Research On Dynamic Resource Allocation Technology In Cooperative Wireless Network

With the exponential growth demand for wireless services,the shortage of wireless spectrum resources and wireless equipment energy have become more and more prominent.In order to solve these problems,the academic community has proposed the cooperative wireless network,which is used to efficiently allocate precious spectrum and energy resources.Cognitive radio is a spectrum cooperation strategy,which dynamically coordinates spectrum sharing.In cognitive radio network(CRN),primary users(PUs)allow secondary users(SUs)to access idle spectrum,which achieves efficient reuse and dynamic allocation of spectrum resources.Through cooperative relay and wireless energy transmission technology,energy cooperation realizes the adaptive transmission and redistribution of energy between the source nodes and the relay nodes,which significantly reduces the energy consumption of wireless transmission.However,the current researches on resource allocation in cooperative wireless networks are still in the preliminary stage,and the research model and allocation mechanism are relatively simple.Aiming at the spectrum sharing,multi-relay selection and power allocation in cooperative wireless communication systems,this thesis mainly investigates corresponding innovative solutions and mechanisms detailed theoretical analysis and performance simulations.The main contributions and innovations of this thesis are as follows:(1)We propose a novel dynamic channel assembling(DCh A)strategy by employing priority queues based on a fine-grained flow classification.First,three categories of SU flows are considered,so-called the real-time SU flows,the elastic large SU flows,and the elastic small SU flows.And various SUs flows are buffered in queues with different priorities.Second,the central base station allocates spectrum resources to the classified SU flows through performing the channel access algorithm.Unlike previous algorithms that only focused on the completion speed of real-time SU flows,our main idea is that the real-time SU flows with higher priority are only supposed to access as few channels as possible,so long as their minimum requirements are fulfilled.Subsequently,the continuous time Markov chain is utilized to model the proposed strategy and conduct theoretical analyses.Finally,with the detailed theoretical analyses and extensive simulations,the proposed DCh A strategy is demonstrated to be able to fulfill the deadline of SU flows,while significantly reducing the blocking probability as well as the completion time of the elastic SU flows.(2)We propose a novel dynamic flow-adaptive spectrum leasing with channel aggregation.First,we design an adaptive leasing algorithm,which adaptively adjusts the portion of leased channels based on the number of ongoing and buffered flows.Second,in the leased spectrum band,the SU flows with access priority employ dynamic spectrum access of channel aggregation.We employ both priority access and opportunistic access in the leased spectrum band and the unleased spectrum band,in order to provide more flexible channel allocation when the demand of flow surges.Subsequently,the corresponding continuous-time Markov mathematical model was established to analyze the effective state of the system and the transition probability between states.Finally,numerical results demonstrate the strategy improves the spectrum utilization and network capacity,while significantly reducing the forced termination probability and blocking probability of SU flows.(3)We propose a relay selection and power allocation algorithm based on energy-harvesting and buffer-aided in a two-way multi-relay cooperative communication network,and the algorithm realizes the solution of two cases of no-delay limited transmission and delay limited transmission.First,by jointing the time switching and energy splitting for RF energy harvesting,we introduce a three time-subslot transmission model to balance the energy storage and the energy consumption for communication.Second,we formulate an optimization problem for throughput maximization of relay network.We purposely convert the non-convex optimization problem into a convex one by carefully decoupling and relaxing.Subsequently,we theoretically derive the maximum throughput and apply an iterative algorithm to achieve the suboptimal solution based on relay selection and power allocation.Finally,extensive simulations have been conducted to demonstrate that the strategy improves the sum-throughput under transmission energy and delay constraints.