Next generation (NextG) wireless networks will likely operate in an environment involving extensive sharing of underlying infrastructure and spectrum. In addition, many NextG services may be provided by over-the-top (OTT) providers who utilize multiple networks of shared spectrum and infrastructure to provide services to end users. These trends raise new challenges in addressing how resources are effectively share  within a network and how OTT service providers can effectively manage resources across different shared networks. These challenges are particularly acute when attempting to offer services that have stringent Quality of Service (QoS) requirements, e.g., in terms of latency and reliability, and so require a high level of robustness. This project lays out a research plan to address these questions. Specifically, we consider the following two inter-related questions:

• How can NextG architectures facilitate the integration of shared spectrum and infrastructure with OTT service providers to enable the provisioning of resilient services?

• What network control algorithms can an OTT service provider use to enable it to learn characteristics of the underlying shared networks and make adaptive decisions about how traffic is routed?

These questions are motivated by two major trends in wireless networks which we believe will only accelerate in NextG systems: (i) Sharing spectrum through infrastructure sharing, and (ii) Separation of infrastructure and services.

Participants:

Randall Berry (PI)

Eytan Modiano (Co-PI)

Fu, Xinzhe (Graduate Student)  

Mu, Kangle (Graduate Student)  

Xie, Zongyun (Graduate Student)  

Brett, Leo (Undergraduate Student)

Publications:

Xinzhe Fu, Eytan Modiano, “A Learning Approach to Minimum Delay Routing in Stochastic Queueing Networks,” IEEE Infocom, New York, May 2023.

Z. Xie and R. Berry "Market Models of Spectrum Attacks with Shared Spectrum," WiOpt 2023.