Scheduling and resource optimization in next generation heterogeneous wireless networks

Next generation wireless networks have many promising features, such as high data rates, hybrid voice and data services, integration of different wireless access technologies, and intelligent networks with self-maintenance. With these features, several scheduling and resource optimization issues arise. In this dissertation, I aim to address these issues by first formulating the problems and then proposing solutions accordingly. These challenging research problems include the resource allocation problem for the Worldwide Microwave Interoperability for Mobile Access (WiMAX) networks, the minimum-cost data delivery problem in heterogeneous wireless networks, the self-maintenance scheduling problem for next generation wireless networks, and the scheduling problem for multi-hop cellular relay networks. In the WiMAX scheduling, I propose a two-phase Fair and Efficient Queueing (FEQ) scheduling algorithm, which effectively combines Weighted Round Robin (WRR) and Earliest Deadline First (EDF) algorithms. I also build an elegant queueing model to derive in theory the performance metrics. In minimum-cost data delivery, I first prove the cost minimization problem to be NP-hard, and then present an efficient minimum-cost data delivery algorithm based on linear programming, with various constraints and scenarios taken into consideration. In self-maintenance scheduling, I consider resource maintenance and resource conflicting constraints and propose a linear programming model and two heuristic algorithms to schedule the maintenance requests, aiming at minimizing the total maintenance time. In scheduling for multi-hop cellular relay networks, I develop a scheduling algorithm based on linear programming to maximize system throughput while maintaining system fairness. This scheduling algorithm takes into account the dynamic queue change in the relay stations, the frame boundary of the cellular networks, and fairness among different concurrent transmission scenarios. Extensive simulations have been conducted to verify the effectiveness of the scheduling algorithms proposed above. In summary, we have proposed several scheduling algorithms to address various scheduling and optimization issues for next generation heterogeneous wireless networks, and we anticipate that the proposed scheduling algorithms will become necessary components of next generation heterogeneous wireless networks.