The massive adoption of eXtended Reality (XR) in most of our daily activities regarding education, work, health, entertainment and personal life will heavily transform our society in the following years. Those XR applications will mostly reach the final user - to both consume and create XR contents - through wireless networks, and Wi-Fi in particular, due to their flexibility, mobility support and ease of use. The success of such an XR-enabled society will depend to a great extent on the ability of the wireless networks to support their stringent performance requirements. Real-time, and interactive XR applications - which mainly consist of exchanging high quality video along with metadata - require both high throughput (hundreds of Mbps per user) and low-latency (ms, or even sub-ms), which generally are opposed performance metrics.

Current wireless networks are not yet ready to cope with a massive use of XR applications in an efficient way, and so both academia and industry are pushing to find innovative solutions. The target is to have them ready by 2030. By then, Wi-Fi will likely continue being the preferred wireless access solution in unlicensed bands, and so the most used technology to consume XR experiences. However, although current Wi-Fi technologies are extremely advanced, reaching speeds of several dozens of Gbps, they are far from being ready to efficiently offer low-latency guarantees.

To support XR needs in future Wi-Fi networks a paradigm change is required from throughput-centered to latency-aware networking. This paradigm change can be supported by allowing Wi-Fi to opportunistically use different spectrum bands in a coordinated way, enable cooperation between different Access Points, implement sub-frame resource allocation schemes, exchange control information with other layers, and support the use of Machine Learning for a seamless adaptation to diverse and rapidly evolving scenarios.

This project aims to build on the aforementioned points to offer innovative and practical solutions for next-generation Wi-Fi networks, so they can successfully offer both high-throughput and low-latency guarantees to interactive streaming applications including video contents, cloud gaming, and immersive XR applications, among others. By considering new principles such as multi Access Point cooperation and opportunistic multi-channel/band access, we will be able to design particular solutions able to satisfy the needs of XR applications in dense and dynamic wireless network deployments. Moreover, we will go beyond traditional protocol/mechanism design: motivated by the need to find/learn specific functionalities that suit each unique scenario, we will focus on the design of intelligent protocols/mechanisms by embedding Machine Learning techniques in the different Wi-Fi functionalities.

The generated results will extend our knowledge in wireless networking, Wi-Fi technologies, real-time and interactive video applications (cloud gaming, and XR), and in the design of intelligent protocols. It will also contribute to developing the required new mathematical, simulation and experimental frameworks to be able to characterize the performance gains of the upcoming latency-aware Wi-Fi networks. All in all, this project will help to build a better future society by contributing to enable the use of interactive and real-time XR applications and services.

Journal Publications

Submitted / Under Review

Miguel Casasnovas, Costas Michaelides, Marc Carrascosa-Zamacois, Boris Bellalta: Experimental Evaluation of Interactive Edge/Cloud Virtual Reality Gaming over Wi-Fi using Unity Render Streaming. CoRR abs/2402.00540 (2024) [https://arxiv.org/pdf/2402.00540]

Accepted but not yet published

Giordano, Lorenzo Galati, Giovanni Geraci, Marc Carrascosa, and Boris Bellalta. "What will Wi-Fi 8 be? A primer on IEEE 802.11 bn ultra high reliability." arXiv preprint arXiv:2303.10442 (2023). [Accepted in IEEE Communications Magazine]  [https://arxiv.org/pdf/2303.10442]

2024

Marc Carrascosa-Zamacois, Giovanni Geraci, Edward W. Knightly, Boris Bellalta: Wi-Fi Multi-Link Operation: An Experimental Study of Latency and Throughput. IEEE/ACM Trans. Netw. 32(1): 308-322 (2024) [https://arxiv.org/pdf/2305.02052]

2023

C Michaelides, Boris Bellalta; "Buffer Resets: A Packet-Discarding Policy for Timely Physiological Data Collection in Virtual Reality Gaming Systems" IEEE Sensors Letters 7 (12), 1-4 [TechArxiv link]

Boris Bellalta, Marc Carrascosa, Lorenzo Galati Giordano, Giovanni Geraci: Delay Analysis of IEEE 802.11be Multi-Link Operation Under Finite Load. IEEE Wireless Commun. Lett. 12(4): 595-599 (2023)  [https://arxiv.org/pdf/2212.12420]

Conference Publications

Submitted / Under Review

C. Michaelides, Boris Bellalta; Responsive and Timely Virtual Reality Gaming: Which Frame Rate Should One Choose? IEEE Conference on Games, 2024. 

