Research And Implementation Of Channel Estimation For Narrowband IoT Systems Based On SDR Platform

The 40 years' achievements of mobile communications have profoundly changed people's lifestyles.Currently,mobile communications are still rapidly changing,and the development trend of mobile IOT is gradually increasing.The features of low-power and widely-covered make IOT with narrow band have a broad application in a wide range of traditional areas.Narrow Band Internet of Things(NB-IoT)international standards are available nowadays,which further promote the application of NB-IoT.The smart grid system,which is an important application scenario of NB-IoT,is a 230MHz-band narrowband communication system based on OAI Platform Software Defined Radio(SDR).The fading characteristics of the wireless channel have many effects on the transmission of the signal,channel estimation is a significant information processing module in the smart grid system,which can provide channel response information that participate in coherent demodulation of receiver,and improve system performance.Thus,the main content of this paper is the algorithm research of channel estimation in smart grid narrowband communication system and the realization based on SDR platform.This paper first introduces the smart grid narrowband communication system,the propagation characteristics of wireless channel and the classification of channel models,channel estimation techniques.Then,we focus on the pilot-based channel estimation techniques,introduce the criteria and classification of pilot patterns design,as well as the pilot pattern design of the system in this paper.The pilot-based channel estimation algorithms studied in this paper include Least-Square(LS)algorithm,Minimum Mean Square Error(MMSE)algorithm and the algorithm base on Discrete Fourier Transform(DFT),interpolation algorithm with constant interpolation,linear interpolation and Gaussian interpolation algorithm.In this paper,a channel estimation emulation link of narrowband system channel estimation is established based on matlab platform.The transmitted bit sequence is subjected to channel estimation through a series of processing and then compared with the output bit sequence to get the bit error rate,and then to judge the performance of the algorithm.The LS,MMSE,LS+DFT and MMSE+DFT algorithms are simulated in AWGN,EVA and EPA channels,which use linear interpolation algorithm.The simulation results show thatthe performance of MMSE algorithm is better than that of LS algorithm,and the performance of algorithm with DFT is better.In addition,the advantages of MMSE and DFT algorithm in the channel with multipath effect and Doppler shift is not obvious.Based on the analysis of the simulation results and the real-time requirement of the SDR platform system,we chose the LS algorithm and the linear interpolation algorithm with lower complexity when implementing channel estimation.The key content of this paper are the code implementation process and performance testing of downlink shared channel code,and the code implementation and performance analysis of the channel estimation.Through the fixed-point and right-shift operation to achieve the optimization of the time,the finally measured average time of channel estimation during a sub-frame is 0.4185 seconds,which is reduced by half than un-optimized.