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Random jammers that overpower transmitted signals are a practical concern formany wireless communication protocols. As such, wireless receivers must be ableto cope with standard channel noise and jamming (intentional or unintentional).To address this challenge, we propose a novel method to augment the resilienceof the recent family of universal error-correcting GRAND algorithms. Thismethod, called Erasure Decoding by Gaussian Elimination (EDGE), impacts thesyndrome check block and is applicable to any variant of GRAND. We show thatthe proposed EDGE method naturally reverts to the original syndrome checkfunction in the absence of erasures caused by jamming. We demonstrate this byimplementing and evaluating GRAND-EDGE and ORBGRAND-EDGE. Simulation results,using a Random Linear Code (RLC) with a code rate of $105/128$, show that theEDGE variants lower both the Block Error Rate (BLER) and the computationalcomplexity by up to five order of magnitude compared to the original GRAND andORBGRAND algorithms. We further compare ORBGRAND-EDGE to Ordered StatisticsDecoding (OSD), and demonstrate an improvement of up to three orders ofmagnitude in the BLER.

GRAND-EDGE: A Universal, Jamming-resilient Algorithm with Error-and-Erasure Decoding