Research On Resource Allocation Of Ground-Ocean Cooperative Relay Communication System In URLLC Scenario

The demand for Ground-Ocean communication services is increasing rapidly due to the vigorous promotion of the national maritime strategy and the rapid development of integrated Air-Space-Ground-Ocean communication networks.In order to meet the diverse needs of users for data transmission,it is crucial to use resources such as spectrum and power rationally to improve the performance of wireless communication networks in Ground-Ocean scenarios.Coastal base stations are commonly used in Ground-Ocean communication systems,and relay cooperative technology is often employed to achieve long-distance communication between ground and ocean users.Meanwhile,lacking of a continuous energy supply,ocean relays need to reasonably allocate radio resource to reduce the energy consumption or effectively apply the Energy Harvesting(EH)technology.The Internet of Vehicle(IoV)is a crucial component of intelligent transport systems,and Vehicle-to-Vehicle(V2V)communication is a form of ultra-Reliable Low Latency Communication(uRLLC).Quick and reliable transmission of data,such as inter-vehicle distances and operating speeds,is necessary to prevent traffic accidents.Similarly,as a critical component of the energy internet,the smart grid must meet strict uRLLC requirements for business information like relay protection and safety automation to ensure the smooth operation of the grid and timely fault repairs.To meet the uRLLC requirements of both IoV and the smart grid,this thesis proposes a Ground-Ocean Cooperative Relay Communication(GOCRC)system and investigates the design of relay processing matrix as well as the allocation of resources such as power,subcarriers,and relays.The main works can be summarized as follows:(1)This thesis proposes a GOCRC system based on IoV,which consists of a vehicle subsystem and a marine relay subsystem.In the vehicle subsystem,neighboring V2V pairs communicate in a Device-to-Device(D2D)manner.Meanwhile,in the ocean relay subsystem,the relay is equipped with multiple antennas and uses Multiple Input Multiple Output(MIMO)technology and Decode-and-Forward(DF)mode to forward the received signals to the Ocean User(OU)after relay processing matrix.The Signal-to-Interference-plus-Noise Ratio(SINR)of the V2V receiver,relay,and OU must meet basic requirements,while considering the long-time average transmission delay of the V2V pair.To minimize the total transmission power of the relay,an optimization problem is established.The Lyapunov optimization method is then used to transform this problem into a Lyapunov drift plus penalty minimization problem within a single time slot.Further,the problem is decomposed into two subproblems:relay processing matrix design and V2V power allocation,which are solved using the continuous convex approximation and Lagrangian dual method.The proposed relay processing matrix design scheme and power allocation strategy are experimentally verified and compared.(2)This thesis proposes a GOCRC system based on smart grid,which includes a cellular subsystem and a marine relay subsystem.The cellular subsystem comprises a base station and multiple Power Service Terminals(PST)that use Orthogonal Frequency Division Multiplexing(OFDM)technology.The PSTs transmit power service information to the base station.Meanwhile,the marine relay subsystem comprises a Shore User(SU),a relay,and an OU with EH functionality that operates in Amplify-and-Forward(AF)mode.The SU multiplexes the subcarriers of the cellular subsystem and selects a relay to send signals to the OU.To maximize the long-term average Energy Efficiency(EE)of the cellular subsystem while satisfying the end-to-end transmission delay of the PST uplink and the SINR requirements of the base station receiver,relay,and OU,this thesis develops an optimization problem for the joint subcarrier,relay,and power allocation.Using the Lyapunov optimization method,the Mixed-Integer Nonlinear Programming(MINLP)problem is decomposed into subcarrier,relay allocation,and power allocation subproblems.The problem is then solved using the Coalition Formation Game(CFG)method and Particle Swarm Optimization(PSO)algorithm.Moreover,the thesis improves the CFG and PSO algorithms to converge to a better solution space.Simulation results show that the proposed resource strategy can significantly improve the overall performance of the system.