Asymptotic Signal Detection Rates with 1-bit Array Measurements

TL;DR

This paper analyzes the detection performance of antenna arrays using low-complexity 1-bit digitization, deriving detection rate expressions and demonstrating reliable radio source monitoring with minimal hardware complexity.

Contribution

It introduces a probabilistic model for 1-bit array measurements and derives analytic detection rates, advancing low-power radio monitoring techniques.

Findings

Detection rates derived for 1-bit array measurements.

Reliable radio source monitoring achievable with few binary sensors.

Performance depends on number of antennas and observation time.

Abstract

This work considers detecting the presence of a band-limited random radio source using an antenna array featuring a low-complexity digitization process with single-bit output resolution. In contrast to high-resolution analog-to-digital conversion, such a direct transformation of the analog radio measurements to a binary representation can be implemented hardware and energy-efficient. However, the probabilistic model of the binary receive data becomes challenging. Therefore, we first consider the Neyman-Pearson test within generic exponential families and derive the associated analytic detection rate expressions. Then we use a specific replacement model for the binary likelihood and study the achievable detection performance with 1- bit radio array measurements. As an application, we explore the capability of a low-complexity GPS spectrum monitoring system with different numbers of antennas and different observation intervals. Results show that with a moderate amount of binary sensors it is possible to reliably perform the monitoring task.