Multi-User Scheduling In Integrated Heterogeneous Networks

Wireless resources have become highly valued and scarce in order to response to the tremendous growth of demands for high capacity and multi-tasking services. Integrated heterogeneous networks have been widely accepted promising techniques to satisfy the unrelenting demands. There thus comes the multi-user scheduling problem of how to allocate and schedule limited wireless resources properly and efficiently to realize interfer-ence suppression and mitigation, increase overall throughput-utility, and provide cost-effective Quality of Ser-vice (QoS) guarantee. With this motivation, this dissertation carries out researches on delay-aware multi-user scheduling in integrated heterogeneous networks, including multi-user scheduling for multi-antenna broad-cast systems, delay-aware access control and scheduling in device-to-device (D2D) underlay commnunication systems, and global optimal rate control and scheduling for spectrm-sharing multi-hop wireless networks.Specific research results and contributions are as follows.1. A general model of delay-aware multi-user scheduling is elaborated, including the system model, the source model, the queueing dynamics and the delay-QoS requirements. The associated stochastic optimiza-tion problem is formally formulated as a long-time averaged system throughput-utility maximization with long-time averaged delay constraints. Two approaches, i.e., the large deviation approach and the Lyapunov optimization approache, are the presented to solve such stochastic optimization problem, which have their relative pros and cons in terms of performance, complexity and implementation issues. For each of the ap-proaches, the problem setup, the general solution and the design methodology are discussed.2. A low complexity user scheduling is presented for multi-antenna broadcast systems with a large number of users with diverse delay-QoS assurances. By adopting effective capacity and effective bandwidth from the large deviation theory to illustrate the behaviours of different traffic characteristics such as different source statistics and queue dynamics, the delay-bound violation probability constraints can be converted into equiva-lent minimum data rate constraints. To further reduce the computational complexity, genetic algorithm (GA) is used to perform scheduling, instead of a brute-force exhaustive search (ES) over all possible user subsets. By comparing the complexity of GA and ES, it is shown that GA is a rapid, although suboptimal, option of performing user scheduling optimization. Simulation results show that the proposed algorithm can not only achieve the weighted sum rate maximization (WSRMax), but also keep the delay-bound violation probability of each user below a given threshold.3. Delay-aware access control and scheduling in D2D underlay communication systems is studied. With the consideration of random bursty arrivals and delay-sensitive information flows, cross-layer optimization seeks to develop algorithms that:(ⅰ) provide efficient throughput-utility, (ⅱ) are robust to general time-vary ing conditions, and (ⅲ) guarantee bounded worst-case delay. In order to further exploiting the multi-user diversity, dynamical network admission is introduced, e.g., each source node can dynamically admit the cellular network or the D2D network at each slot. To deal with the delay constraints, both the large deviation approach and the Lyapunov optimization approach are presented. It is shown that, via either the large deviation approach or the Lyapunov optimization approach, the original optimization can be converted to WSRMax with minimum data rate constraint for each S-D pair. The simulation results also imply that the large deviation approach performs better in light traffic loading regimes with large delay bound requirements, while the Lyapunov drift approach may not have good delay performance in moderate and light traffic loading regimes but can keep the system stability when data arrival rate grows large.4. Global optimization for rate control and scheduling is proposed to maximize the network-wide utility in spectrum-sharing multi-hop multi-flow wireless networks. In particular, this multi-user scheduling problem is addressed in the gradient-scheduling framework. Given routes, the scheduling problem can be reduced into a time-varying WSRMax. A global optimal rate control and scheduling algorithm, referred to as G-RCS, is developed that bypasses the non-convexity issue and converts the problem into a monotonic optimization problem by exploiting the hidden monotonicity of the problem. Simulation results shows that the proposed G-RCS algorithm is guaranteed to converge to an (η, ∈)-optimal solution in a finite number of iterations. To further reduce the complexity, an accelerated algorithm, referred to as A-G-RCS, is proposed based on the inherent symmetry of the optimal solution. Numerical results validate that the proposed algorithms can achieve the global sum flow rate maximization for the multi-hop multi-flow wireless networks, which serves as a performance benchmark for existing heuristic algorithms.