Contributed and Invited Presentations

(Sharif University of Technology, Iran)
Abstract: Coding is known as an effective approach to deal with some of the major challenges in distributed information systems in terms of security of the network, privacy of the data, and efficiency of the resource management. The current solutions are often based on expanding the existing coding tools and techniques, still following the conventional mindset. In this talk, we argue that there are some major scenarios and thread models that do not conform with the traditional rules. For example: (1) Coding techniques are often designed for "exact error-free decoding". However, in some scenarios, e.g. straggler-resistance computing for machine learning, only an "approximate decoding" is enough, (2) In conventional coding techniques, "input sources" are supposed to be conveyed and decoded correctly. However, in some scenarios (e.g. sharded blockchains), some parts of "input symbols" are chosen and distributed adversarially to prevent "other input symbols" from being recovered correctly. In this talk, we will review some solutions and bounds for those scenarios and discuss some open problems.
(Weizmann Institute of Science, Israel)
Abstract: The famous Shannon-Nyquist theorem has become a landmark in analog to digital conversion and the development of digital signal processing algorithms. However, in many modern applications, the signal bandwidths have increased tremendously, while the acquisition capabilities have not scaled sufficiently fast. Furthermore, the resulting high rate digital data requires storage, communication and processing at very high rates which is computationally expensive and requires large amounts of power. In this talk we consider a general framework for communication and sensing including sub-Nyquist sampling, quantization and processing in space, time and frequency which allows to dramatically reduce the number of antennas, sampling rates, number of bits and band occupancy in a variety of applications. Our framework relies on exploiting signal structure, quantization and the processing task in both standard processing and in deep learning networks leading to a new framework for model-based deep learning. It also allows for the development of efficient joint radar-communication systems. We consider applications of these ideas to a variety of problems in wireless communications, imaging, efficient massive MIMO systems, automotive radar and ultrasound imaging and show several demos of real-time sub-Nyquist prototypes including a wireless ultrasound probe, sub-Nyquist automotive radar, cognitive radio and radar, dual radar-communication systems, analog precoding, sparse antenna arrays, and a deep Viterbi decoder. We end by discussing more generally how models can be used in deep learning methods with application to a variety of communication settings.
(University of Electro-Communications)
Abstract: In this plenary talk we present our previous works on information theoretic security consisting of three miscellaneous topics. Those topics provide some specific but interesting problems arising inherently in communication systems with security requirement. The first topics is the relay channel with confidential messages (the RCC), which provides an interesting subject discussing an interplay between the two roles of the relay as a “helper” and as an “eavesdropper”. The second topics is the broadcast channel with confidential messages (the BCC) with randomness constraints stochastic encoders. In the BCC, we study a practical problem that we have some resource constraint on “dummy random variables” used for the stochastic encoders. The third topic is our recent work on an information theoretic analysis of the Shannon cipher system under side-channel attacks. In this topics we discuss some interesting relationship between the privacy amplification and the strong converse theorem for a certain multiterminal source coding system.
(Chalmers University of Technology, Sweden)
Abstract: To support the Internet-of-Things vision of enabling distributed autonomous systems operating in real time, we need a new wireless infrastructure, able to provide highly reliable and low-latency connectivity to a large number of sporadically active devices transmitting short data packets. In this talk, I will illustrate how to use recent results from finite-blocklength information theory to optimally design such a wireless infrastructure. Scenarios that are relevant for 5G and beyond will be presented. In particular, I will discuss how to support low-latency, ultra-reliable communications in both cellular and cell-free massive multiple-input multiple-output architectures.