Identification for Inverse Gaussian Channels
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arXiv
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866917467921580032 |
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| author | Salariseddigh, Mohammad Javad |
| author_facet | Salariseddigh, Mohammad Javad |
| contents | We derive lower and upper bounds on the identification capacity of inverse Gaussian channels, a fundamental model for molecular communications in fluid environments. The analysis considers deterministic encoding schemes under a peak time constraint and characterizes the asymptotic growth of codebook sizes. A central result reveals that, under a mild regularity condition on the noise, i.e., the stochastic first arrival time of an information-carrying molecule propagating via diffusion and drift to the receiver, the identification capacity exhibits super-exponential growth in the codeword length, $n,$ i.e., $\sim 2^{(n \log n)R},$ where $R$ is the coding rate. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_06103 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Identification for Inverse Gaussian Channels Salariseddigh, Mohammad Javad Information Theory We derive lower and upper bounds on the identification capacity of inverse Gaussian channels, a fundamental model for molecular communications in fluid environments. The analysis considers deterministic encoding schemes under a peak time constraint and characterizes the asymptotic growth of codebook sizes. A central result reveals that, under a mild regularity condition on the noise, i.e., the stochastic first arrival time of an information-carrying molecule propagating via diffusion and drift to the receiver, the identification capacity exhibits super-exponential growth in the codeword length, $n,$ i.e., $\sim 2^{(n \log n)R},$ where $R$ is the coding rate. |
| title | Identification for Inverse Gaussian Channels |
| topic | Information Theory |
| url | https://arxiv.org/abs/2605.06103 |