Conformal Decode-or-Erase: Certified Spiking Decoding for Short-Packet URLLC

Abstract

Ultra-reliable low-latency communication (URLLC) must deliver short packets within a hard deadline at low error probability. A conventional receiver waits for the full packet before deciding, spending the full latency and energy even though many packets are resolvable well before the deadline. Committing early without a reliability guarantee, however, risks a silent wrong delivery, so the receiver is left choosing between wasted resources and uncontrolled errors. We propose Conformal Decode-or-Erase (CoDE), a spiking neural network (SNN) receiver that resolves this tension. The SNN reads one symbol per channel use and forms, at predetermined checkpoints, a set of candidate messages that provably contains the true one with a prescribed probability. CoDE commits once the set narrows to a singleton and otherwise declares an erasure that triggers hybrid automatic repeat request (HARQ) retransmission. A wrong commit means the true message fell outside that singleton. Hence, the prediction set provides an upper bound on the undetected error rate in a distribution-free manner and for any pretrained SNN and any calibration size. Simulations confirm reliability at roughly half a fixed-length decoder's latency and compute.