Soft GRAND under Channel Switching and Drift

2026-08-23

AI Summary

研究解决了软GRAND在信道切换和漂移下的解码误差问题，通过限定查询排名并结合精确随机子集碰撞概率来控制误差。

Abstract

Under channel switching or drift, the posterior used to order soft GRAND queries can differ from the matched correction posterior, which can increase rank and finite-budget decoding error. We bound log query rank by matched posterior self-information plus positive log-posterior mismatch; exact random-subset collision probabilities yield GRANDAB error bounds. For switching among memoryless channels with capacity-achieving uniform input, a state-path mixture yields vanishing error uniformly over admissible paths below the minimum constituent capacity when log path-class size is sublinear. For drift, pilot refresh bounds mismatch and yields the continuous minimizer of a tracking upper bound. Generalized-Gaussian BPSK experiments evaluate both.

Problem

• channel switching
• posterior mismatch
• decoding error

Innovation

• channel switching
• posterior mismatch
• state-path mixture
• pilot refresh