QoS-driven adaptive resource allocation for mobile wireless communications and networks

• Main Author: Tang, Jia
• Other Authors: Zhang, Xi
• Format: Others
• Language: en_US
• Published: 2010
• Subjects: quality-of-service; resource allocation; wireless communications
• Online Access: http://hdl.handle.net/1969.1/ETD-TAMU-1050; http://hdl.handle.net/1969.1/ETD-TAMU-1050

Quality-of-service (QoS) guarantees will play a critically important role in future mobile wireless networks. In this dissertation, we study a set of QoS-driven resource allocation problems for mobile wireless communications and networks. In the first part of this dissertation, we investigate resource allocation schemes for statistical QoS provisioning. The schemes aim at maximizing the system/network throughput subject to a given queuing delay constraint. To achieve this goal, we integrate the information theory with the concept of effective capacity and develop a unified framework for resource allocation. Applying the above framework, we con-sider a number of system infrastructures, including single channel, parallel channel, cellular, and cooperative relay systems and networks, respectively. In addition, we also investigate the impact of imperfect channel-state information (CSI) on QoS pro-visioning. The resource allocation problems can be solved e±ciently by the convex optimization approach, where closed-form allocation policies are obtained for different application scenarios. Our analyses reveal an important fact that there exists a fundamental tradeoff between throughput and QoS provisioning. In particular, when the delay constraint becomes loose, the optimal resource allocation policy converges to the water-filling scheme, where ergodic capacity can be achieved. On the other hand, when the QoS constraint gets stringent, the optimal policy converges to the channel inversion scheme under which the system operates at a constant rate and the zero-outage capacity can be achieved. In the second part of this dissertation, we study adaptive antenna selection for multiple-input-multiple-output (MIMO) communication systems. System resources such as subcarriers, antennas and power are allocated dynamically to minimize the symbol-error rate (SER), which is the key QoS metric at the physical layer. We propose a selection diversity scheme for MIMO multicarrier direct-sequence code- division-multiple-access (MC DS-CDMA) systems and analyze the error performance of the system when considering CSI feedback delay and feedback errors. Moreover, we propose a joint antenna selection and power allocation scheme for space-time block code (STBC) systems. The error performance is derived when taking the CSI feedback delay into account. Our numerical results show that when feedback delay comes into play, a tradeoff between performance and robustness can be achieved by dynamically allocating power across transmit antennas.