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.

## On the Synergistic Benefits of Reconfigurable Antennas and Partial Channel Knowledge for the MIMO Interference Channel

(2021)

Blind Interference Alignment (BIA) schemes create and exploit channel coherence patterns without the knowledge of channel realizations at transmitters, while beamforming schemes rely primarily on channel knowledge available to the transmit- ters without regard to channel coherence patterns. In order to explore the compatibility of these disparate ideas and the possibility of synergistic gains, this work studies the Degrees of Freedom (DoF) of the 2-user (?1 × ?1)(?2 × ?2) Multiple- Input Multiple-Output (MIMO) Interference Channel (IC) where Transmitter 1 is equipped with reconfigurable antennas and has no channel knowledge, while Transmitter 2 has partial channel knowledge but no reconfigurable antennas. Taking a fundamental dimensional analysis perspective, the main question is to identify which antenna configurations allow synergistic DoF gains. The main results of this work are two-fold. The first result identifies antenna configurations where both reconfigurable antennas and partial channel knowledge are individually beneficial, as those where ?1 < ?1 < min(?2,?2). The second result shows that synergistic gains exist in each of these settings, over the best known solutions that rely on either reconfigurable antennas or partial channel knowledge alone. Coding schemes that jointly exploit partial channel knowledge and reconfigurable antennas emerge as a byproduct of the analysis.

## Exploring Aligned-Images Bounds:Robust Secure GDoF of 3-to-1 Interference Channel

(2020)

Sum-set inequalities based on Aligned-Images bounds have been recently introduced as essential elements of converse proofs for asymptotic/approximate wireless network capacity characterizations under robust assumptions, i.e., as- sumptions that limit channel knowledge at the transmitters to finite precision. While these sum-set inequalities have produced robust Generalized Degrees of Freedom (GDoF) results for various wireless networks, their scope and limitations in general are not well understood. To explore these limitations, in this work we study the robust secure GDoF of a symmetric 3-user many- to-one interference channel. We identify regimes where existing sum-set inequalities are sufficient, settling the GDoF for those settings. For the remaining regime we conjecture the form of new sum-set inequalities that may be needed, whose validity remains an open problem for future work.

(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.