Semantic Private Information Retrieval From MDS-Coded Databases
Sajani Vithana, Karim Banawan, Şennur Ulukuş · 2021
We investigate the problem of semantic private information retrieval (PIR) from coded databases, where a user requires to download a message out of$M$independent messages, without revealing its identity to the databases. These messages are coded using an (N, K) MDS code and stored in$N$non-colluding databases. The$M$messages are allowed to have different semantics, e.g., different sizes and different probabilities of retrieval. We characterize the exact capacity of semantic PIR with coded databases, and provide an achievable scheme with non-uniform subpacketization. We show that the retrieval rate of semantic PIR with coded databases outperforms that of classical PIR with coded databases when the effects of zero padding shorter messages are taken into account.