Boris Bellalta, Katarzyna Kosek-Szott, Szymon Szott, Francesc Wilhelmi; "Towards an AI/ML-defined Radio for Wi-Fi: Overview, Challenges, and Roadmap" IEEE Future Networks Technical Community (FNTC)'s "International Network Generations Roadmap" (INGR), AI/ML Chapter, 2024 Edition. [Invited Paper] 

2023

C Michaelides, M Casasnovas, D Marchitelli, Boris Bellalta; "Is Wi-Fi 6 Ready for Virtual Reality Mayhem? A Case Study Using One AP and Three HMDs" IEEE Future Networks 2023. [Best Paper Award] [TechArxiv Link]

Rashid Ali, Boris Bellalta; “A Federated Reinforcement Learning Framework for Link Activation in Multi-Link Wi-Fi Networks”. IEEE BlackSeaCom 2023: 360-365 [https://arxiv.org/pdf/2304.14720]

Francesc Wilhelmi, Lorenzo Galati Giordano, Giovanni Geraci, Boris Bellalta, Gianluca Fontanesi, David Nunez; “Throughput Analysis of IEEE 802.11bn Coordinated Spatial Reuse”. IEEE CSCN 2023: 401-407 [https://arxiv.org/pdf/2309.09169]

David Nunez, Malcolm Smith, Boris Bellalta; “Multi-AP Coordinated Spatial Reuse for Wi-Fi 8: Group Creation and Scheduling”. MedComNet 2023: 203-208 [https://arxiv.org/pdf/2305.04846]

Marc Carrascosa-Zamacois, Giovanni Geraci, Lorenzo Galati Giordano, Anders Jonsson, Boris Bellalta: “Understanding Multi-link Operation in Wi-Fi 7: Performance, Anomalies, and Solutions”. PIMRC 2023: 1-6 [https://arxiv.org/pdf/2210.07695]

Marc Carrascosa-Zamacois, Lorenzo Galati Giordano, Anders Jonsson, Giovanni Geraci, Boris Bellalta: “Performance and Coexistence Evaluation of IEEE 802.11be Multi-link Operation”. WCNC 2023: 1-6 [Joint work with Nokia Bell-Labs, Collaboration with AI/ML group from UPF] [Link to IEEE Xplore]
 

Rooms and wgpuEngine

Rooms and wgpuEngine are open-source under the MIT license and is being actively maintained at GitHub:

• https://github.com/upf-gti/rooms

• https://github.com/upf-gti/wgpuEngine

• https://webglstudio.org/projects/rooms/

Tutorials

IEEE PIMRC 2023: “On the Way to Wi-Fi 8: From Extremely High Throughput to Ultra High Reliability”. With G. Geraci, L. Galati. and F. Wilhelmi. Sept. 2023.

ACM Mobicom 2023: “Machine Learning and Wi-Fi: Confluences, Ongoing Activities, and Ways Forward”. With S. Szott, K. Kosek-Szott, and F. Wilhelmi. Madrid. October 2023.

IEEE ICC 2023: “On the Way to Wi-Fi 8: From Extremely High Throughput to Ultra High Reliability”. With G. Geraci and L. Galati. June 2023.

IEEE WCNC 2023: “Towards Wi-Fi 8: From Extremely High Throughput to Ultra High Reliability”. With G. Geraci and L. Galati. March 2023.

IEEE CCNC 2023: “IEEE 802.11be and Beyond: All You Need to Know about Next-generation Wi-Fi”. With G. Geraci and L. Galati. Jan. 2023.

IEEE Globecom 2022: “IEEE 802.11be and Beyond: All You Need to Know about Next-generation Wi-Fi”. With G. Geraci and L. Galati. Sept. 2022.

IEEE 802.11 standardization

Co-authors of the "IEEE 802.11 AIML TIG Technical Report." IEEE 802.11-22/0987r925, 2023. https://mentor.ieee.org/802.11/dcn/22/11-22-0987-02-aiml-aiml-tig-technical-report-draft.doc