Idiosyncratic Self-Organized Resources Allocation Algorithm Based On Fractional Frequency Reuse Scheme To Enhance Service Rate And Throughput In LTEA Hetnets

Abstract

This study addresses the issue of Radio Resource Management (RRM) in the Heterogeneous Network (HetNets) consisting of Macro Cells and Small Cells (Femto-Pico) for LTE-A. The main objective of deploying Femto-Pico cells, along with macro cells in HetNets, is to improve coverage, network capacity, and QoS for users who require connectivity, especially with their increasing numbers. However, at the same time, the traditional mechanism of allocating radio resources to users becomes disproportionate to familiar interference coordination techniques such as Fractional Frequency Reuse (FFR), given that planning methods of small cells are often random and the control center is not periodically aware of the locations of their deployment. In addition, user locations are also random at the centers and edges of the network's coverage areas. Therefore, suitable cells cannot be predicted for appropriate radio assignment. This makes interference mitigation and resource allocation management interrelated through design. The issue of radio resource management becomes more difficult with the increase of Co-Layer interference and Cross-Layer interference, especially with planning of ultra-dense small cells and with increase in the density of users. In this study, we reviewed the resource allocation strategies available in the literature for LTE-A HetNets. Next, we proposed a new Self-Organized Reuse Resources Allocation (SORRA) scheme based on the search for the best Idiosyncratic Cluster (IC) of cells surrounding each individual user to implement the appropriate allocation of available resources while simultaneously mitigating interference between cells in downlink. Thus, it improves both the service rate and network throughput. We compared the performance of the proposed SORRA with traditional schemes such as Strict and Soft FFR. the simulation results obtained using MATLAB.