Research on Channel Characteristics Under Smart Classroom Based on Ray Tracing and Neural Network
Smart classrooms play an important role in modern teaching practice.In this scenario,the reliability of wireless communication links is the key to ensuring the quality of teaching.In the smart classroom environment,wireless signal needs seamless coverage,desks and chairs can be placed flexibly,and a large numbers of people might exits.It is very important to establish a channel model that can accurately describe these characteristics.Thus,this paper combines ray tracing channel data and multi-layer neural network to construct a channel model in a smart classroom en-vironment that supports multiple inputs and binary outputs.The results show that the proposed model achieves higher accuracy than conventional models.The proposed model can provide basic references for the design of wireless communication systems in the smart classroom environment.
smart classroomray tracingneural networkchannel model
NETL
NSTL
万方数据
