entered the frozen stage, no future enhancement beyond release 14 only minor revisions. While over the same time, the revolution in mobile handsets, and internet of thing (IoT) "connected devices" have expedited the surge in desire for more data resources, which are ubiquitous. Undoubtedly LTE as a technology has been the most dominant wireless medium, in transporting broadband services for both voice and data. Thus the efficient operations of an LTE Heterogeous network(HetNets) are of ultimate importance, both in terms of the load balance and the performance delivered to users. The packet scheduling is an advanced radio resource management (RRM) mechanism, which plays a key fundamental role in the delivery of time-frequency resources to users in uplink and downlink. Thus the operation of the packet scheduler determines the overall LTE network performance and also the services level for the user's example (e.g.) the quality of service (QoS), throughput. In this study, two packet algorithm schemes were proposed, firstly one that focuses on modulation and coding scheme(MCS), fairness and QoS called Flexible Fair Allocation Scheme (FFAS). It was evaluated with contemporary algorithms Least Load and Greedy algorithm. The results for FFAS were superior for both simulations scenarios. The second proposed packet scheduling algorithm area of focus was with massive machine type communication (MTC) for HetNets. Where the PR-M2M scheduler was proven to deliver superior outcomes in distributing resources for a human to human(H2H) as well as for Device to device(D2D) communication. The simulations were piloted in Matlab using the Vienna LTE Downlink System simulator, where we were able to conduct diverse network analysis. The network simulations produced outcomes which indicated FFAS and PR-M2M are the best algorithms for LTE Advanced networks. In conclusion, it should be noted while access to additional spectrum is an issue, optimal uti-lization of current license spectrum is of utmost importance. With carrier aggregation as an LTE Advanced feature, operators are able to efficiently use the available spectrum. The sched-uling algorithms proposed plays a pivotal roll in controlling how the resources are distributed to users. Therefore these two scheduling schemes will be contributing to improved performance of LTE Advanced networks.