Open Access Publications from the University of California

### Recent Work

This is the website for papers published by the Center for Pervasive Communications and Computing at the University of California, Irvine.

(2019)

## On the Necessity of Non-Shannon Information Inequalities for Storage Overhead Constrained PIR and Network Coding

(2018)

We show that to characterize the capacity of storage overhead constrained private information retrieval (PIR) with only 2 messages, and 2 databases, non-Shannon information inequalities are necessary. As a by-product of this result, we construct the smallest instance, to our knowledge, of a network coding capacity problem that requires non-Shannon inequalities.

## Optimality of Simple Layered Superposition Coding in the 3 User MISO BC with Finite Precision CSIT

(2018)

We study the 3 user multiple input single output (MISO) broadcast channel (BC) with 3 antennas at the transmitter and 1 antenna at each receiver, from the generalized degrees of freedom (GDoF) perspective, under the assumption that the channel state information at the transmitter (CSIT) is limited to finite precision. In particular, our goal is to identify a parameter regime where a simple layered superposition (SLS) coding scheme achieves the entire GDoF region. With αij representing the channel strength parameter for the link from the jth antenna of the transmitter to the ith receiver, we prove that SLS is GDoF optimal without the need for time-sharing if max(αji,αij) ≤ αii and αki + αij ≤ αii + αkj for all i,j,k ∈ [3]. The GDoF region under this condition is a convex polyhedron.

(2017)

## Interference Mitigation Using Asynchronous Transmission and Sampling Diversity

(2016)

In this paper, we show that by investigating inherent time delays between different users in a multiuser scenario, we are able to cancel interference more efficiently. Time asynchrony provides another tool to cancel interference which results in preserving other resources like frequency, time and code. Therefore, we can save the invaluable resource of frequency band and also increase spectral efficiency. A sampling method is presented which results in independent noise samples and obviates the need for the complex process of noise whitening. By taking advantage of this sampling method and its unique structure, we implement maximum-likelihood sequence detection which outperforms synchronous maximum-likelihood detection. We also present successive interference cancellation with hard decision passing which gives rise to a novel forward-backward belief propagation method. Next, the performance of zero forcing detection is analyzed. Simulation results are also presented to verify our analysis.