Quality-of-information Oriented Resource Allocation In Energy Harvesting Networks

The highly intelligent 5G mobile terminal is often powered by the battery.However,the restricted battery capacity is the fatal shackles to the ultimate traffic experience of users.Therefore,exploring new energy supply mode is important for future communication systems.Energy harvesting(EH)technology can harvest energy from ambient environment to provide a green and sustainable energy supply for mobile terminals.Therefore,EH networks will become a hot research issues and direction.Meanwhile,how to guarantee the quality of service(Qo S)for communication traffics has not been will solved.In the 5G era,since different types of traffics have different Qo S requirements,how to provide the heterogeneous Qo S provisioning in EH networks is very challenging.On the other hand,due to the highly-varying network states,statistical Qo S provisioning,in stead of deterministic Qo S guaranteed,has become a recognized feature in wireless networks.Resource allocation is an effective method to increase the utilization of resources.Resource allocation based on heterogeneous Qo S requirements and stochastic EH process can maximize resource utilization under statistical Qo S provisioning.This paper focus on the Qo S oriented resource allocation in energy harvesting sensor networks and machine-type communication network with EH.The paper is organized as follows.1.We study the resource allocation problem under Qo S provisioning(time-averaged queueing delay)for energy harvesting sensor networks.To capture the stochastic processes,we formulate a network utility optimization problem under the queue stability and energy causality constraint.We employ Lyapunov optimization to decompose the problem into three sub-problems.In particular,one of the sub-problem is a mixed integer problem.To facilitate the design of a tractable solution,we transform the sub-problem into a one-to-one matching problem and solved by Hungarian algorithm.Performance analysis shows that the proposed algorithm can achieve a close-to-optimal network utility while guaranteeing the queue stability.2.For machine-type communication(MTC),massive access congestions and the limited energy budget of MTC devices will lead to the decline of Qo S.To tackle these issues,a non-orthogonal multiple access(NOMA)-based MTC network with EH technique is proposed in this paper.Unfortunately,the cochannel interference caused by non-orthogonal of NOMA may negatively affect the achievable rate and further reduce the Qo S of users.Therefore,user scheduling in time domain is necessary to increase the Qo S satisfaction.By jointly consider the energy management and user scheduling,we formulate a stochastic optimization problem to maximize the long-term average sum rate under the constraint of Qo S requirements.For tractability,the stochastic problem is firstly transformed into two static subproblems.Then,using successive convex approximation method,we design an effective algorithm to solve subproblems.Simulation results demonstrate the proposed algorithm has a good performance in convergence and outperforms other schemes in terms of Qo S provisioning.