ITEE-DP: Massive MIMO – Fundamentals and State-of-the-Art

Wednesday, June 7, 2017 to Friday, June 9, 2017

Information Technology and Electrical Engineering Doctoral Programme

Lecturer:  Assistant Professor Luca Sanguinetti, University of Pisa, Dipartimento di Ingegneria dell’Informazione, Pisa, Italy; and Large Systems and Networks Group (LANEAS), CentraleSupelec, France.

Date: June 7-9, 2017
Time & Room: See below.

Credit points (ECTS): approximately 3-4

The course is mainly targeted for doctoral students, but master students are also welcome. The course will be administered as 521318S Modern Topics in Telecommunications and Radio Engineering such that its inclusion in M.Sc. degree is also possible.

Each student needs to solve in total eight (8) problems such that there is at least one problem for each lecture. Return your solutions as PDF (a scan of hand-written solutions is fine) by e-mailing to Prof. Markku Juntti (with cc to Docent Antti Tölli) by Wednesday, August 16th latest.

Abstract

The next generation wireless networks need to accommodate around 1000x higher data volumes and 50x more devices than current networks. Since the spectral resources are scarce, particularly in bands suitable for wide-area coverage, the main improvements need to come from a more aggressive spatial reuse of the spectrum; that is, many more concurrent transmissions are required per unit area. This can achieved by the massive MIMO (massive multi-user multiple-input multiple output) technology, where the access points are equipped with hundreds of antennas and can serve tens of users on each time-frequency resource by spatial multiplexing. The large number of antennas provides a great separation of users in the spatial domain, which is a paradigm shift from conventional multi-user technologies that mainly rely on user separation in the time or frequency domains.

In recent years, massive MIMO has gone from being a mind-blowing theoretical concept to one of the most promising 5G-enabling technologies. Everybody seems to talk about massive MIMO, but do they all mean the same thing? What is the canonical definition of massive MIMO? What are the main differences from the classical multi-user MIMO technology from the nineties? What are the key characteristics of the transmission protocol? How can massive MIMO be deployed? Is pilot contamination an actual problem? Are there any widespread misunderstandings?

These lectures build upon our recent book:

E. Bjornson, J. Hoydis, L. Sanguinetti
Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency
Foundations and Trends in Signal Processing (under review)

which provide answers to all of the above questions and aims at giving a clear and balanced picture of the fundamentals of Massive MIMO, as well as an up-to-date survey of the state-of-the-art results in the main areas of spectral efficiency for spatially correlated channels, channel modeling, array deployments, energy efficiency.

Outline of the lectures

Wednesday 7 June 9-12am – TS101:
Massive MIMO: Motivation and Introduction

  • Introduction: Trends and 5G goals
  • Evolving cellular networks for higher area throughput
  • Key aspects of having massive antenna numbers
  • Achieving a scalable Massive MIMO protocol

Wednesday 7 June 1-4pm – TS101:
Spectral efficiency

  • Basic communication theoretical results
  • Methodology for performance evaluation
  • Channel estimation
  • Spectral efficiency in uplink and downlink
  • The limiting factors of Massive MIMO

Thursday 8 June 9-12am – L10
Asymptotic analysis

  • Linearly independent and orthogonal covariance matrices
  • Asymptotic Insights
  • The unlimited capacity of Massive MIMO
  • Acquiring covariance matrices

Thursday 8 June 1-4pm – L10:
Practical deployment considerations

  • Power allocation
  • Spatial resource allocation
  • Array deployments – different antenna geometries, effect of antenna element spacing
  • Massive MIMO at mmWave frequencies
  • Co-existence with heterogeneous networks

Friday 9 June 9-12am – TS101:
Energy efficiency

  • Why care about energy efficiency?
  • Transmit power – asymptotic insights
  • Mathematical definition of energy efficiency
  • Importance of accurate power consumption modeling
  • Energy Efficiency and Throughput Tradeoff
  • Network Design for Maximal Energy Efficiency

Friday 9 June 1-4am – TS101:
Hardware efficiency

  • Transceiver hardware impairments
  • Channel estimation with hardware impairments
  • Spectral efficiency with hardware impairments
  • Hardware-quality scaling law quality

Biography

Dr. L. Sanguinetti is an Assistant Professor in the Dipartimento di Ingegneria dell’Informazione of the University of Pisa. He received the Telecommunications Engineer degree (cum laude) and the Ph.D. degree in information engineering from Pisa University, Italy, in 2002 and 2005. In 2004, he was a visiting Ph.D. student at the German Aerospace Center (DLR), Oberpfaffenhofen, Germany. During the period June 2007 - 2008, he was a postdoctoral associate in the Department of Electrical Engineering at Princeton. Since July 2013, he is also with CentraleSupelec, Paris, France. He is serving as an Associate Editor for IEEE Trans. Wireless Commun. and IEEE Signal Process. Lett. He is the Lead Guest Associate Editor for IEEE JSAC - Game Theory for Networks. From June 2015 to June 2016, he was in the editorial board of IEEE JSAC - Series on Green Commun. and Networking. Dr. Sanguinetti served as Exhibit Chair of ICASSP14 and as the general co-chair of the 2016 Tyrrhenian Workshop on 5G&Beyond. His expertise and general interests span the areas of communications and signal processing with special emphasis on multiuser MIMO, game theory and random matrix theory for wireless communications. He was the co-recipient of 2 best paper awards: IEEE Wireless Commun. and Networking Conference (WCNC) 2013 and IEEE Wireless Commun. and Networking Conference (WCNC) 2014. He was also the recipient of the FP7 Marie Curie IEF 2013 “Dense deployments for green cellular networks”. Dr. Sanguinetti is a Senior IEEE Member.

More information: Markku Juntti

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Last updated: 27.6.2017