Emil Björnson is an Associate Professor at Linköping University, Sweden. He has performed MIMO research for more than 10 years and has filed more than 20 related patent applications. He also conducts research on radio resource allocation, machine learning for communications, and energy-efficient communications. He has authored the textbooks “Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency” (2017) and “Optimal Resource Allocation in Coordinated Multi-Cell Systems” (2013). He is dedicated to reproducible research and has made a lot of simulation code openly available.
He received the 2019 IEEE Communications Society Fred W. Ellersick Prize, the 2019 EURASIP Early Career Award, the 2018 IEEE Marconi Prize Paper Award in Wireless Communications, the 2016 Best PhD Award from EURASIP, and the 2014 Outstanding Young Researcher Award from IEEE ComSoc EMEA. He has received best conference paper awards at WCSP 2017, IEEE ICC 2015, IEEE WCNC 2014, IEEE SAM 2014, IEEE CAMSAP 2011, and WCSP 2009.
Tutorial: Distributed Networks with Cell-Free Massive MIMO and Radio Stripes
Abstract: The fifth generation of cellular network technology is now a reality and promises higher peak rates and better service quality than previous generations. However, these gains are not achievable everywhere. The cellular architecture is characterized by a sparse deployment of high-power access points, which are surrounded by users being at different distances. Some are close and get good service, and some are far away and get bad service. Despite all the improvements that have been made from 1G to 5G, this fundamental weakness has remained.
Looking beyond the current 5G technology, it is not higher peak rates that are needed but a more uniform service quality over the coverage area. This cannot be achieved by moving to higher frequency bands or densifying cellular networks. However, a distributed network architecture building on the Cell-free Massive MIMO principle is a promising solution. In this tutorial, we will first cover the motivation and background of distributed cell-free networks. We will then describe four different ways to distribute the physical-layer processing over the network and evaluate them in terms of communication performance and fronthaul capacity requirements. Finally, we will describe how to enable large-scale deployment of cell-free networks using dynamic cooperation clusters and radio stripes.
Keynote: Communication Using Intelligent Reflective Surfaces: Myths and Realities
Abstract: Thanks to the success of Massive MIMO in 5G, many academic researchers are now looking for a new multi-antenna technology that can revolutionize beyond 5G networks. Recently, the classic concept of reconfigurable reflectarrays from the electromagnetic literature has appeared in the communication theoretic literature under a variety of different names: intelligent reflective surfaces, software-controlled metasurfaces, and reconfigurable intelligent surfaces. The main idea is to support the transmission from a source to a destination by deploying electromagnetically active surfaces that can reconfigure their reflective properties to improve the channel conditions. In principle, the reconfigurability opens a new dimension for network optimization: we can not only optimize the transmitter and receiver, but also adjust the channel propagation. However, it is easy to get excited by new technology and forget about which existing technologies can potentially provide similar gains. It is still unclear what practical gains can be achieved by intelligent reflective surfaces and whether it can provide any orders-of-magnitude improvements over legacy technology. In this keynote, we will review some of the overly optimistic or misleading claims that have been made in recent literature and provide a more balanced view of the technology.