Research On Resource Allocation Algorithm In Multi-user Data And Energy Integrated Network

In order to address the energy shortage of communication devices in the 5G and IoT era,engineers are seeking renewable energy from the ambient environment for charging miniature devices in networks.Therefore,energy harvesting is becoming more and more widely used in communication networks.Due to the instability of energy in the environment,more stable radio frequency(RF)signals are now used for energy transmission.In the communication network,many resources are limited,in order to improve the performance of the network system and reduce the waste of resources,the resource allocation and optimization among multiple users in the network is very important.In this background,the resourse allocation algorithm in multi-users data and energy integrated network is studied in this thesis.The content including:Firstly,a full duplex data and energy integrated network is described in this thesis.In order to maximize the total uplink throughput of all user equipment,we propose a joint optimization algorithm of user scheduling strategy and time allocation to ensure users' upload needs.In this system,the user scheduling strategy is established as a classic matching problem and is solved by the Hungarian algorithm.Then,based on the results of the user scheduling strategy,we propose an optimization algorithm and a suboptimization algorithm with lower complexity for time allocation.Finally,the optimal resource allocation strategy is obtained by iteration.Besides,a multicast cooperative network system for densely populated scene is described in this thesis,which uses time division multiple access(TDMA)to avoid conflict.In our system,the property of successful content transmission depends on the physical wireless transmission environment and the social relationship between the users.In a single transmission frame,we model the content distribution process as a discrete pure Markoff chain,and then derive the closed expression of the state-remain and the state transition property.We reduce the time delay of content distribution by reducing the state transition probability and maximizing the state transition step in each frame.And we get the optimal time allocation strategy with fairness by Lagrange multiplier method.Finally,based on the model of the delay sensitive social network model mentioned earlier,this thesis adds the function of user energy collection into the old model and takes into account the variable power of users during transmission,making the system more close to the real situation.On the basis of this model,the content distribution process is also established as a discrete pure Markoff chain.Considering the limitation of energy,we maximize the state transfer efficiency of Markoff chain by optimizing the power allocation and time allocation of mobile users,which has achieved energy saving and ensured the probability of successful transmission between users.Finally,we have simulated the performance of the algorithm and the results of the algorithm can be improved.