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In this paper, we present a new LoRa transceiver scheme to ensure discrete communications secure from potential eavesdroppers by leveraging a simple and elegant spread spectrum philosophy. The scheme modifies both preamble and payload waveforms by adapting a current state-of-the-art LoRa synchronization front-end. This scheme can also be seen as a self-jamming approach. Furthermore, we introduce a new payload demodulation method that avoids the adverse effects of the traditional cross-correlation solution that would otherwise be used. Our simulation results show that the self-jamming scheme exhibits very good symbol error rate (SER) performance with a loss of just 0.5 dB for a frequency spread factor of up to 10.

In the context of cognitive radio, smart cities and Internet-of-Things, the need for advanced radio spectrum monitoring becomes crucial. However, surveillance of a wide frequency band without using extremely expensive high sampling rate devices is a challenging task. The recent development of compressed sampling approaches offers a promising solution to these problems. In this context, the Modulated Wideband Converter (MWC), a blind sub-Nyquist sampling system, is probably the most realistic approach and was successfully validated in real-world conditions. The MWC can be realized with existing analog components, and there exist calibration methods that are able to integrate the imperfections of the mixers, filters and ADCs, hence allowing its use in the real world. The MWC underlying model is based on signal processing concepts such as filtering, modulation, Fourier series decomposition, oversampling and undersampling, spectrum aliasing, and so on, as well as in-flow data processing. In this paper, we develop an MWC model that is entirely based on linear algebra, matrix theory and block processing. We show that this approach has many interests: straightforward translation of mathematical equations into simple and efficient software programming, suppression of some constraints of the initial model, and providing a basis for the development of an extremely fast system calibration method. With a typical MWC acquisition device, we obtained a speed-up of the calibration computation time by a factor greater than 20 compared with a previous implementation., Competing Interests: The authors declare no conflicts of interest.

This paper considers hiding messages in overt transmissions with a full-duplex receiver, which emits artificial noise to secure its transmission connection while a transmitter opportunistically sends a covert message to a covert user. The warden's uncertainties in decoding the overt message and artificial-noise-received power are exploited to hide messages. Then, the covert throughput accompanied with the warden's average detection error probability are determined. The results show that increasing the transmit power of artificial noise or improving secure connection at the overt user will improve the covert performance. The results also show that the covert performance is improved when the self-interference cancellation is improved at the full-duplex receiver or when the warden is located close to the full-duplex receiver, indicating the positive impact of the overt performance on the covert performance.

This paper studies the secrecy coding analysis achieved by the self-jamming technique in the presence of an eavesdropper by considering a short-packet Full-Duplex (FD) transmission developed based on iterative blind or semi-blind channel estimation and advanced decoding algorithms. Indeed, the legitimate receiver and eavesdropper can simultaneously receive the intended signal from the transmitter and broadcast a self-jamming or jamming signal to the others. Unlike other conventional techniques without feedback, the blind or semi-blind algorithm applied at the legitimate receiver can simultaneously estimate, firstly, the Self-Interference (SI) channel to cancel the SI component and, secondly, estimate the propagation channel, then decode the intended messages by using 5G Quasi-Cyclic Low-Density Parity Check (QC-LDPC) codes. Taking into account the passive eavesdropper case, the blind channel estimation with a feedback scheme is applied, where the temporary estimation of the intended channel and the decoded message are fed back to improve both the channel estimation and the decoding processes. Only the blind algorithm needs to be implemented in the case of a passive eavesdropper because it achieves sufficient performances and does not require adding pilot symbols as the semi-blind algorithm. In the case of an active eavesdropper, based on its robustness in the low region of the Signal-to-Noise Ratio (SNR), the semi-blind algorithm is considered by trading four pilot symbols and only requiring the feedback for channel estimation processes in order to overcome the increase in noise in the legitimate receiver. The results show that the blind or semi-blind algorithms outperform the conventional algorithm in terms of Mean Square Error (MSE), Bit Error Rate (BER) and security gap (Sg). In addition, it has been shown that the blind or semi-blind algorithms are less sensitive to high SI and self-jamming interference power levels imposed by secured FD transmission than the conventional algorithms without feedback.

The paper proposes a joint semi-blind algorithm for simultaneously cancelling the self-interference component and estimating the propagation channel in 5G Quasi-Cyclic Low-Density Parity-Check (QC-LDPC)-encoded short-packet Full-Duplex (FD) transmissions. To avoid the effect of channel estimation processes when using short-packet transmissions, this semi-blind algorithm was developed by taking into account only a small number (four at least) pilot symbols, which was integrated with the intended information sequence and used for the feedback loop of the estimation of the channels. The results showed that this semi-blind algorithm not only achieved nearly optimal performance, but also significantly reduced the processing time and computational complexity. This semi-blind algorithm can also improve the performances of the Mean-Squared Error (MSE) and Bit Error Rate (BER). The results of this study highlight the potential efficiency of this joint semi-blind iterative algorithm for 5G and Beyond and/or practical IoT transmission scenarios.