Research On Cross-Layer Data Driven Vehicular Communication Beam Multicast Coverage Technology

With the advent of 5G era,modern automobile is no longer a pure means of transportation.At present,the automotive industry is undergoing key technology evolution and change.5G technology makes more and more cars can access to the Internet,and can achieve interconnection.In this context,it is particularly important to realize the rapid information interaction between vehicles.Millimeter-wave(mm Wave)bands are expected to be an important choice for future vehicular communication to support Gbps links for reliable data transfer in high-rate applications.The recent online learning technologies addressed the problem of fast beam tracking by exploiting user location information and mining received data in mm Wave vehicular systems to adapt to the vehicle’s environmental situation.However,the fairness and efficiency over mm Wave beams are difficult to maintain on the move,especially for high-density traffic,since the number of available beams is quite limited by hardware and cost for current antenna arrays.Fortunately,the social structure of preferences between the neighboring smart cars and their passengers can be leveraged to improve the beam coverage efficiency by performing the broadcast transmission via a single beam.In this paper,a two-layer online learning CSML algorithm based on vehicle location and social preference information is proposed to realize fast beam access of broadcast coverage in millimeterwave communication system.Based on the multi-armed bandit model,CSML embodies the selection of appropriate beams in the first layer and steers the broadcast angle along these beams in the second layer by aggregating the received data.Furthermore,CSML needs to adjust the timing of exploration and exploitation based on the social information,i.e.,the probability of vehicles meeting with each other that have the same preference.In this paper,the performance of the algorithm is evaluated and simulated by using real traffic patterns(such as road blocking rate,vehicle arrival rate,number of selected beams,etc.),and the results show that the CSML algorithm using location information and social preference information improves the efficiency of millimeterwave base station,improves the amount of data transferred between base station and vehicle,and optimizes the performance of millimeter wave communication system,and the algorithm is close to the optimal performance of the system.