Efficient Load Balancing Algorithm in Long Term Evolution (LTE) Heterogeneous Network Based on Dynamic Cell Range Expansion Bias

The traditional scheme for load balancing in a homogeneous Long Term Evolution (LTE) Network where User Equipment (UEs) associate to a node with the strongest received signal strength is not practical for LTE Heterogeneous Network (LTE HetNet) due to power disparity between the nodes. Therefore, dynamic Cell Range Expansion (CRE) based load-balancing schemes were employed by several scholars to address the challenges in the LTE HetNet. However, the fairness index in achieving the desired average user throughput and UE offloading effect is relatively low. In this work, an efficient load-balancing algorithm for LTE HetNet based on dynamic Cell Range Expansion (CRE) was developed to improve the fairness of the network for the desired throughput and UE offloading effect. The simulation results achieve a throughput gain improvement of up to 11%, while the fairness index improves by 6% compared to the existing algorithm. Further, the UEs offloading effect shows a significant improvement of 3% relative to the existing algorithm. Keywords: Fairness Index; Cell Range Expansion; Load Balancing; LTE Heterogeneous Network; Throughpu

Integration of a genetic optimisation algorithm in a simulation framework for optimising femtocell networks.

The developments in mobile communication systems from 1G to 4G have increased demands on the network due to the increased number of devices and increasing volume of data and 5G is expected to significantly increase demands further. Therefore, networks need to be more efficient to deliver the expected increase in volume. An energy and cost efficient way to cope with such an anticipated increase in the demand of voice and data is the dense deployment of small cells i.e. femtocells. Femtocells are identified as a crucial way to the delivery of the increased demands for heterogeneous networks in which macrocells work in combination with femtocells to provide coverage to offices, homes and enterprise. A survey of the literature is conducted to examine the mechanisms and approaches different authors have used to optimise the network. One of the major activities in this project before the transfer was the identification of the parameters. The literature was analysed and key performance parameters were identified. Based on the identified key performance parameters, a simulation framework is used to perform the experiments and to analyse the performance of a two-tier LTE-A system having femtocell overlays. A comprehensive and easy to use graphical user interface has been set up with the desired two- tier network topologies. It estimates the throughput and path loss of all the femto and macro users for all the supported bandwidths of an LTE-A system using different modulation schemes. A series of tests are carried out using the described simulation framework for a range of scenarios. The modulation scheme that yield highest throughput for a femtocell user is identified, and path loss is found to be independent from the modulation scheme but is dependent on the distance from its base station. In another series of experiments, the effects that walls inside buildings have on connectivity are examined and positioning of the femtocells is changed for each scenario inside buildings to analyse the performance. These results are used to find the optimised location of femtocells in different room layouts of the building. The simulation framework is further developed to be able to optimise the whole femtocell network by finding the optimised positioning of femtocells using the genetic optimisation algorithm. The end user can provide the inputs of the desired network topology to the simulation framework through a graphical user interface. The throughput and path loss of all the femto users are calculated before and after optimisation. The simulation results are generated in the form of tables before and after optimisation for comparison and analysis. The layouts depicting the indoor environment of the building before and after optimisation can be seen and analysed through the graphical user interface developed as a part of this simulation framework. Two case studies are defined and described to test the capacity and capability of the developed simulation framework and to show how the simulation framework can be used to identify the optimum positions of the femtocells under different configurations of room designs and number of users that represent contrasting loads on the network. Any desired network topology can be created and analysed on the basis of throughput and path loss by using this simulation framework to optimise the femtocell networks in an indoor environment of the building. The results of the experiments are compared against the claims in other published research