Identification capacity bounds for colored Gaussian channels with polynomially bounded noise spectrum and sub-linear ISI memory allow super-exponential codebook growth of order 2^(n log n R).
Identification for ISI Gaussian Channels
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abstract
We establish lower and upper bounds for the identification capacity of discrete-time Gaussian channels subject to inter-symbol interference (ISI), a canonical model in wireless communication. Our analysis accounts for deterministic encoders under peak power constraint. A principal finding is that, even when the number of ISI taps scales sub-linearly with the codeword length $n$ as $\sim n^{\kappa}$ with $\kappa \in [0,1/2),$ the number of messages that can be reliably identified grows super-exponentially in $n$ as $\sim 2^{(n \log n)R},$ where $R$ is the coding rate.
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cs.IT 1years
2026 1verdicts
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Identification for Colored Gaussian Channels
Identification capacity bounds for colored Gaussian channels with polynomially bounded noise spectrum and sub-linear ISI memory allow super-exponential codebook growth of order 2^(n log n R).