Research On Resource Allocation And Performance Analysis In Energy Harvesting Aided Mobile Cellular Networks

With the explosive growth of the number of mobile devices and the continuous emergence of diversified application scenarios,5G/B5G(The Fifth Generation/Beyond Fifth Generation)wireless communication networks are facing the environmental pollution problem caused by excessive energy expenditure.Energy harvesting(EH)technology introduces the renewable energy into mobile cellular networks by harvesting energy from the surrounding environment to support equipment communication,which increases the energy source of the system.In addition,in order to satisfy the requirement of massive connections,large bandwidth and low delay,various technologies have emerged,such as device-to-device(D2D)communication,edge cache and edge computing.Combining EH technology with the mobile cellular network which integrating various communication technologies can support the needs of various services and reduce the conventional energy consumption.However,the energy provided by EH technology for equipment has strong randomness and instability,which makes the traditional resource allocation strategy based on deterministic model no longer applicable.It seriously restricts the wide application of this technology in future mobile communication networks.It seriously restricted the wide application of EH in future mobile communication networks.In view of the above analysis,under the EH aided mobile cellular networks,considering the limitation of equipment dynamic energy supply,the purpose of this dissertation is to make full use of the communication,cache and computing resources with D2D communication,edge cache and edge computing technology respectively.The resource allocation strategies are designed to satisfy different service requirements,and the key factors affecting the network performance gain are explored.The main work and innovations of this dissertation are summarized as follows:(1)A communication resource allocation scheme under dynamic energy supply is proposed to solve the resource imbalance problem caused by the available energy and complex interference in EH aided D2D cellular networks.Firstly,in order to improve the utilization of spectrum resources,the many-to-one and many-to-many spectrum reusing scenarios between EH-D2D users and cellular users are proposed and modeled respectively.Taking the constraint of EH,the influence of spectrum multiplexing,and the quality of service of users into account,a spectral efficiency maximization problem is formulated.Secondly,two different resource allocation algorithms based on matching game are designed for the two spectrum reusing scenarios,respectively.Each algorithm is divided into two steps.The first step is the many-to-one or many-to-many spectrum matching algorithm to obtain the stable spectrum allocation results of EHD2D users and cellular users.Based on the above matching results,the convex optimization tool is used to solve the optimal transmission power and transmission time of EH-D2D users.Finally,the simulation results validate the proposed algorithms significantly outperform the other spectrum allocation strategies.(2)A cache scheduling scheme under dynamic energy supply is proposed to solve the transmission outage caused by the mismatch between the user’s available energy and the requested service of the cache file in the EH-and cache-aided cellular network.Firstly,under the EH-and cacheaided D2D cellular network,jointly considering the location distribution of mobile users,the limitation of the harvested energy,and the randomness of the tasks cache and request model,the mathematical model is constructed by using stochastic geometry.The content delivery strategy is proposed and the interference of the network is analyzed.Secondly,according to the source of obtaining the required content,each user can communicate under three modes,i.e.,self-satisfied,D2D communication and cellular downlink communication.Further,the cache hit probability and successful offloading probability of each user in the three modes are derived respectively.Based on the analyzed results,two probabilistic caching strategies with different objectives are further designed.Finally,through the simulation results,the effect of different parameters on network performance are analyzed,and the superiority of the proposed caching strategies is verified.(3)A computing offload strategy under dynamic energy supply is proposed to solve the problem of queuing delay caused by limited energy and computing resources in EH-aided Non-orthogonal Multiple Access(NOMA)mobile edge computing(MEC)network.Firstly,the MEC network eploying EH and task storage unit is modeled.Considering the random harvested energy,the random arrival of tasks,limited computing power and NOMA offloading constraints,the local computing and offloading strategy is proposed,and the success computing probability of the task is analyzed and deduced.Further,the process of task random arrival,queuing,local computing and NOMA offloading of each user is depicted by a discrete-time queuing model under four-dimensional Markov chain.The steady-state equation of the model is solved,and the average response time and waiting time of task in the system are derived.Finally,the correctness of the model is verified by numerical simulation,and the influence of different parameters on the system performance is analyzed.