Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Wireless Communications

Alhussein Abouzeid Rensselaer Polytechnic Institute Raviraj Adve University of Toronto Dharma Agrawal University of Cincinnati Walid Ahmed Tyco M/A-COM Sonia Aissa University of Quebec, INRSEMT Huseyin Arslan University of South Florida Nallanathan Arumugam National University of Singapore Saewoong Bahk Seoul National University Claus Bauer Dolby Laboratories Brahim Bensaou Hong Kong University of Science and Technology Rick Blum Lehigh University Michael Buehrer Virginia Tech Antonio Capone Politecnico di Milano Javier Gómez Castellanos National University of Mexico Claude Castelluccia INRIA Henry Chan The Hong Kong Polytechnic University Ajit Chaturvedi Indian Institute of Technology Kanpur Jyh-Cheng Chen National Tsing Hua University Yong Huat Chew Institute for Infocomm Research Tricia Chigan Michigan Tech Dong-Ho Cho Korea Advanced Institute of Science and Tech. Jinho Choi University of New South Wales Carlos Cordeiro Philips Research USA Laurie Cuthbert Queen Mary University of London Arek Dadej University of South Australia Sajal Das University of Texas at Arlington Franco Davoli DIST University of Genoa Xiaodai Dong, University of Alberta Hassan El-sallabi Helsinki University of Technology Ozgur Ercetin Sabanci University Elza Erkip Polytechnic University Romano Fantacci University of Florence Frank Fitzek Aalborg University Mario Freire University of Beira Interior Vincent Gaudet University of Alberta Jairo Gutierrez University of Auckland Michael Hadjitheodosiou University of Maryland Zhu Han University of Maryland College Park Christian Hartmann Technische Universitat Munchen Hossam Hassanein Queen's University Soong Boon Hee Nanyang Technological University Paul Ho Simon Fraser University Antonio Iera University "Mediterranea" of Reggio Calabria Markku Juntti University of Oulu Stefan Kaiser DoCoMo Euro-Labs Nei Kato Tohoku University Dongkyun Kim Kyungpook National University Ryuji Kohno Yokohama National University Bhaskar Krishnamachari University of Southern California Giridhar Krishnamurthy Indian Institute of Technology Madras Lutz Lampe University of British Columbia Bjorn Landfeldt The University of Sydney Peter Langendoerfer IHP Microelectronics Technologies Eddie Law Ryerson University in Toronto

Wireless communications

What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.

What Will 5G Be

We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

The coded caching scheme originally proposed by Maddah-Ali and Niesen (MAN) transmits coded multicast messages from a server to users equipped with caches via a capacitated shared-link and was shown to be information theoretically optimal within a constant multiplicative factor. This work extends the MAN scheme to a class of two-hop wired-wireless networks including one server connected via fronthaul links to a layer of $H$ helper nodes (access points/base stations), which in turn communicate via a wireless access network to $K$ users, each equipped with its own cache. Two variants are considered, which differ in the modeling of the access segment. Both models should be regarded as abstractions at the “network layer” for physical scenarios such as local area networks and cellular networks, spatially distributed over a certain coverage area. The key of our approach consists of routing MAN-type multicast messages through the network and formulating the optimal routing scheme as an optimization problem that can be solved exactly or for which we give powerful heuristic algorithms. Our approach addresses at once many of the open practical problems identified as stumbling blocks for the application of coded caching in practical scenarios, namely: asynchronous streaming sessions, finite file size, scalability of the scheme to large and spatially distributed networks, user mobility and random activity (users joining and leaving the system at arbitrary times), decentralized prefetching of the cache contents, end-to-end encryption of HTTPS requests, which renders the helper nodes oblivious of the users’ demands.

Coded Caching Over Multicast Routing Networks

Urban intersections constitute an important safety-critical scenario for vehicle-to-vehicle communication. Based on measurements, this paper presents detailed investigations of the radio wave propagation processes in a typical urban intersection. We focus on one time instance of the propagation process and set up hypothesis for locations of the scattering objects. Multipath components (MPCs) are identified and an MPC tracking algorithm is applied. The number of MPCs and the lifetime of MPCs for this communication scenario are analyzed. It is concluded that the lifetime of an MPC is heavily dependent on its relative power, with typical values in the range 0.05-0.3 s corresponding to 0.5-3 m travel distance of the vehicles.

/pdf/propagation-of-multipath-components-at-an-urban-intersection-atu69ymju7.pdf

Propagation of Multipath Components at an Urban Intersection

Building upon Slepian-Wolf coding, sparse-graph codes, belief propagation, and closed-loop iterative doping, we propose new schemes for interactive data exchange between two agents who want to communicate losslessly their respective information via several rounds of communication.

/pdf/practical-schemes-for-interactive-data-exchange-yjvbu8sl1v.pdf

Practical schemes for interactive data exchange

Efficient data delivery is of significant importance, however highly challenging for vehicle-to-vehicle (V2V) communications due to high vehicle speed, time-varying vehicle density, and limited inter-vehicle contact duration. Alternatively, incorporating vehicle-to-infrastructure (V2I) communications paves a migration path for bridging long-range vehicular connectivity by introducing stationary network entities, e.g., road-side unit. In this paper, we develop a mathematical framework to address the performance of data delivery in hybrid V2V and V2I networks by considering both latency and throughput requirements. With the theoretical analysis, we formulate an optimization problem to maximize the weighted sum of the latency and the throughput for the hybrid V2V and V2I networks, and further propose a multihop routing algorithm to select the optimal route for the weighted sum maximization. Simulation results show that the proposed solution achieves significantly higher throughput and lower latency compared to the existing routing algorithms.

Multihop Routing in Hybrid Vehicle-to-Vehicle and Vehicle-to-Infrastructure Networks

We study the multi-antenna Coded Caching setting in the finite Signal-to-Noise-Ratio (SNR) region, with the purpose to utilize the extra resources from the multiple antennas to increase the rate performance of the system. Specifically, assuming an L-antenna setting with K cache-enabled users (each with normalized cache-size γ), previous works showed that at the high SNR region the performance is proportional to L + Kγ degrees-of-freedom while, if one considers the low SNR region this would be outperformed by a strategy that focuses on beamforming a (single) multicast message (of Kγ + 1 elements) to its recipients. In order to bridge these two extremes we use a recently proposed algorithm that can balance the amount of users served in order to maximize the achieved sum-rate.

Giuseppe Caire

Papers

Coded Caching Over Multicast Routing Networks

Propagation of Multipath Components at an Urban Intersection

Practical schemes for interactive data exchange

Multihop Routing in Hybrid Vehicle-to-Vehicle and Vehicle-to-Infrastructure Networks

Bridging the Gap between Multiplexing and Diversity in Finite SNR Multiple Antenna Coded Caching