Using Parseval-frame projections onto shared anchor features, a receiver can approximately reconstruct the latent vectors of an unseen, independently trained encoder; a Lyapunov scheduler then allocates bandwidth, CPU, and quantization to meet latency and accuracy targets.
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Frame-Based Zero-Shot Semantic Channel Equalization for AI-Native Communications
Using Parseval-frame projections onto shared anchor features, a receiver can approximately reconstruct the latent vectors of an unseen, independently trained encoder; a Lyapunov scheduler then allocates bandwidth, CPU, and quantization to meet latency and accuracy targets.