Regular Seminars

Sparse NOMA: A Closed-Form Characterization

Speaker: Shlomo Shamai (Shitz)

Time and Place: Thursday September 27, 2018, 10h30, Room VI.144 (Salle du Conseil), Bâtiment Gustave Eiffel (Univers Vivant, 1st floor), CentraleSupélec, Campus of Gif-sur-Yvette, France

Abstract: Understanding fundamental limits of the various technologies suggested for future 5G and beyond cellular systems is crucial for developing efficient state-of-the-art designs. A leading technology of major interest is non-orthogonal multiple-access (NOMA). In particular, sparse, or low-density code-domain (LDCD) NOMA is a prominent sub-category, which conceptually relies on multiplexing low-density signatures (LDS). The main attractiveness of this class of NOMA schemes is in its inherent receiver complexity reduction, achieved by utilizing message-passing algorithms, and different variants of sparse NOMA have recently gained much attention in 5G standardisation. Relying on recent results from the spectral theory of large random graphs, we derive an explicit closed-form analytical expression for the optimum spectral efficiency in the large-system limit of regular sparse NOMA. The latter setting corresponds to the case where only a fixed and finite number of orthogonal resources is allocated to any designated user, and vice versa. The basic Verdu-Shamai (1999) formula for (dense) randomly-spread code-division multiple-access (RS-CDMA) turns out to coincide with the limit of the derived expression, when the number of orthogonal resources occupied by each user grows large. Furthermore, regular sparse NOMA is shown to be spectrally more efficient than RS-CDMA across the entire system load range. It may therefore serve as an efficient means for reducing the throughput gap to orthogonal transmission in the underloaded regime, and to the ultimate Cover-Wyner multiple-access channel bound in overloaded systems. The results analytically reinforce preliminary conclusions for the regular sparse NOMA setting, which mostly relied on the non-rigorous cavity method of statistical physics and numerical integration. The spectral efficiency is also derived in closed form for the sub-optimal linear minimum-mean-square-error (LMMSE) receiver, which again extends the corresponding Verdu-Shamai (1999) formula to regular sparse NOMA. An extreme-SNR analysis is also provided, leading to useful insights.

The talk is based on a joint work with Dr. Benjamin Zaidel (Bar-Ilan University) and Dr. Ori Shental (Nokia Bell Labs).

Cloud Radio Access Networks, Distributed Information Bottleneck, and More: A Unified Information Theoretic View

Speaker: Prof. Shlomo Shamai (Shitz)

Time and Place: 28 September 2018, 11h00, Room F900, Télécom ParisTech, 46 rue Barrault, 75013 Paris

Abstract:

We consider transmission over a cloud radio access network (CRAN) focusing on the framework of oblivious processing at the relay nodes (radio units), i.e., the relays are not cognizant of the users' codebooks. This approach is motivated by future wireless communications (5G and beyond) and the theoretical results connect to a variety of different information theoretic models and problems. First it is shown that relaying a-la Cover-El Gamal, i.e., compress-and-forward with joint decompression and decoding, which reflects 'noisy network coding,' is optimal. The penalty of obliviousness is also demonstrated to be at most a constant gap, when compared to cut-set bounds. Naturally, due to the oblivious (nomadic) constraint the CRAN problem intimately connects to Chief Executive Officer (CEO) source(s) coding under a logarithmic loss distortion measure. Furthermore, we identify and elaborate on some interesting connections with the distributed information bottleneck model for which wecharacterize optimal tradeoffs between rates (i.e., complexity) and information (i.e., accuracy) in the discrete and vector Gaussian frameworks. Further connections to 'information combining' and 'common reconstruction' are also pointed out. In the concluding outlook, some interesting problems are mentioned such as the characterization of the optimal input distributions under users' power limitations and rate-constrained compression at the relay nodes.

Joint work with: I.E. Aguerri (Paris Research Center, Huawei France) A. Zaidi (Universite Paris-Est, Paris) and G. Caire (USC-LA and TUB, Berlin) The research is supported by the European Union's Horizon 2020 Research And Innovation Programme: no. 694630.

