Research On Adaptive Transmission Technology In Intelligent Multimode Network Communication

When natural disasters and emergency emergencies occur,the demand for communications will increase dramatically,but due to geographical and electronic environments and other complex factors,human deployment cannot be achieved.The traditional emergency communication system adopts a fixed spectrum allocation method,and a large number of communication services will lead to a shortage of spectrum resources,and the communication is crowded or even paralyzed.At this time,the emergency communication device needs to have an understanding of its own electromagnetic surrounding environment and intelligently adjust the transmission parameters to achieve adaptive communication in order to reasonably solve the above problems.Under the cognitive radio architecture,the cognitive decision engine is a key part of the adaptive transmission system,and its performance determines the performance of the adaptive transmission system.In this paper,we design the cognitive decision engine and optimize the parameters such as power,BER,and modulation in adaptive transmission to realize adaptive transmission.The modulation types include:BPSK,QPSK,16QAM,and 64QAM.In order to send information accurately,a high-speed digital-to-analog conversion module and a host computer software capable of human-computer interaction are designed.The upper computer controls and displays the system,and communicates with the lower computer hardware platform through high-speed PCI-E to ensure real-time performance.The key technology research and implementation of adaptive transmission system based on cognitive decision engine of cognitive radio is mainly to make multi parameter optimization possible through multi-objective optimization theory.By combining chaos algorithm and standard particle swarm optimization algorithm,binary chaos particle swarm optimization algorithm is formed to realize the intelligent configuration of emission parameters,After simulation testing,based on the OFDM system,the cognitive decision engine based on the binary chaotic particle swarm optimization algorithm designed in this paper has better performance than other algorithms.Through the chip selection and the design of each unit,a high-speed digital-to-analog conversion module with a conversion speed of up to 2.5GSPS and an accuracy of up to 14 quantization digits is finally achieved.And in the communication between the host computer and the hardware platform for testing,the PCI-E speed is not less than 3GB/s,which can meet the real-time requirements of the system.Finally,the adaptive transmission system was tested,and the text,audio and multimedia services were tested separately.The maximum bit error rate of the system was less than1?10^-4,which fully verified the effectiveness of this design.