Content And Spectrum Aware Resource Allocation In Wireless Broadband Mobile Networks

The exponentially growth of data traffic in wireless broadband mobile networks has brought a big challenge for an efficient use of the wireless spectrum. To deal with the challenge, in this dissertation, we study the call admission control and resource scheduling in wireless broadband mobile network from two aspects:context-aware resource allocation and spectrum-aware resource allocation.Time-frequency resource conversion (TFRC) based call admission control is studied firstly. We propose a new context-aware resource allocation strategy, TFRC. A double-threshold guard channel policy tailored for the new strategy has been proposed, and an analytical model has been established to evaluate its impact on the call-level performance of an LTE-type cellular network. By applying multiple-stair Markov model, we transfer the original problem which is a continuous and discrete mixed Markov process into a pure continuous Markov process, thus derive the steady-state probabilities and outage probabilities of three types of calls (e.g. new call, handoff call, recovering call). Simulation results verify the accuracy of the analysis, and show that the new strategy can help the network accommodate more users in a heavy traffic condition and the potential drawback of the new technique measured by the recovering call dropping probability can be well controlled.TFRC-based resource scheduling is investigated. With the previous work, we further study the resource scheduling problem applying TFRC in an LTE-type cellular network. The optimal offline resource allocation problems, aiming at maximizing the total reward of the system with consideration of each service’s scheduling time, required data amount, and the time varying channel capacity, under both general case and TFRC-applied case are formulated for the on-demand date service. In addition, to facilitate implementation, we also formulate the optimal online resource allocation problem, for which a heuristic algorithm with low-time complexity is designed. Simulation results show that the designed algorithm can effectively promote the total reward and reduce the incomplete ratio of delivered services, and also verify the effectiveness of TFRC strategy. Dynamic channel allocation-based call admission control in cognitive radio networks is studied. Different from directly applying channel reservation, which is commonly applied in cognitive radio network and relatively conservative, a slotted call admission control scheme integrated with dynamic channel allocation is proposed. An analytical framework using a four-dimensional discrete-time Markov chain is established to analyze the impact of the proposed scheme on the performance of SUs. Specifically, a middle variable-based approach is proposed to analyze the state transitions of the multidimensional Markov chain. Simulation results verify the accuracy of the analysis and show the effectiveness of the proposed scheme in reducing blocking and dropping probabilities, lowering packet queueing delay, and improving spectrum utilization efficiency.