Autoencoders and compression with DNN

Speaker: G. Valenzise and L. Wang

Time and Place: 8 March 2018, 14h30, B555, CentraleSupélec, Campus of Gif-sur-Yvette, France

Recurrent neural networks and long-short term memory (LSTM) units

Speaker: Bogdan Cirstea

Time and Place: 22 March 2018, 14h30, B555, CentraleSupélec, Campus of Gif-sur-Yvette, France

Layered Secrecy on Broadcast Networks

Speaker: Shlomo Shamai (Shitz)

Time and Place: Wednesday 11 Oct 2017, 11h00, Amphi Rubis, Telecom ParisTech, 46 rue Barrault, 75013 Paris

Abstract: We review the setting of layered secrecy, addressing the degraded broadcast channel. The basic framework facilitates for a legitimate receiver who enjoys a better channel quality (channel state information, unavailable to the transmitter) to decode more secret messages, while the eavesdroppers with worse channel quality are kept ignorant of more messages. While this layered based secrecy coding approach (variable-to-fixed rate secrecy coding) is evaluated for degraded channels, the strategy is relevant to general settings, though not necessarily optimal. Examples of the approach for fading channels, where the legitimate and eavesdropping channels are corrupted by multiplicative random fading gains are presented.

We use a similar paradigm of a layered approach to address secret sharing problem, where groups of users are able to determine certain secrets by sharing their channel outputs, and other groups of users are kept ignorant of certain secrets even if they share their outputs.

We also present secret capacity region results for secrecy outside of a bounded range, focusing on simple models, for which it is shown that the secret capacity requires combinations of superposition coding, binning, and embedded codes, as well as sharing designs (as rate splitting). Specific capacity results are demonstrated for the K-user degraded broadcast channel with a two level secrecy range. For this case an induction approach for the Fourier-Motzkin elimination is developed yielding the closed form capacity results.

In the concluding outlook we discuss secret communication designs for different models.

The talk is based on joint studies with S. Zou, Y. Liang, L. Lai and H.V. Poor.

On the Degrees of Freedom of MISO Broadcast Channels with Partial CSIT

Speaker: Dr. Hamdi Joudeh

Time and Place: Sep 20th 2017 at 14h00, The Council room (B.4.40), L2S, CentraleSupelec

Abstract: The multiple-input-single-output (MISO) broadcast channel (BC), in which a multi-antenna transmitter communicates with multiple uncoordinated single-antenna receivers, is an essential building block of modern wireless networks. In this channel, multiuser interference management is naturally carried out at the transmitter. This in turn requires highly accurate and up-to-date channel state information at the transmitter (CSIT), which is not always available in practice. While it is understood that the MISO BC is sensitive to CSIT inaccuracies, the capacity under such conditions remains largely a mystery. Hence, it is natural to resort to coarse approximations, e.g. the Degrees of Freedom (DoF), when studying such challenging problems. In this talk, I will review some recent (and not so recent) results in DoF studies of the MISO BC when only partial instantaneous CSIT is available. I will be focusing on tools used to derive achievability and converse result. I will also present some new DoF results for parallel MISO BCs (e.g. OFDM) with partial CSIT. Implications, insights and open problems are also discussed.

Bio: Hamdi Joudeh is a postdoctoral research associate in the Communication and Signal Processing Group, Department of Electrical and Electronic Engineering at Imperial College London. He received his PhD in Electrical Engineering and MSc in Communications and Signal Processing from Imperial College London, UK, in 2016 and 2011 respectively. His research interests are in the areas of wireless communications and multiuser information theory. He is currently serving as an associate editor for the EURASIP Journal on Wireless Communications and Networking.

Economics of Wi-Fi Networks

Speaker: Prof. Jianwei Huang

Time and Place: May 19th 2017 at 10h30, Univ. Paris-Sud, 445, room patio exterieur

Abstract: Stable and high-quality Wi-Fi networks play an important role in supporting fast-growing wireless data demands. According to the forecast by the Cisco Visual Networking Index, global Wi-Fi networks will carry 54% of the smartphones traffic and 70% of the tablets traffic by 2019. Comparing with cellular networks, Wi-Fi network equipments are often low-cost, easy to install and manage, and can offer high transmission rates. However, the operation of large-scale Wi-Fi networks often faces several challenges, such as the limited coverage of each Wi-Fi access point and the customers' unwillingness to pay for public Wi-Fi access. In this talk, we will present several economic mechanisms to address these challenges. The first mechanism aims at achieving a large network coverage by incentivizing the sharing of private Wi-Fi hotspots. The second mechanism increases the Wi-Fi operator's revenue through an advertisement-sponsored differential Wi-Fi pricing scheme. Both mechanisms will encourage more investment and better utilization of the Wi-Fi networks.

