Resource allocation framework for downlink subframe of mobile WiMAX

Abstract

Mobile WiMAX technology is anticipated to be one of the technologies that dominate to meet the requirements of modern wireless communication systems, it is mobile broadband wireless communication system based on OFDM technique and it uses multiple-access version OFDMA to deliver high-speed data. Multiple-access technique allows many users to request high data rates in finite resources of the downlink channel. Management of shared downlink resources strictly affect the performance of mobile WiMAX base station, due to downlink resource allocation is complex decision which require to quantify many aspects that influence the performance of network operator and users’ satisfaction. The main and common problem of the resource allocation management is the resource wastage, due to management flaw in resource allocation algorithm, which is responsible for maximizing the resources utilization. Resource wastage is directly translated to decline in the overall performance of Mobile WiMAX system, since it represents a bandwidth shortage which adversely affects all Mobile WiMAX system participants and vice versa. In this thesis a novel design of dynamic resource allocation algorithm for Mobile WiMAX base station is proposed. The proposed allocation algorithm is called Sequential Burst Allocation (SBA) algorithm. SBA algorithm focuses on minimizing the wasted resources to increase the utilization efficiency of the downlink channel resources. SBA algorithm takes advantages of the physical layer specification to satisfy mobile users’ requirements, and utilizes downlink channel structure to reduce the redundant information in the downlink overhead and to manipulate resource allocation in innovative method. SBA design preserves users’ priorities and minimizes power consumption at mobile stations. The performance evaluations, comparisons and analysis showed that SBA is a low complexity algorithm that overcomes the restriction and difficulties of allocating users’ resources and achieves significantly minimization in resource wastage, which increases data transfer rate in the downlink direction to contribute in supporting the presented quality of service. Results showed that SBA algorithm achieves 97.54% utilization efficiency of the downlink channel and stable performance under various operating parameters, which lead to increase number of users per base station and enhance system capacity. A new method of overall performance assessment and comparison for resource allocation algorithms is proposed. It showed that SBA algorithm achieves the highest percentage (90.13%) of overall performance.