Research On Handover Algorithm Of Dense Vehicular Network Based On Multi-Attribute Fuzzy Logic

The Internet of Vehicles combines people,vehicles,roads,and Internet into an intelligent transportation system,enabling vehicles to realize complex environmental perception,data exchange,and intelligent decision-making and other tasks,thereby improving traffic efficiency and reducing accidents.In recent years,In the Internet of Vehicles,when the vehicle is moving very fast,the traditional network cannot meet the data transmission needs of the vehicle terminal.Therefore,the dense deployment of the network plays a key role in increas ing the system capacity.However,in this scenario of high mobility and network densification,vehicles inevitably produce more frequent network handover,which makes handover management problems become more complicated and challenging.Network handover is a key technology for vehicles to obtain continuous communication.Only when network handover is effective and accurate can communication interruption be reduced and can the safety of driving be improved.Based on the characteristics and handover requirements of dense vehicular network scenarios,dense vehicular network system is established and reasonable performance indicators are defined.In addition,the performance of traditional handover decision algorithms is analyzed through corresponding simulatio ns,including distance-based,RSS-based,SAW-based and A3 event-based handover algorithm.Experiments have proved that handover algorithms based on a single attribute or a fixed threshold are likely to deteriorate the handover performance,and the handover parameters suitable for low-speed scenarios may not be suitable for high-speed scenarios,so it is difficult to meet the needs of vehicular network applications.Aiming at the problems of low effectiveness and low accuracy caused by the traditional handover algorithm without fully considering the characteristics of dense vehicular network,a handover optimization algorithm based on multi-attribute fuzzy logic is proposed.The algorithm fully considers the network and terminal attribute information as well as takes into account the ambiguity of attributes,applying fuzzy logic theory,so that the handover threshold of the output can be adaptively changed according to the fusion of the input attribute.The handover threshold can be used for subsequent handover decisions.The simulation results show that the average number of handover attempts of the improved algorithm is significantly reduced.In the case of high network density and high speed,the handover failure rate is about3% lower than that of the SAW-based handover algorithm,while the ping-pong handover rate remains at 1% under different conditions,which improves the overall performance of the handover.Aiming at the problem that fuzzy logic algorithms need to rely on expert experience and knowledge to obtain better results and need to adjusted manually in time once the environment changes,neural network technology is applied and a handover algorithm based on a multi-attribute fuzzy neural network is proposed.The algorithm tracks the available historical handover data in the area so that system parameters can be automatically adjusted according to changes in the environment,thereby reducing manual intervention and improving the robustness of the algorithm.The simulation results show that compared with the basic fuzzy logic handover algorithm,the average number of handover attempts of the improved algorithm is further reduced,the handover failure rate is reduced by about 2%,and the ping-pong handover rate is almost close to zero.Therefore,the pro posed algorithm has obvious advantages and can better meet the handover requirements of dense vehicular network scenarios.