Guest Speakers

Speaker: Dr. Alexios Balatsoukas-Stimming

Title:  Practical Approximate Channel Decoders

During the so-called happy scaling era of integrated circuits, the increasing transistor count per unit area and the increasing energy-efficiency were able to offset the ever-increasing complexity of communications and digital signal processing algorithms. Unfortunately, the gains from circuit technology scaling have slowed down significantly in the last few years. (read more)

Speaker: Dr. Min Ye, Princeton University

Title:  Explicit Constructions of MDS Array Codes with Optimal Repair Bandwidth

Maximum distance separable (MDS) codes are optimal error-correcting codes in the sense that they provide the maximum failure-tolerance for a given number of parity nodes. (Read more)

Speaker: Dr. Hsuan-Yin Lin, Simula@UiB, Bergen, Norway

Title: Achieving Private Information Retrieval Capacity in Distributed Storage Using an Arbitrary Linear Code

In this talk, we will present a private information retrieval (PIR) protocol for distributed storage systems (DSSs) with noncolluding nodes where data is stored using an arbitrary linear code. (Read more)

Speaker:  Mehul Motani, National University of Singapore (NUS) and a Visiting Research Collaborator at Princeton University

Title: Coding for Constrained Communication Systems

We motivate the study of codes for constrained communication systems.  Constrained codes are useful for applications such as power line communications, low cost authentication systems, and joint energy and information transfer.  (Read more)

Speaker:  Jasper Goseling, University of Twente

​Title: Sign-Compute-Resolve for Tree Splitting Random Access

A framework for random access is presented that is based on three elements: physical-layer network coding (PLNC), signature codes and tree splitting. In presence of a collision, physical-layer network coding enables the receiver to decode, i.e. compute the sum of the packets that were transmitted by the individual users. (Read more)

Speaker:  Mario Goldenbaum, Postdoctoral Research Fellow at Princeton University and Lecturer at Technical University of Munich, Germany

Title: On Secure Computation over Multiple-Access Wiretap Channels

An integral part of the emerging Internet of Things (IoT) will be the reliable and efficient computation of functions that depend on the data available at spatially distributed terminals/agents (e.g., smart meters). (Read more)

Speaker: Dr. Brian Krongold, University of Melbourne, Austrailia

Title: Energy Consumption Modelling and Optimization of Cooperative Relay Transmission

Cooperative relays have been used in many wireless applications to reduce transmit power and add receiver diversity.  We start with an energy analysis of a point-to-point link, including both analog and digital electronics' energy consumption. (Read more

Speaker: Emina Soljanin, Rutgers University

Title: "Cloud Storage Space vs. Download Time for Large Files

A radio frequency (RF) signal carries both energy and information. From this standpoint, a variety of modern wireless systems suggest that RF signals can be simultaneously used for information and energy transmission. However, these two tasks are usually conflicting and thus, there exists a trade-off between information transmission rates and energy transmission rates in most of point-to-point channels and multi-user channels. (Read more)

Speaker: Alex Dytso, Princeton University

Title: "On the Minimum p-th Error in Gaussian Noise Channels and its Applications"

Selection of fidelity criteria or quantitative performance measure is an important first step, in engineering applications, for comparing different signal processing methods and optimizing signal processing algorithms. In this work, we study a large class of such fidelity criteria (cost functions) termed Minimum Mean p-th Errors (MMPE's) where the classical Minimum Mean Square Error (MMSE) is a special case of the MMPE. (Read More)

Speaker: Professor Stefano Rini, National Chiao-Tung University, Taiwan

Title: A Little Knowledge is Truly a Dangerous Thing: Interference Pre-cancellation in the Presence of Partial Channel Knowledge

In this talk we argue that interference pre-cancellation is effective only when very precise channel estimates are available at the users, a condition which is not easily attainable in many communication networks. (Read more)

Speaker: Dr. Visa Koivunen, Dept of Signal Processing and Acoustics, Aalto University, Finland

Title: Robust, Scalable and Fast Bootstrap Method for Analyzing Large Scale Data

This talk address the problem of performing statistical inference for large scale data sets i.e., Big Data. The volume and dimensionality of the data may be so high that it cannot be processed or stored in a single computing node. We propose a scalable, statistically robust and computationally efficient bootstrap method, compatible with distributed processing and storage systems. (Read More)

