The Performance Optimization Of D2D And UAV-Assisted Emergency Communication Network

With the development of the Fifth Generation(5G)mobile communica-tion system,the new generation of mobile communication systems has made a number of breakthroughs and innovations in network architecture and com-munication technology.The scale of mobile communication networks has expanded rapidly with the emerging scenarios such as enhanced Mobile Broad-band(eMBB),Ultra Reliable Low Latency Communications(uRLLC),and massive Machine Type Communications(mMTC).At the same time,the de-mand for mobile communication traffic will also see an explosive growth with the emergence of more advanced technologies.This increases the the human society’s dependence on information networks in daily life,industrial produc-tion,economic development,and social management.Under this society,the emergency communication guarantee system is of great significance for main-taining social order and stability and ensuring the safety of people’s lives and property.While the emerging technologies has brought challenges to the emer-gency communication capabilities of mobile communication systems,they are also expected to enhance the situational awareness and rapid response deploy-ment capabilities of the next generation of emergency communication net-works.Therefore,it is very necessary to conduct research on the optimization of emergency communication networks based on emerging technologies.This thesis starts with the two emerging technologies of D2D communication and UAV communication,and conducts research on D2D communication and UAV communication-assisted emergency communication network optimization.The main contributions of this thesis are summarized as follows:1.A mobility-aware D2D emergency communication network is proposed,since the mobility of D2D users in the existing research work has not been widely used in the resource optimization of emergency communication networks.This thesis models the resource optimization of the emergency communication net-work as a joint optimization problem of D2D assignment,channel resource allocation,and power control to maximize the total transmission rate of the system.This thesis further proposes a joint optimization algorithm based on the maximum weight matching problem of the bipartite graph.Simulation results show that the proposed algorithm can effectively improve the system throughput.2.A method for the joint optimization of access and backhaul link in the multi-UAV-assisted emergency network is proposed,since the UAV’s backhaul link is often ignored in the existing research work.This thesis constructs an emergency communication model for multi-UAV base stations and relays,and models the joint optimization of access and backhaul links to maximize the system transmission rate.Three theorems are derived to prove the optimality of our proposed resource optimization strategy and UAV deployment strategy.The thesis further proposes an optimization algorithm for joint user association,UAV deployment and resource allocation.Finally,various simulations are performed to verify the effectiveness of the proposed algorithm.3.A multi-agent based reinforcement learning method is proposed for the joint optimization of D2D assignment,resource allocation,and power control.Existing research on resource optimization of emergency communication net-works assisted by combined D2D and UAVs faces a key problem that resource management strategies usually lead to heavy system signaling overhead.To alleviate this issue,the thesis first presents a system model of an emergency communication network combining D2D and UAVs,and models the optimiza-tion problem as a multi-agent-environment interaction problem.A long and short-term memory neural network based multi-agent actor-critic reinforce-ment learning method is further proposed,which learns an optimal strategy for each D2D pair to select resource blocks and transmission power and optimizes the bandwidth allocation and transmission power of cellular users at the UAV base station.Finally,simulated experiments are conducted which verify the effectiveness of the proposed algorithm.