User Scheduling with QoS Support in Mobile Self-Organizing Networks

• Main Authors: Huang, Yu-Han, 黃鈺涵
• Other Authors: Chao, Hsi-Lu
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/57717433089122687647

碩士 === 國立交通大學 === 網路工程研究所 === 102 === In recent years, because of the wireless communication product innovation, the number of handheld devices will continuously increase, so the future wireless systems will require more resources. In response to the trend of the future, we use Cognitive Radio Network and a cloud to allocate and manage huge data. We have designed cloud-based cognitive radio access network (C2-RAN) in TV white space in our works. To effectively use the resources, we proposed a resource management scheme for our C2-RAN. Our resource management scheme is separated to three parts, clustering and resource management in Cloud, power control and channel allocation in Cloud, and resource management and user scheduling in CR access points (CR APs). This paper focuses on the third part. Specifically, we define several service classes. To protect continuity of service for mobile users, we define three states for users and group the users with the same state. We propose a physical channel mapping method to change the service request into the number of required channels. After the first two-tiers channel allocation and power control mechanisms performed at the cloud, the designed scheduling algorithm further allocates resources (in terms of time slots) to CR users to maximize the sum of throughout utilities. To solve this problem, we proposed an optimal algorithm. However, because of the high time complexity of optimal algorithm, we proposed a heuristic scheduling algorithm for our system. Finally, the small-scale simulation results show the comparison in the performance between optimal algorithm and our proposed algorithm. In addition, the small-scale simulation results also show the impact of overall performance with changing the service guarantee degree and utilization degree. From the large-scale simulations, we can see the overall benefits of the users in our system.