Research On Resource Optimization For Diversified Communication Service Demands Of Internet Of Vehicles

With the increasing number of vehicles year by year,urban traffic congestion has become more and more serious,and accidents have become more and more frequent,which cause many environmental and energy issues.To improve the efficiency and security of transportation,so as to alleviate the environmental and energy crisis,Internet of Vehicles(Io Vs)has emerged as the times require.To achieve effective and accurate vehicle-road information collaboration,reliable and secure Vehicle-to-Vehicle(V2V)and Vehicle-to-Infrastructure(V2I)communications are essential.However,existing Io Vs research lacks the considerations of the real-world channel model,network topology changes,and dynamic behaviors of vehicles.Thus,it is hard to meet the requirement of precise and efficient services of Io Vs.To comprehensively considers these factors,this thesis optimizes the spectral efficiency,energy efficiency,and covert rate under the premise of guaranteeing the preset reliability and covertness of the link,eventually achieves the diversity of communication services.The first three works of this thesis mainly propose robust power control schemes to maximize the sum rates and energy efficiency for all vehicle communication links under high-density V2V communication scenarios.The last work considers the backscatter communication-based V2I communication scenario,where covert communication is adopted to realize the secure transmission of vehicle-road information.The research details are as follows:(1)In light of the V2V channel uncertainty and the co-channel interferences of V2V links under high-density vehicular ad hoc network,a V2V channel model with Doppler frequency shift is adopted,and a robust optimization problem is modeled to maximize the sum rates of all uplinks under the constraint of predetermined outage probability.Since the problem is non-convex,the mean-variance method is used to transform the intractable probabilistic constraints with the random V2V channel gains into deterministic constraints,and Successive Convex Approximation(SCA)is further used to obtain a convex one.The dual decomposition is used to determine the optimal transmission power for each user.The numerical simulation results show the effectiveness and robustness of the proposed algorithm,which is especially true for dynamic Io Vs scenarios.(2)In light of the co-channel interference and the channel uncertainty when multiple Device-to-Device enabled V2V(D2D-V)links reuse the channel of one cellular user(CU),an optimization problem is proposed to maximize the sum rates of all D2D-V links under the quality of service(Qo S)constraint of CU.Due to the channel uncertainty,the deterministic Qo S constraint of CU is formulated as a probability constraint.Under the Bernstein approximation,this intractable probability constraint is reduced to two deterministic constraints with separable structures.Since the objective function with the logarithmic summation form is non-convex,a SCA is used to transform the non-convex problem into a convex one,dual decomposition is used to determine the optimal transmission powers of vehicles,and a distributed robust power control algorithm is used to achieve high-reliability and high-rate service requirements.Simulation results show that the proposed algorithm greatly improves the Qo S of vehicular communications.The effectiveness of the proposed scheme is further verified by comparison with existing solutions.(3)To achieve stable V2V communication performances and optimal network energy-spectral efficiency under the hybrid architecture of Io Vs,the vehicle clustering and robust power control scheme are combined to maximize the network spectral-energy efficiency.Considering that the interference-limited probability constraint at the cluster head is intractable and the unified utility function is non-convex,Bernstein approximation and SCA are used to transform the problem into an easy one.Through the dual decomposition,the near-optimal solutions related to the fixed price C and the optimal price C~*are determined,respectively.Numerical simulation shows that these algorithms greatly improve the Qo S of vehicular communications under the hybrid architecture.By comparison,the effectiveness of the joint clustering and robust power control scheme is further verified.(4)In light of the high energy consumption caused by the traditional large-scale deployment of roadside units and the information security risk caused by the openness of vehicle-road communication,the V2I communication integrating covert communication and backscatter communication is considered to realize the secure transmission of vehicle-road information.Under the encrypted information broadcasted by the base station,the roadside tag requires a relatively high rate to reflect its key information,and easily exposes the behavior of its reflection.The covertness of the reflected link is enhanced by utilizing random artificial noise generated by the assisted jammers.Moreover,to obtain the maximum transmission rate of the backscatter link securely and covertly,under both random channel fading and artificial noise conditions,the minimum detection error rate of the surveillance vehicle and the outage probability of the backscatter link are derived.According to the average detection error rate of the surveillance vehicle,the reflection coefficient of the tag is optimized to maximize the effective covert transmission rate of the key information under covert constraints.The numerical results indicate the optimized reflection coefficient can achieve an efficient secure transmission of vehicle-road information.