Imposing exponentially small identification errors removes the superlinear message growth of deterministic identification and yields linear rates governed by the Minkowski dimension of the channel output set.
Identification Capacity of the Discrete-Time Poisson Channel
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abstract
Numerous applications in the field of molecular communications (MC) such as healthcare systems are often event-driven. The conventional Shannon capacity may not be the appropriate metric for assessing performance in such cases. We propose the identification (ID) capacity as an alternative metric. Particularly, we consider randomized identification (RI) over the discrete-time Poisson channel (DTPC), which is typically used as a model for MC systems that utilize molecule-counting receivers. In the ID paradigm, the receiver's focus is not on decoding the message sent. However, he wants to determine whether a message of particular significance to him has been sent or not. In contrast to Shannon transmission codes, the size of ID codes for a Discrete Memoryless Channel (DMC) grows doubly exponentially fast with the blocklength, if randomized encoding is used. In this paper, we derive the capacity formula for RI over the DTPC subject to some peak and average power constraints. Furthermore, we analyze the case of state-dependent DTPC.
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Rate-reliability tradeoff for deterministic identification
Imposing exponentially small identification errors removes the superlinear message growth of deterministic identification and yields linear rates governed by the Minkowski dimension of the channel output set.