Abstract
We propose three private information retrieval (PIR) protocols for distributed storage systems (DSSs) where data is
stored using an arbitrary linear code. The first two protocols, named Protocol 1 and Protocol 2, achieve privacy for
the scenario with noncolluding nodes. Protocol 1 requires a file size that is exponential in the number of files in
the system, while the file size required for Protocol 2 is independent of the number of files and is hence simpler. We
prove that, for certain linear codes, Protocol 1 achieves the maximum distance separable (MDS) PIR capacity, i.e., the
maximum PIR rate (the ratio of the amount of retrieved stored data per unit of downloaded data) for a DSS that uses an
MDS code to store any given (finite and infinite) number of files, and Protocol 2 achieves the asymptotic
MDS-PIR capacity (with infinitely large number of files in the DSS). In particular, we provide a necessary and a
sufficient condition for a code to achieve the MDS-PIR capacity and prove that cyclic codes, Reed-Muller (RM) codes,
and a class of distance-optimal local reconstruction codes achieve both the finite MDS-PIR capacity (i.e., with
any given number of files) and the asymptotic MDS-PIR capacity with Protocols 1 and 2, respectively. Furthermore, we
present a third protocol, Protocol 3, for the scenario with multiple colluding nodes, which can be seen as an
improvement of a protocol recently introduced by Freij-Hollanti et al. Similar to the noncolluding case, we
provide a necessary and a sufficient condition to achieve the maximum possible PIR rate of Protocol 3. Moreover, we
provide a particular class of codes that is suitable for this protocol and show that RM codes achieve the maximum
possible PIR rate for the protocol. For all three protocols, we present an algorithm to optimize their PIR rates.