This letter presents a new method of digital adaptive pre-distortion for linearization of power amplifiers (PA). The method is derived from a post-distortion approach which identifies the PA inverse function. This approach leads to the minimization of a quadratic function of the polynomial coefficients in the case of a polynomial predistorter form and a least square criterion. We have compared our solution to a method previously proposed by Ghaderi (1996) that was also based on the transformation of a post-distortion into a pre-distortion system. We have tested our predistorter (along with a baseband adaptation of Ghaderi's) on OFDM Hiperlan signals. Both methods significantly reduced the signal distortion and the spectral regrowth. Our less complex approach proved to be even better for small peak back off values.

The paper provides real-word wireless measurement data of the intravehicular channel for both the 3-11 GHz and the 55-65 GHz frequency bands under similar conditions. By spatially averaging channel impulse response realizations within a 10 × 10 grid, we obtain the power-delay profile (PDP). The data measured at 3-11 GHz and 55-65 GHz exhibit significant differences in terms of root mean square (RMS) delay spread, number of resolvable clusters, and variance of the maximal excess delay. Moreover, we evaluate the spatial stationarity via the Pearson correlation coefficient and via the PDP collinearity, depending on the distance in the grid. The measured and calculated results indicate that a strong reverberation inside the vehicle produces similar PDPs within the range of approximately ten wavelengths. We also provide a linear piecewise model of the PDP in logarithmic scale and a generalized extreme value model of a small-scale signal fading. Our channel model is validated utilizing the Kolmogorov-Smirnov test.

This contribution documents and discusses recent wideband radio channel measurements carried out in the intra-vehicle environment. Channels in the millimeter-wave (MMW) frequency band have been measured in 55-65 GHz using open-ended rectangular waveguides. We present a channel modeling approach based on a decomposition of spatially specific Channel Impulse Responses (CIRs) into the large and small scale fading. The decomposition is done by a Hodrick-Prescott filter. We parametrize the small scale fading utilizing Maximum-likelihood estimates for the parameters of a generalized extreme value (GEV) distribution. The large scale fading is described by a two dimensional polynomial curve. We also compare simulated results with our measurement exploiting two-sample Kolmogorov-Smirnov test.

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.