Signal Design for 6G Ultra-Reliable Wireless Communications

Room: ENG460, Bldg: ENG building , 245 Church Street, Toronto, Ontario, Canada

Next sixth generation (6G) wireless systems are expected to support ultra-reliable communications (URC) for data generated from various devices and applications. To achieve URC, various techniques can be used, such as multiple-input multiple-output (MIMO), intelligent reflective surfaces (IRS), forward error correction coding, and automatic repeat request (ARQ). The design of

Signal Design for 6G Ultra-Reliable Wireless Communications

Room: ENG 460, Bldg: ENG building , 245 Church Street, Toronto Metropolitan University, Toronto, Ontario, Canada

Next sixth generation (6G) wireless systems are expected to support ultra-reliable communications (URC) for data generated from various devices and applications. To achieve URC, various techniques can be used, such as multiple-input multiple-output (MIMO), intelligent reflective surfaces (IRS), forward error correction coding, and automatic repeat request (ARQ). The design of

Sleep, The Reflection of Health

Virtual: https://events.vtools.ieee.org/m/423915

Join the IEEE Toronto Instrumentation & Measurement – Robotics & Automation Joint Chapter for a talk on the Sleep, The Reflection of Health, presented by Dr. Nasim Montazeri from Queen's University. Wednesday, July 24, 2024 @ 4:30 – 5:30 PM Abstract: While sufficient sleep is one of the health pillars,

Walking with Robots

Virtual: https://events.vtools.ieee.org/m/425309

[] Join the IEEE Toronto Instrumentation & Measurement – Robotics & Automation Joint Chapter for a talk on the Walking with Robots, presented by Dr. Amy R. Wu from Queen's University. Wednesday, July 31, 2024 @ 5:00 – 6:00 PM Abstract: A world embedded with robots seems inevitable. One challenge,

Federated Learning in Resource Limited Wireless Networks

Room: 460, Bldg: ENG, 245 Church Street, Toronto, Ontario, Canada, M5B 1Z4

Federated learning (FL) is an efficient and privacy-preserving distributed learning paradigm that enables massive edge devices to train machine learning models collaboratively. Although various communication schemes and algorithm designs have been proposed to expedite the FL process in resource-limited wireless networks, the unreliable nature of wireless channels, device heterogeneity, and

Supporting Patient-Clinician Collaboration on Shared Surfaces

Virtual: https://events.vtools.ieee.org/m/423931

[] Join the IEEE Toronto Instrumentation & Measurement – Robotics & Automation Joint Chapter for a talk on the Supporting Patient-Clinician Collaboration on Shared Surfaces, presented by Dr. Fateme Rajabiyazdi from Carleton University. Tuesday, August 20, 2024 @ 4:00 – 5:00 PM Abstract: Patient health data needs to be discussed

Materials As Machines

Virtual: https://events.vtools.ieee.org/m/424150

[]Join the IEEE Toronto Instrumentation & Measurement – Robotics & Automation Joint Chapter for a talk on the Materials As Machines, presented by Dr. Irina Garces from Carleton University. Wednesday, August 21, 2024 @ 4:30 – 5:30 PM Abstract: The Materials as Machines Lab specializes in developing systems and devices