| The most precious resource in wireless communication is the bandwidth of wireless channel.In order to achieve higher transmission efficiency,data header compression is an important research field.By reducing the additional overhead of Internet transport protocol package,the channel resources needed to transmit in the same application are reduced,the channel utilization is improved,and the round-trip response time in application interaction is reduced.Nowadays,the emerging Internet of Things communication technology NB-IoT has the characteristics of low power consumption and small data,so there is a strong technical demand for header compression.The Robust Header Compression,which is used in the current version of NB-IoT protocol,is not the best way to compress headers in low-rate,high-latency and high-error-rate environments for NB-IoT applications.Aiming at the environment characteristics of NB-IoT system application,a header compression algorithm ROHC-M based on Markov prediction model is designed,which can further improve the header compression rate.The core idea is to establish a Markov prediction model by analyzing the state transition mode in the compression process,and introduce channel information to realize the prediction of decompression state transition,so as to improve the success rate of decompression.On the basis of the accumulated data,the long-term optimization of the prediction results is achieved,which further improves the success rate of decompression.Finally,the header compression rate is improved.The effectiveness of the algorithm is verified by simulation in this paper.The experimental results show that the algorithm achieves good compression results for data headers.Compared with ROHC header compression algorithm,the average length of compressed headers is reduced by 0.71 bytes,and the throughput is increased by 10%.The transmission of redundant bytes is reduced and the transmission efficiency is improved.The expected objects of this paper is achieved. |
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