Resource Allocation Algorithms for LTE over Wi-Fi Spectrum

Abstract

As 4G services became more widely available, the number of 4G users has increased greatly, and the services began to suffer from the huge loads for base stations. Fortunately, 3GPP proposed Carrier Aggregation (CA), a method to aggregate component carriers (CCs) and increase the bandwidth to 100 MHz. In order to avoid low efficiency for a cell edge user, we position Wi-Fi stations around the cell edges and utilize the 5 GHz unlicensed band along with CA to achieve a high transmission rate. However, the method for allocating these resources to user equipment (UE) became a significant issue. Given the facts above, the goal of this thesis is to provide a solution for network performance optimization. To achieve this, we design a smart resource allocation scheme with the help of optimization schemes, such as Genetic Algorithm (GA), under different frequency bands (intra-or inter-band CA) and in the Orthogonal Frequency Division Multiple Access (OFDMA) system for the downlink (DL) of Long-Term Evolution-Advanced (LTE-A). In these two algorithms, the simulation is conducted every transmission time interval (TTI) and lasts for 100 TTIs. Improved GA can enhance convergence by 20% over GA, the Improved GA base.