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[Abstract]:With the development of communication technology in recent years, the requirements of wireless communication system for spectrum efficiency and communication efficiency are becoming higher and higher. On the basis of the original half-duplex communication mode, the transmission efficiency can be doubled theoretically in the same frequency full-duplex communication system. However, the strong self-interference signal from the local transmitter is the biggest obstacle to the full-duplex communication system. The research of self-interference suppression is one of the key points of the system. Therefore, this paper will focus on the design of algorithms and modules for self-interference suppression in analog and digital domains, and then verify the effectiveness of the system. The basis and system model of full duplex communication are studied and analyzed, and the simultaneous frequency full duplex communication system and its transceiver model are introduced. The OFDM signal model, the communication channel and the self-interference channel model are studied. In the background of the simultaneous co-frequency full-duplex communication system, the communication channel model is Rayleigh fading model, and the self-interference channel model is the Rice channel with higher K rice factor. In this paper, self-interference suppression in analog domain is studied. Using channel estimation to reconstruct analog self-interference to suppress simulated self-interference, IFFT module in OFDM system is used to reduce the complexity of reconstruction self-interference by using product instead of convolution in frequency domain. The experimental results show that the channel estimation performance of the LS algorithm is similar to that of the MMSE algorithm under the background of full duplex and high error-noise ratio. In the analog self-interference suppression module, the self-interference of 32dB can be suppressed. Thirdly, This paper analyzes the necessity of improving the dynamic range of A / D conversion under the background of low signal-to-noise ratio. In this paper, a large dynamic range A / D conversion algorithm based on analog to digital conversion quantization error signal compensation is proposed, and the validity of the algorithm is verified. Combined with the experimental background of full-duplex communication system, the effective dynamic range of ADDA converter used in the algorithm should be no less than 50dB and 75dB, and the simulation results show that the algorithm can improve 20dB on the basis of 8-bit AD. Dynamic range. Finally, The self-interference suppression in digital domain is studied. The original mode of operation is improved, and the self-interference channel does not change obviously with time. Channel estimation based on half-duplex training mode before full-duplex operation is used as the basis for reconstruction of digital self-interference signal and channel estimation is carried out by using low-complexity frequency-domain least square algorithm. Experimental results show that the proposed method can increase the self-interference suppression by 15dB compared with the channel estimation based on comb pilot. The self-interference suppression of the whole system is studied in combination with simulated self-interference suppression under different signal-to-noise ratios. The experimental results show that the digital self-interference suppression module can suppress the self-interference of 36dB and the whole system can suppress the 68dB self-interference. The demodulation error rate of the system is compared with that of the half-duplex system under the same index under different signal-to-noise ratio. The conclusion that self-interference can be effectively suppressed under the condition of not less than -55dB signal-to-noise ratio is verified. In summary, active self-interference suppression is studied under the background of simultaneous full-duplex OFDM communication system. In this paper, a large dynamic range A / D conversion algorithm in full duplex communication is proposed and its validity is verified. Finally, the effectiveness of self interference suppression is verified by using self interference suppression as an indicator, and the effectiveness of the communication system is verified by using the bit error rate (BER) as the index.
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