Communicating Correlated Sources Over an Interference Channel

A new coding technique, based on \textit{fixed block-length} codes, is proposed for the problem of communicating a pair of correlated sources over a $2-$user interference channel. Its performance is analyzed to derive a new set of sufficient conditions. The latter is proven to be strictly less binding than the current known best, which is due to Liu and Chen [Dec, 2011]. Our findings are inspired by Dueck's example [March, 1981]

Achievable rate region for three user discrete broadcast channel based on coset codes

We present an achievable rate region for the general three user discrete memoryless broadcast channel, based on nested coset codes. We characterize 3-to-1 discrete broadcast channels, a class of broadcast channels for which the best known coding technique\footnote{We henceforth refer to this as Marton's coding for three user discrete broadcast channel.}, which is obtained by a natural generalization of that proposed by Marton for the general two user discrete broadcast channel, is strictly sub-optimal. In particular, we identify a novel 3-to-1 discrete broadcast channel for which Marton's coding is \textit{analytically} proved to be strictly suboptimal. We present achievable rate regions for the general 3-to-1 discrete broadcast channels, based on nested coset codes, that strictly enlarge Marton's rate region for the aforementioned channel. We generalize this to present achievable rate region for the general three user discrete broadcast channel. Combining together Marton's coding and that proposed herein, we propose the best known coding technique, for a general three user discrete broadcast channel.Comment: A non-additive 3-user discrete broadcast channel is identified for which achievable rate region based on coset codes is analytically proven to be strictly larger than that achievable using unstructured iid codes. This version is submitted to IEEE Transactions on Information Theor

Computing sum of sources over an arbitrary multiple access channel

The problem of computing sum of sources over a multiple access channel (MAC) is considered. Building on the technique of linear computation coding (LCC) proposed by Nazer and Gastpar [2007], we employ the ensemble of nested coset codes to derive a new set of sufficient conditions for computing the sum of sources over an \textit{arbitrary} MAC. The optimality of nested coset codes [Padakandla, Pradhan 2011] enables this technique outperform LCC even for linear MAC with a structural match. Examples of nonadditive MAC for which the technique proposed herein outperforms separation and systematic based computation are also presented. Finally, this technique is enhanced by incorporating separation based strategy, leading to a new set of sufficient conditions for computing the sum over a MAC.Comment: Contains proof of the main theorem and a few minor corrections. Contents of this article have been accepted for presentation at ISIT201

Fat Shattering, Joint Measurability, and PAC Learnability of POVM Hypothesis Classes

We characterize learnability for quantum measurement classes by establishing matching necessary and sufficient conditions for their PAC learnability, along with corresponding sample complexity bounds, in the setting where the learner is given access only to prepared quantum states. We first probe the results from previous works on this setting. We show that the empirical risk defined in previous works and matching the definition in the classical theory fails to satisfy the uniform convergence property enjoyed in the classical setting for some learnable classes. Moreover, we show that VC dimension generalization upper bounds in previous work are frequently infinite, even for finite-dimensional POVM classes. To surmount the failure of the standard ERM to satisfy uniform convergence, we define a new learning rule -- denoised ERM. We show this to be a universal learning rule for POVM and probabilistically observed concept classes, and the condition for it to satisfy uniform convergence is finite fat shattering dimension of the class. We give quantitative sample complexity upper and lower bounds for learnability in terms of finite fat-shattering dimension and a notion of approximate finite partitionability into approximately jointly measurable subsets, which allow for sample reuse. We then show that finite fat shattering dimension implies finite coverability by approximately jointly measurable subsets, leading to our matching conditions. We also show that every measurement class defined on a finite-dimensional Hilbert space is PAC learnable. We illustrate our results on several example POVM classes.Comment: 33 page

An Algebraic Framework for Multi-Terminal Communication.

We consider the problem of developing coding techniques and characterizing information-theoretic achievable rate regions for the following three multi-terminal communication channels. Firstly, we study an interference channel with three transmitter receiver pairs (3-IC). Secondly, we consider a broadcast channel with three receivers (3-BC), wherein three independent information streams are to be communicated to the three receivers. Thirdly, we consider a two user multiple access channel (MAC) with channel state information distributed at the transmitters (MAC-DSTx). The above channels are assumed discrete, memoryless and used without feedback. Current known coding technique for a general instance of these channels are based on independent unstructured codes. Recognizing the need for codes endowed with algebraic closure properties, we identify three ensembles of coset codes. We propose coding techniques based on these ensembles that exploit their algebraic closure property. We develop tools to characterize information-theoretic performance of the proposed coding techniques. These enable us derive achievable rate regions for a general instance of the above channels. The current known achievable rate regions can be enlarged by gluing together current known coding techniques and the ones proposed herein. Moreover, such an enlargement, as indicated below, is proven to be strict for certain instances. We identify additive and non-additive instances of 3-IC for which the derived achievable rate region is analytically proven to be strictly larger than current known largest. Moreover, for these channels, the proposed coding techniques based on coset codes is capacity achieving. We also identify a vector 3-BC for which the achievable rate region derived herein is analytically proven to be strictly larger than the current known largest. This vector 3-BC is the first known broadcast channel, for which superposition and binning of unstructured independent codes, proposed over three decades ago, can be strictly improved upon. We also identify non-additive and non-symmetric instances of MAC-DSTx for which the proposed coding technique is verified, through computation, to yield strictly larger achievable rate regions. Finally, we develop a coding technique based on nested coset codes to characterize a weaker set of sufficient conditions for the problem of computing sum of sources over a discrete memoryless MAC.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107264/1/arunpr_1.pd