An Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments

Unmanned Aerial Vehicles (UAVs) show promise in a variety of applications and recently were explored in the area of Search and Rescue (SAR) for finding victims. In this paper we consider the problem of finding multiple unknown stationary transmitters in a discrete simulated unknown environment, where the goal is to locate all transmitters in as short a time as possible. Existing solutions in the UAV search space typically search for a single target, assume a simple environment, assume target properties are known or have other unrealistic assumptions. We simulate large, complex environments with limited a priori information about the environment and transmitter properties. We propose a Bayesian search algorithm, Information Exploration Behaviour (IEB), that maximizes predicted information gain at each search step, incorporating information from multiple sensors whilst making minimal assumptions about the scenario. This search method is inspired by the information theory concept of empowerment. Our algorithm shows significant speed-up compared to baseline algorithms, being orders of magnitude faster than a random agent and 10 times faster than a lawnmower strategy, even in complex scenarios. The IEB agent is able to make use of received transmitter signals from unknown sources and incorporate both an exploration and search strategy.

A Bivariate Volterra Series Model for the Design of Power Amplifier Digital Predistorters

The operation of the power amplifier (PA) in wireless transmitters presents a trade-off between linearity and power efficiency, being more efficient when the device exhibits the highest nonlinearity. Its modeling and linearization performance depend on the quality of the underlying Volterra models that are characterized by the presence of relevant terms amongst the enormous amount of regressors that these models generate. The presence of PA mechanisms that generate an internal state variable motivates the adoption of a bivariate Volterra series perspective with the aim of enhancing modeling capabilities through the inclussion of beneficial terms. In this paper, the conventional Volterra-based models are enhanced by the addition of terms, including cross products of the input signal and the new internal variable. The bivariate versions of the general full Volterra (FV) model and one of its pruned versions, referred to as the circuit-knowledge based Volterra (CKV) model, are derived by considering the signal envelope as the internal variable and applying the proposed methodology to the univariate models. A comparative assessment of the bivariate models versus their conventional counterparts is experimentally performed for the modeling of two PAs driven by a 30 MHz 5G New Radio signal: a class AB PA and a class J PA. The results for the digital predistortion of the class AB PA under a direct learning architecture reveal the benefits in linearization performance produced by the bivariate CKV model structure compared to that of the univariate CKV model.

Impact of GPS Interference on Time Synchronization of DVB-T Transmitters

Nowadays, the Global Positioning System (GPS) is widely used in all aspects of our lives. GPS signals are not used only in positioning and navigation applications and services in transport and military, but, thanks to quite precise information about time, also for synchronization of world trade and synchronization of wireless transmitters. However, with the recent spread of location-based services, a large number of GPS jammers had appeared. Use of these jammers is prohibited by law; however, their use is gaining popularity especially in the transport segment since jammers can be used to trick vehicle onboard units and help avoid paying toll fees on highways or avoid tracking of company cars when used privately. In this paper, we will investigate the impact of GPS interference caused by jamming and spoofing on the synchronization of Single Frequency Network (SFN) Digital Video Broadcasting–Terrestrial (DVB-T) transmitters. Since GPS signals are used in the DVB-T SFN to provide synchronization which is crucial for the correct network operation, the interference of GPS signals can cause problems with signal distribution. Thus, signals received from a DVB-T SFN network might be out of synchronization and disrupt the service for users.