Locally Best Invariant Test for Multiple Primary User Spectrum Sensing

TL;DR

This paper introduces a noise-uncertainty-free, optimal detector for multi-antenna cooperative spectrum sensing in cognitive radio networks with multiple primary users, providing analytical formulas and simulation validation.

Contribution

It derives exact moments of test statistics for a new detector, enabling accurate false alarm and threshold calculations in multi-user spectrum sensing.

Findings

The detector performs accurately in low SNR regimes.

Analytical formulas match simulation results.

Outperforms existing detectors in realistic scenarios.

Abstract

We consider multi-antenna cooperative spectrum sensing in cognitive radio networks, when there may be multiple primary users. A noise-uncertainty-free detector that is optimal in the low signal to noise ratio regime is analyzed in such a scenario. Specifically, we derive the exact moments of the test statistics involved, which lead to simple and accurate analytical formulae for the false alarm probability and the decision threshold. Simulations are provided to examine the accuracy of the derived results, and to compare with other detectors in realistic sensing scenarios.