Information Transmission And Detection Of Wireless Communication System Based On Ambient Backscatter

The ambient backscatter has become a promising approach for realizing the future large-scale deployment of the Internet of Things(Io T)network,which exploits the ambient radio frequency(RF)signal as carrier,thereby eliminating the overhead of configuring the RF chains and reducing the cost and power consumption of the backscatter systems.However,the ambient backscatter technology faces the challenges of low communication reliability,limited communication range and low data rate due to the strong interference of the unknown ambient RF signal.Responding to this,this paper conducts a comprehensive study from the perspectives of coding,antennas,modulation and reflecting elements,which provides effective solutions to the above challenges.Firstly,the detection scheme is studied by adopting Manchester coding at the tag.Specifically,exploiting the shift characteristic of Manchester codes,the semi-coherent and non-coherent detectors are designed,and the bit error rate(BER)of the two detectors assuming either complex Gaussian or unknown deterministic ambient signal are studied,thus revealing the impact of the distribution of symbols,sampling rate and signal-to-noise ratio(SNR)on the detection performance.The simulation results show that the proposed two detectors can achieve higher reliability with lower detection delay than the existing detection methods in scenarios with imperfect channel state information(CSI),and are universal to the distribution of symbols.Secondly,a signal detection mechanism based on multiple receiving antennas is explored,and corresponding detectors are designed under different CSI conditions.Specifically,assuming perfect CSI,the optimal detector is designed based on the principle of maximum a posteriori(MAP),and its BER expression in precise and asymptotic scenarios is derived.Assuming imperfect CSI,the maximum-eigenvalue detector is derived based on the general likelihood ratio test(GLRT)and its approximate BER expression are derived.To demonstrate the superiority of the proposed detectors,an energy detector is proposed as a benchmark for comparison.Furthermore,an efficient parameter estimation method is proposed to construct test statistics and decision thresholds.Theoretical and simulation results show that the optimal detector outperforms the maximum-eigenvalue detector,and can effectively cancel the interference,thus enlarging the communication range.Nextly,the detection methods assuming different ability of the reader are proposed with multiple frequency-shift keying(MFSK)modulation at the tags.First,a maximum likelihood(ML)detector is derived when reader is not capable of removing the direct interference.In addition,by exploiting the frequency shift feature of MFSK modulation,a simple energy detector is proposed when reader can remove the interference,and the symbol error rate(SER)and outage probability expressions are obtained.By analyzing the relevant analytical expressions,the optimal modulation,optimal bit signal-to-noise ratio(b-SNR),and optimal deployment of the tag is designed.The simulation results show that using MFSK modulation can effectively improve the data rate and detection performance.Finally,a passive beamforming and joint information transmission scheme based on discretephase intelligent reflecting surface(IRS)is explored.Specifically,to maximize the power of the received signal,a low-complexity IRS passive beamforming scheme is proposed.On the other hand,to jointly transmit IRS and transmitter information,a joint information transmission scheme is proposed for anti-aliasing,and an algorithm maximizing the minimum Euclidean distance(MED)of the constellation is designed.Simulation results show that the proposed joint information transmission scheme can effectively improve the data rate and achieve satisfactory detection performance with imperfect CSI.