Stochastic Geometry Based Analysis And Optimization Of Air-Ground Ad Hoc Networks

The last decade has witnessed a tremendous increase in the number of mobile devices and also a sharp rise in the demand for mobile data communication.Facing such massive consumer demand for mobile data communications,especially that from the skyrocketing number of mobile user devices,we have,however,only rather limited wireless band resources.Obviously,relying solely on the traditional cellular networking cannot meet the great demand.As a new architecture for broadband wireless access systems,air-ground ad hoc network holds its great promise to significantly enhance network performance,as well as improve quality of service(Qo S)and network resilience.It is believed that air-ground ad hoc network has broad prospects for technological development and application.In light of the great advantage of air-ground ad hoc network,how to effectively explore and evaluate the network performance is quite an important work.However,it is extremely complex to evaluate performance of the advanced network architecture through traditional system-level simulation due to its specific characteristics such as heterogeneity,self-organization,and time-variability.Recently,stochastic geometry has been widely used in analyzing and modeling of wireless network because of its natural advantage in characterizing network randomness and sometimes may lead to closed-form expression.Therefore,in this thesis,we mainly focus on exploring network performance of UAV communication and D2 D communication,which are very important parts of air-ground ad hoc networks.By utilizing the tools of stochastic geometry,we aim to model and analyze the key performance metrics brought by utilizing D2 D communication or by deploying multiple UAVs under different network scenarios.It is expected that this thesis could provide theoretical basis and technical support for future mobile network design and deployment.The main contributions of this thesis are summarized as follows.1.Based on the tool of stochastic geometry,we present in this chapter a framework for analyzing and optimizing the network performance in a D2 D overlaying multichannel downlink cellular network.We consider a flexible new scheme for mobile UEs which located far from BSs to connect to a nearby BS via another intermediate UE in a two-hop manner to offloading data traffic from the base station while improving network performance.We first highlight a D2D-communication based technique for load balancing that is able to efficiently offload traffic among multi-tier cells according to their real-time traffic distributions.In addition,we present numerical results to show the great promise of applying the proposed algorithm to improve quality of experience.By utilizing the tool of stochastic geometry,we give closed-form expression for network performance in terms of coverage probability and ergodic rate.Our results indicate that the developed framework is very helpful for network designers to efficiently determine the optimal network parameters at which the optimum system performance can be achieved.Furthermore,as corroborated by extensive numerical results,enabling the D2 D link based two-hop connection can significantly improve the network coverage performance,especially for the low SIR regime.2.We explore the performance gains brought by utilizing two cooperative UAVs for downlink transmission over a large number of emergency response rescue vehicles on the ground in post-disaster areas.Toward this end,we introduce the concept of average channel access delay for a generic vehicle to establish a full transmission to an UAV in real world scenarios.Based on the proposed concept,we present a stochastic geometry based mathematical framework to analyze the coverage probability and average achievable rate for a multi-UAV assisted downlink overlaying network,where vehicles connect to the Internet via satellites in a two-hop manner.According to the derived closed-form solutions for the network performance metrics,we give extensive numerical results to illustrate the network performance gains brought by UAVs.Moreover,our results reveal that the network performances are strongly affected by many aspects,such as the UAVs' altitudes,flying speed,transmit powers,ground user density and so forth.Additionally,we also present optimal settings for network designers to efficiently determine the optimal network parameters so as to achieve the optimum network performances in post-disaster areas.3.Upon the above mentioned work,we develop an effective analytical approach to characterize the properties of UAV-enabled edge computing platform in narrow band Internet of Things(NB-Io T)system over a large number of Io T devices by introducing average channel access delay.Then,we present a stochastic geometry based mathematical framework to analyze the coverage probability and average achievable rate for a multi-UAV assisted underlaid downlink network,where random channel allocation scheme and the mobility of UAV are considered.Extensive numerical results are provided to validate the effectiveness of developed framework.Besides,we give their optimal settings to maximize the coverage probability and the average achievable rate.Additionally,we present system-level simulations on network scenarios with multiple moving UAVs and that with two hovering flight UAVs.Our results indicate that it is inappropriate to improve the network performance by only increasing the number of UAVs.