The power amplifier (PA) is an indispensable component in wireless communication systems, while the nonlinearity induced by PA can lead to significant performance degradation. The conventional nonlinearity equalization (NLE) method can effectively mitigate the nonlinear effects and provide superior BER performance but requires intensive computational complexity. To this end, we propose a novel NLE method in the time domain, which can significantly reduce the computational complexity without sacrificing the BER performance. Specifically, we first propose a novel PA representation of the sum of products (SPs), which is a unified time-domain representation for several typical memory and memoryless PA models. On this basis, the SPs-iterative least square equalizer (SPs-ILSE) method is proposed to mitigate the impact of both the memory and memoryless PA’s nonlinear distortions at the receiver side. The computational complexity of complex multiplication (CCCM) in the proposed method isO(NlogN) for the memoryless PA models andO(KN2) for the memory PA models. Moreover, considering the commonly utilized PA models, we also derive the closed-form expression for the achievable SINR of the SPs-ILSE method in the ideal conditions. Numerical results show that (i) the closed-form SINR expression is valid for both the memory and memoryless scenarios (ii) the proposed method exhibits the superior bit error rate (BER) performance in comparison to several relevant nonlinear signal processing methods such as digital pre-distortion (DPD), and power amplifier nonlinearity cancellation (PANC) (iii) the proposed NLE method achieves the same BER performance as the previous NLE method, i.e., reconstruction of distorted signals (RODS), while the CCCM of the proposed method is much lower.

Aiming to improve the security in device authentication, many methods based on the physical layer signal are proposed. The essential characteristics of the physical layer signal captured during the wireless communications are called Radio Frequency Fingerprint (RFF). Constellation diagram is a form of two-dimensional signal representation besides the waveform, and different digital modulation types will generate different constellation patterns. Compared with the existing researches on the feature extraction or the circuit component impairments, we investigate the effect of different digital modulation types on RF fingerprints identification. Five bitsimilar USRP X310 and one calibrated USRP 2943R act, respectively, as the transmitting and receiving devices. In this experiment, we use ten digital modulation types with signal carrier to transmit the randomly generated bit sequences, and use the cable connection to reduce the impact of the channel. Then we observe the variation of recognition accuracy under different modulation types. Our experiment results show that except for the BPSK and OQPSK, the recognition accuracy of the rest modulation types is over 98% when SNR is more than 20dB.