Optimization-based resource allocation and transmission scheduling for wireless networks
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Future wireless communication networks are expected to be more energy-efficient and to provide higher throughput, in order to satisfy the demands for the increasing number of mobile users. Resource allocation and transmission scheduling play more and more important roles in improving the performance of wireless networks, in terms of energy saving, throughput, delay, etc. In this thesis, we consider three networks with different characteristics and objectives, i.e., wireless relay networks for distant transmissions, dense multi-user coexisting networks, and device-to-device (D2D) assisted mobile edge computing systems for compute-intensive mobile applications. We aim to investigate the key resource allocation and/or transmission scheduling issues in these networks. In particular, i) a transmit power allocation scheme with reduced overheads for amplify-and-forward relay networks is proposed to reduce energy consumption, based on the two-stage stochastic programming method, ii) an analysis framework for buffer-aided decode-and-forward relay networks under time-correlated fading channels is developed and an improved link scheduling/selection policy is presented, through the analyses to two quasi-birth-death Markov chains, iii) an interference-avoidance scheduling scheme for dense multi-user coexisting networks with heterogeneous priorities and demands is presented to increase the number of admitted users, on the basis of the column generation method, and iv) a joint optimization of admission control, link scheduling, and resource management for D2D-assisted mobile edge computing is carried out, according to the branch-and-price method. Simulations are performed to verify the effectiveness of the proposed schemes where the performance of networks is shown to be improved significantly.