The Nyquist-Shannon sampling theorem states that bandlimited signals can be perfectly reconstructed from samples taken at a fixed rate. Signals with varying spectral content are not considered, which leads to an unnecessarily high number of samples in signal intervals with narrowband content. An extension of the Nyquist-Shannon theorem enables the definition of variable bandwidth signals through nonlinear time axis distortion. This technique, known as time warping, enables variable-rate sampling based on instantaneous bandwidth, resulting in sample numbers proportional to the average bandwidth rather than the maximum bandwidth as in classical sampling. In practice, however, the instantaneous bandwidth of a signal is unknown, except for a few analytically determinable exceptions. In this paper, we introduce a novel spectrogram-based algorithm for estimating the instantaneous bandwidth of classically sampled signals, allowing to project them to variable bandwidth signals. We examine the tradeoff between sample reduction and reconstruction accuracy of electrocardiograms and compare the results to classical downsampling.

Wireless sensor nodes need a drastically reduced technical complexity to fit constraints of future applications. Reducing complexity often results in a degradation of energy and bandwidth efficiency. An interesting new approach that promises to reduce both technical complexity and energy consumption is event-based communication (EBC). While practical low-complexity implementations of such systems have already been proposed, the general question of energy and bandwidth efficiency remains open. In this paper, we compare these between EBC and a system relying on classical uniform sampling. We show that EBC is indeed much more energy efficient, and this comes at the cost of bandwidth efficiency. Therefore EBC is particularly suitable in combination with ultra-wideband communication.

Wireless sensor nodes need a drastically reduced technical complexity to fit constraints of future applications. Current multi-user detection requires large amounts of technical complexity, leading to increased sensor node size, cost and energy consumption. Instead of deterministic resource allocation we propose an ultra-low-complexity communication scheme using truly asynchronous direct random access. The randomness in this scheme solely stems from manufacturing tolerances, further decreasing cost, size and energy consumption. While these tolerances have to be compensated for at great expense in classic digital communication, we use them specifically to enable multi-user detection with sensor nodes that do not differ in design or configuration. After studying the necessary steps for a measurement reconstruction at the base station we propose an algorithm, based on a time-frequency transformation in combination with a peak search to implement the first of these steps. We derive an analytical lower bound on the user-capacity of the scheme and compare the results with the performance of the proposed detection algorithm.

Wireless Sensor Nodes communicating measurements to a base station is one of the scenarios in the emerging field of Machine-Type-Communication. Those systems rely on low complexity of the nodes, due to cost and energy consumption. The main idea of this paper is to employ a low complexity analog modulation scheme in the node, and combine it with state of the art digital signal processing in the base station. Specifically, we focus on Amplitude Modulation in a point to point scenario facing noise and hardware offsets. We show that under certain assumptions this transmission can be described by a linear model. Subsequently we utilize payload (measurement) signal structure, namely sparsity, to estimate the payload signals as well as the hardware offsets using a dictionary learning algorithm. Numerical simulations show, that for realistic noise assumptions the algorithms are able to reconstruct payload signals and estimate hardware offsets.

In this paper the development and implementation of a Telecommand (TC) receiver application for microsatellite communication is presented. The TC receiver application is executed and operated by a highly integrated Generic Software-Defined Radio (GSDR) platform. This platform architecture is designed for the reliable operation of multiple radio frequency applications on spacecraft. For the development and implementation process of the TC receiver application, a new model-based development workflow by Matlab/Simulink is used and evaluated.

In this paper the development and implementation of a Telecommand (TC) receiver application for microsatellite communication is presented. The TC receiver application is executed and operated by a highly integrated Generic Software-Defined Radio (GSDR) platform. This platform architecture is designed for the reliable operation of multiple radio frequency applications on spacecraft. For the development and implementation process of the TC receiver application, a new model-based development workflow by Matlab/Simulink is used and evaluated.