Blind Interference Alignment for Private Information Retrieval
This work addresses the efficiency of private data retrieval for users in distributed database systems, representing a foundational advance in information theory.
The paper connects blind interference alignment (BIA) with private information retrieval (PIR) to tackle the problem of optimizing download cost in PIR, achieving an information-theoretic optimal solution for K=2 messages and arbitrary N databases.
Blind interference alignment (BIA) refers to interference alignment schemes that are designed only based on channel coherence pattern knowledge at the transmitters (the "blind" transmitters do not know the exact channel values). Private information retrieval (PIR) refers to the problem where a user retrieves one out of K messages from N non-communicating databases (each holds all K messages) without revealing anything about the identity of the desired message index to any individual database. In this paper, we identify an intriguing connection between PIR and BIA. Inspired by this connection, we characterize the information theoretic optimal download cost of PIR, when we have K = 2 messages and the number of databases, N, is arbitrary.