Noisy Private Information Retrieval: On Separability of Channel Coding and Information Retrieval
Karim Banawan, Sennur Ulukus

TL;DR
This paper investigates the capacity of noisy private information retrieval systems over noisy channels and multiple access channels, establishing when channel coding can be separated from retrieval and when it cannot, with implications for privacy and efficiency.
Contribution
It characterizes the PIR capacity with noisy channels, proves the near-optimality of separation in NPIR, and demonstrates inseparability in MAC-PIR for certain channels, providing new schemes and capacity results.
Findings
Separation between channel coding and retrieval is optimal for NPIR with up to 3 messages.
In MAC-PIR, channel coding and retrieval are inseparable for additive and conjunction/disjunction MACs.
Full capacity can be achieved by exploiting channel properties, especially in MAC-PIR scenarios.
Abstract
We consider the problem of noisy private information retrieval (NPIR) from non-communicating databases, each storing the same set of messages. In this model, the answer strings are not returned through noiseless bit pipes, but rather through \emph{noisy} memoryless channels. We aim at characterizing the PIR capacity for this model as a function of the statistical information measures of the noisy channels such as entropy and mutual information. We derive a general upper bound for the retrieval rate in the form of a max-min optimization. We use the achievable schemes for the PIR problem under asymmetric traffic constraints and random coding arguments to derive a general lower bound for the retrieval rate. The upper and lower bounds match for and , for any , and any noisy channel. The results imply that separation between channel coding and retrieval is optimal…
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