Bio: Jianwei Huang is an IEEE Fellow, a Distinguished Lecturer of IEEE Communications Society, and a Thomson Reuters Highly Cited Researcher in Computer Science. He is an Associate Professor and Director of the Network Communications and Economics Lab (ncel.ie.cuhk.edu.hk), in the Department of Information Engineering at the Chinese University of Hong Kong. He received Ph.D. from Northwestern University in 2005, and worked as a Postdoc Research Associate at Princeton University during 2005-2007. His main research interests are in the area of network economics and games, with applications in wireless communications, networking, and smart grid. Dr. Huang is the co-recipient of 8 Best Paper Awards, including IEEE Marconi Prize Paper Award in Wireless Communications in 2011, and Best (Student) Paper Awards from IEEE WiOpt 2015/2014/2013, IEEE SmartGridComm 2012, WiCON 2011, IEEE GLOBECOM 2010, and APCC 2009. He has co-authored six books, "Wireless Network Pricing," "Economics of Database-Assisted Spectrum Sharing," "Monotonic Optimization in Communication and Networking Systems," "Cognitive Mobile Virtual Network Operator Games," "Social Cognitive Radio Networks," and "Cooperative Traffic Off-Loading in Heterogeneous Cellular Networks." He received the CUHK Young Researcher Award in 2014 and IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award in 2009.

Dr. Huang has served as an Editor of IEEE/ACM Transactions on Networking, Editor of IEEE Transactions on Cognitive Communications and Networking, Editor of IEEE Transactions on Wireless Communications, Editor of IEEE Journal on Selected Areas in Communications - Cognitive Radio Series, Editor and Associate Editor-in-Chief of IEEE Communications Society Technology News. He has served as a Guest Editor of IEEE Journal on Selected Areas in Communications, IEEE Transactions on Smart Grid, IEEE Network, and IEEE Communications Magazine. He also serves as a Co-Editor-in-Chief of Wiley Information and Communication Technology Series, an Area Editor of Springer Encyclopedia of Wireless Networks, and a Section Editor for Springer Handbook of Cognitive Radio. Dr. Huang has served as Chair of IEEE Communications Society Cognitive Network Technical Committee, Chair of IEEE Communications Society Multimedia Communications Technical Committee, and a Steering Committee Member of IEEE Transactions on Multimedia. He has served as the General/TPC/Symposium Co-Chair of IEEE WiOpt 2018/2017/2012, IEEE SDP 2017/2016/2015, IEEE ICCC 2015/2012, NetGCoop 2014, IEEE SmartGridComm 2014, IEEE GLOBECOM 2017/2013/2010, IWCMC 2010, and GameNets 2009. He is the recipient of IEEE ComSoc Multimedia Communications Technical Committee Distinguished Service Award in 2015 and IEEE GLOBECOM Outstanding Service Award in 2010.

Coded Caching in Wireless Networks

Speaker: Prof. Meixia Tao

Time and Place: May 19th 2017 at 9h30, the Counsil room at L2S, CentraleSupélec

Abstract: The global mobile data traffic has been shifting from voice and messages to rich content distributions, such as video streaming and application downloads. These contents are typically produced ahead of transmission and can be requested by multiple users though at possibly different times. By prefetching popular contents during off-peak times at the edge of wireless networks, such as small base stations, helper nodes, and user devices, wireless caching can alleviate peak-time network congestion and reduce user access latency. A fundamental question is what and how much gain can be leveraged by caching. In this talk, we shall investigate the gain of caching in two types of wireless networks. One is a general wireless interference network with arbitrary number of transmitters and arbitrary number of receives and with caches equipped at all the nodes. An information-theoretic study in terms of the storage-latency tradeoff will be presented. The other is a large-scale small-cell network where each small base station is equipped with a cache. We apply stochastic geometry to model, analyze, and optimize coded caching with performances characterized by average fractional offloaded traffic and average ergodic rate. Our study reveals several design insights of caching in practical wireless networks.

Bio: Meixia Tao received the B.S. degree from Fudan University, Shanghai, China, in 1999, and the Ph.D. degree from Hong Kong University of Science and Technology in 2003. She is currently a Professor with the Department of Electronic Engineering, Shanghai Jiao Tong University, China. Prior to that, she was a Member of Professional Staff at Hong Kong Applied Science and Technology Research Institute during 2003-2004, and a Teaching Fellow then an Assistant Professor at the Department of Electrical and Computer Engineering, National University of Singapore from 2004 to 2007. Her current research interests include content-centric wireless networks, wireless caching and multicasting, resource allocation, and interference coordination.

Dr. Tao is currently serving as a member of the Executive Editorial Committee of the IEEE Transactions on Wireless Communications and an Editor for the IEEE Transactions on Communications. Dr. Tao is the recipient of the IEEE Heinrich Hertz Award for Best Communications Letters in 2013 and the IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award in 2009. She also receives the best paper awards from IEEE/CIC ICCC 2015 and IEEE WCSP 2012.