October 2023 PPCS Meeting - Introduction to Reconfigurable Intelligent Surfaces - with Anders M. Buvarp


In addition to machine learning (ML) algorithms, reconfigurable intelligent surfaces (RIS) are considered the key candidates for 6th generation mobile communication systems.

Both technologies introduce a paradigm shift from traditional and contemporary wireless communication methods.

Typically, the wireless channel is considered passive and not modifiable by the network operator; hence, the transmitter and receiver are optimized to overcome fixed impairments of the channel model.

However, with the introduction of RIS, the channel becomes intelligent and controllable to a certain degree.

For example, a mmWave communications system would suffer severely from absorption in the line-of-sight propagation path. Using a RIS for reflecting or directing the electromagnetic wave, the communications link can be properly restored.

Similarly, ML could be used to learn the most effective configuration for particular channel impairments. Remote sensing applications are another area where RIS can assist in enhancing performance.

A RIS is a two-dimensional surface of discrete, individually tunable but passive elements (unit cells), typically consisting of varactors, PIN diodes, or MEMS. Reconfigurable metamaterials and meta-surfaces are another approach to implementing RIS.

By carefully designing and optimizing the tuning of the elements, various electromagnetic (EM) wave transformation objectives can be met.

Some examples of achievable EM functions are polarization, reflection, refraction, focusing, collimation, modulation, absorption, or a combination of these. Furthermore, a RIS can be considered a new type of network node employing structures with various considerations such as form factor, design, and integration.

The RIS has low implementation costs and energy consumption; hence, combining RIS with ML is creating enormous innovation opportunities that will progressively impact the evolution of wireless system architecture, access technologies, and networking protocols.

  Date and Time




  • Date: 12 Oct 2023
  • Time: 06:30 PM to 08:00 PM
  • All times are (UTC-06:00) Mountain Time (US & Canada)
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  • Starts 21 September 2023 08:23 PM
  • Ends 12 October 2023 06:00 AM
  • All times are (UTC-06:00) Mountain Time (US & Canada)
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Anders Buvarp Anders Buvarp


Anders M. Buvarp Bio

Anders is a researcher at the Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute, and State University in Blacksburg, Virginia. He is researching novel wireless communication concepts such as reconfigurable intelligent surfaces as well as robust and blind channel estimation. From 2020 to 2022, he worked for the National Security Institute at Virginia Tech, researching reconfigurable intelligent surfaces, specific radar emitter detection, and anomaly detection in electric intelligence systems. He holds a professional engineering degree (equivalent to a Master of Science) from Lulea University of Technology, Sweden, specializing in control and communications theory. His master’s thesis was supervised by faculty at Nanyang Technological University, Singapore. In addition to his engineering degree, he holds a mutually exclusive bachelor’s degree in business administration and economics. After graduating with dual degrees in 1992 and 1993, he worked in various senior engineering positions in the semiconductor industry in Singapore, California, and Canada. He also has a successful track record of consulting for national defense contractors and other high-tech corporations. Concurrent with his work as an engineer, he assisted Professor Sven-Erik Widmalm at the University of Michigan, Ann Arbor, with signal processing algorithms, resulting in two published journal papers on oral rehabilitation.