Speaker: Dr. Yana Shkel, Princeton University

Title: f-Separable Distortion Measures: Towards Better Models for Data Compression

Rate-Distortion Theory is a branch of Information Theory which provides theoretical foundation for lossy data compression. In this setting, the decompressed data need not match original data exactly; however, it must be reconstructed with a prescribed fidelity which is modeled by a distortion measure. (Read More

Speaker: Dr. Flavio Calmon, IBM T.J. Watson Research Center and Harvard University

Title: Estimation and Privacy

Widespread collection of data has led to new and challenging privacy and security risks. There is a need to engineer mechanisms that allow users to selectively disclose their data to a third party in order to achieve a utility goal (e.g. receive high quality product recommendations), while restricting the release of private information (e.g. not revealing a given medical condition). In this talk, we use tools from information theory, statistics and estimation theory to characterize the fundamental limits of estimation when only partial statistics of the data are known. (Read More)

Speaker: Selma Belhadj Amor

Title: Fundamental Limits of Simultaneous Energy and Information Transmission

A radio frequency (RF) signal carries both energy and information. From this standpoint, a variety of modern wireless systems suggest that RF signals can be simultaneously used for information and energy transmission. However, these two tasks are usually conflicting and thus, there exists a trade-off between information transmission rates and energy transmission rates in most of point-to-point channels and multi-user channels. (Read More)

Speaker: Wei Yang

Title: Fading Channels: Capacity and Channel Coding Rate in the Finite-Blocklength Regime

Information-theoretic studies on the fundamental limits of communication over wireless fading channels typically rely on simplifying assumptions, such as perfect channel state information (CSI), infinite blocklength, and vanishing probability of error. Although these assumptions are reasonable for most of the current wireless communication systems, they may be inaccurate for next-generation wireless systems.  (Read More)

Speaker: Ziv Goldfeld

Title: Semantic Security versus Active Eavesdroppers

Information theoretic security has adopted the weak- and strong-secrecy metrics as a standard for measuring security. Respectively, weak- and strong-secrecy refer to the normalized and unnormalized mutual information between the secret message and the channel symbol string observed by the eavesdropper. (Read More)

Speaker: Mohammad Ali Maddah-Ali, Bell Labs, Nokia

Title: Fundamental Limits of Communication, Computation, and Storage: An information Theoretic Perspective

The objective of this talk is to investigate the fundamental tradeoffs among communication, computation, and storage, as the major components of the data infrastructures, from an information theoretic perspective. (Read More)

Speaker: Qi Chen,Postdoctoral Fellow both at the Institute of Network Coding, The Chinese University of Hong Kong and ECE Department, Drexel University

Title: Laws of Information Theory: Entropy and Information Inequalities

Constraints on the (joint) entropies for a given set of random variables, mostly in the form of information inequalities, are considered as the laws of information theory not only because converse theorems of coding theorems are proved by information inequalities, but also they bound the capacities or capacity regions  of many information theory problems, such as network coding, data storage, secret sharing, etc. (Read More)

Speaker: Megumi Kaneko, Assistant Professor in the Department of Systems Science, Graduate School of Informatics, Kyoto University

Title: Distributed Resource Allocation with Local CSI Overhearing and Scheduling Prediction for OFDMA Heterogeneous Networks

In this work, we propose a resource allocation method for the downlink of an OFDMA-based macrocell/femtocell overlaid Heterogeneous Network (HetNet). (Read More)

Ronit Bustin, Postdoctoral Research Associate in the Department of Electrical Engineering at Princeton University

Title: Gaussian Channels: I-MMSE at Every SNR

Multi-user information theory presents many open problems, even in the simple Gaussian regime. One such prominent problem is the two-user Gaussian interference channel which has been a long standing open problem for over 30 years. (Read More)

Speaker: Erik G. Larsson, Professor at Linköping University in Sweden and currently also a visiting fellow at Princeton University

Title: Massive MIMO for 5G Wireless

Massive MIMO is a leading 5G technology candidate, that aims at delivering uniformly good service to wireless terminals in high-mobility environments.  The key concept is to equip base stations with large arrays of antennas that serve many terminals simultaneously, in the same time-frequency resource.  (Read More)