Latency Analysis for Sequential Detection in Low-Complexity Binary Radio Systems

Abstract

We consider the problem of making a quick decision in favor of one of two possible physical signal models while the numerical measurements are acquired by sensing devices featuring minimal digitization complexity. Therefore, the digital data streams available for statistical processing are binary and exhibit temporal and spatial dependencies. To handle the intractable multivariate binary data model, we first consider sequential tests for exponential family distributions. Within this generic probabilistic framework, we identify adaptive approximations for the log-likelihood ratio and the Kullback-Leibler divergence. The results allow designing sequential detectors for binary radio systems and analyzing their average run-time along classical arguments of Wald. In particular, the derived tests exploit the spatio-temporal correlation structure of the analog sensor signals engraved into the binary measurements. As an application, we consider the specification of binary sensing architectures for cognitive radio and GNSS spectrum monitoring where our results characterize the sequential detection latency as a function of the temporal oversampling and the number of antennas. Finally, we evaluate the efficiency of the proposed algorithms and illustrate the accuracy of our analysis via Monte-Carlo simulations.

Glancing Through Massive Binary Radio Lenses: Hardware-Aware Interferometry With 1-Bit Sensors

“…The binary telescope with M = 92 antennas outperforms all three 64-bit stations with M = 46 array elements in terms of imaging uncertainty, although the measurement data is by a factor 32 smaller. These results confirm that reducing the A/D resolution to 1-bit and doubling the number of receivers is an effective method to obtain highperformance low-complexity sensing architectures [17].…”

“…Key to such a progressive scientific platform is the transfer of theoretic advances in hardware-aware probabilistic signal modeling and likelihood-oriented statistical data processing [16], [17] to the practical design of all-digital radio telescope systems. As a firm orientation point for this challenging endeavor, the envisaged physical system is defined by sketching the architecture and components of a radio telescope which we refer to as The Massive Binary Radio Lenses.…”

Spectral Power Parameter Estimation of Random Sources with Binary Sampled Signals

“…The simplicity of basic digital processing steps, small sensor data volume, and energy-efficient analog front-end design make it possible to deploy higher temporal, spectral, and spatial sampling rates. Such, with the same A/D resources, digital measurements can be acquired, which contain more information about the analog signal model [11]. To extract all this information from the data, efficient binary signal processing methods are required.…”