With the expansion of wireless mobile networks into both the daily lives of individuals as well as into the widely developing market of connected devices, communication is an increasingly attractive target for attackers. As the complexity of mobile cellular systems grows and the respective countermeasures are implemented to secure data transmissions, the attacks have become increasingly sophisticated on the one hand, but at the same time the system complexity can open up expanded opportunities for security and privacy breaches. After an in-depth summary of possible entry points to attacks to mobile networks, this paper first briefly reviews the basic principles of the physical layer implementation of 4G/5G systems, then gives an overview of possible attacks from a physical layer perspective. It also provides an overview of the software frameworks and hardware tool-software defined radios currently in use for experimenting with 4G/5G mobile networks, and it discusses their basic capabilities. In the final part, the paper summarizes the currently most promising families of techniques to detect illegitimate base stations—the machine-learning-based, localization-based, and behavior-based methods.

In modern communication systems advanced techniques such as digital predistortion (DPD) are required to satisfy stringent demands on transmitter linearity and efficiency. DPD, however, increases the hardware and computational complexity of transmitters. In this article we show that the computational complexity of DPD adaptation can be drastically reduced if a low number of samples is properly selected for DPD adaptation. For this purpose we propose methods of sample selection for DPD adaptation. Among the proposed methods, the highest computational complexity reduction is achieved by a method based on the histogram of signal magnitudes, optimised with respect to characteristics of the radio frequency power amplifier and of the transmitted signal. Simulations indicate that this proposed method can reduce the computational complexity of DPD adaptation by a factor of up to 400 while the linearisation performance of conventional methods is preserved. Besides simulations for three models of distinct power amplifiers, measurements on a real power amplifier further verify the linearisation capabilities of the proposed methods.

Interference between users in adjacent channels negatively affects throughput of mobile networks. In this paper we aim at cancellation of interference caused by a nonlinear power amplifier in a generalized orthogonal frequency division system. We propose an interference cancellation method to subtract these out-of-band emissions from the received signal. In contrast to state-of-the-art methods, our proposed method employs over-the-air estimation of power amplifier model parameters together with a particular frequency domain filtering method that allows to generate the required training data. The proposed interference cancellation method is also verified by an experiment on a software defined radio test bench.