Videos from San Diego Wireless Summit (SDWS) 2024

San Diego Wireless Summit (SDWS) took place end of May and was hosted by Qualcomm and Center for Wireless Communications(CWC) at UC San Diego. This year’s summit theme was "Wireless in the Era of AI". The speakers discussed challenges, innovations and opportunities arising from the integration of AI and compute capabilities into wireless communication technologies including the emerging areas of RF Sensing, Digital Twins, 3D networks and AI-aided circuit design. They also explored how Wireless and AI convergence will power existing and new applications across the wireless industry and various verticals including automotive, immersive reality, IoT, smart cities and e-health.

The agenda is available here. The slides haven't been shared publicly but the video playlist is embedded below:

There is a good write-up from the event available here. Quoting some points from the article: 

  • The message from the panelists was that while it’s not too early to think about 6G, there are many innovations that will occur in the intervening years before the first commercial rollouts of 6G connectivity in 2030. As Rob Soni, Vice President of Radio Access Network (RAN) Technology at AT&T put it, innovation doesn’t happen on 10-year cycles, so AT&T uses the phrase “NextG” to incorporate all of the improvements and changes that will happen before 6G hits the networks. With three times more devices predicted to be in the average household by 2030 and four times more data on the networks in the next five years, AI poses both opportunities and challenges to deal with this continued growth of network connectivity needs.
  • In what sectors will these IoT devices proliferate? The automotive sphere is one major area, where increasing automation relies on these sensors and software. Misha Dohler, Vice President at Ericsson, said he believes there will also be significant IoT growth in “droids and drones,” meaning delivery and passenger drones, as well as robots. 
  • Among the challenges facing next-generation wireless communications are technical issues—how to increase the sustainability of networks and enable data sharing between operators to take advantage of AI's promise—as well as non-technical issues, from declining populations in much of the world to business model challenges and workforce development needs.
  • “One of the challenges is that we see a shift of interest from students into AI-driven fields,” said Heath. “I think that’s definitely going to be a concern for my industry colleagues in communications. UC San Diego has strength in teaching the fundamentals derived from mathematical models: communications theory and information theory. Model-based thinking is incredibly important for building intuition and making design decisions. We won't leave every decision about how to design and build a communication system up to a machine that uses data-driven models. And what I see is that aside from a few isolated schools like UC San Diego, you're going to see vastly fewer engineers trained that have that thinking. I would be concerned about the prospects of hiring engineers with only a background in machine learning, without knowledge of communication fundamentals.”
  • Training students to have technical competencies in artificial intelligence is important, but not at the expense of communication fundamentals, said Thomas Cheng, principal researcher at Ericsson. He said he’s found that it’s easier to train someone with a good wireless background on AI skills, but the opposite is very difficult.
  • One challenge both created by and potentially solved by AI is the very large and growing rate of video traffic on the networks- for example, Soni from AT&T said video accounts for 60 -70% of their network traffic. Much of this is thanks to social media and streaming platforms pushing up to 10 video streams to a single device simultaneously, allowing users to advance or toggle between streams. While AI algorithms are partly to blame for generating these streams of content, there is also an opportunity for AI tools to be used to reduce the load of this video traffic.
  • “We actually developed one of the lowest power injectable biosensors ever reported,” said Drew Hall, professor of electrical and computer engineering at UC San Diego. “It uses less than a microwatt of power. The implanted sensor is injected under the skin where it wirelessly receives power and wirelessly transmits data back to a wearable device. There’s a lot of opportunities coming up in this space that haven’t been tapped on the healthcare side of sensors that will start to get figured out due to a clear regulatory pathway.”
  • Lowering the power consumption for wearable devices will enable more of these rings, earbuds, patches, and watches to provide continuous data streams, providing a more holistic picture of patient health. Alex Gao, Chief Strategy Officer for Health Unity, said this continuous data could be used to predict COPD exacerbation, congestive heart failure exacerbation, and even predict asthma attacks or seizures before they happen. He noted that combining this constant flow of data with generative AI tools capable of sifting through the information to make accurate predictions will enable much more personalized treatments for patients. The key from an AI perspective is to reduce hallucination, and ensure clinical efficacy is high. 
  • Digital twins are used in a variety of industries, from civil engineering to computer science, to improve the performance of the physical version. In the context of wireless networks, John Macias, an associate fellow in Systems Architecture at Verizon, said they’re very useful when planning to roll out new features or assets. Verizon will choreograph sending out network parameter updates using a digital twin to see in granular detail how it will impact the network. This information will be used to most effectively implement the roll out in a much more confident manner.  

Feel free to add your thoughts or comments below.

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