This work presents Windex, a novel light weight whittle index network-driven realtime scheduler for scalable service guarantees in NextG cellular networks. Windex addresses the resource allocation challenge in NextG cellular radio access networks (RAN), where resources must be shared among diverse user applications, each requiring guarantees on throughput and service regularity, taking into account service guarantees, channel quality, and system load. Implemented in a real time intelligent controller (RIC), and evaluating across standardized 3GPP service classes, we demonstrate the least service violations compared to state-of-the-art systems using over-the-air channel traces on a 5G testbed.

This work presents SPARC (Spatio-Temporal Adaptive Resource Control), a novel approach for multi-site spectrum management in NextG cellular networks. SPARC addresses the challenge of limited licensed spectrum in dynamic environments. We leverage the O-RAN architecture to develop a multi-timescale RAN Intelligent Controller (RIC) framework, featuring an xApp for near-real-time interference detection and localization, and a μApp for real-time intelligent resource allocation. By utilizing base stations as spectrum sensors, SPARC enables efficient and fine-grained dynamic resource allocation across multiple sites, enhancing signal-to-noise ratio (SNR) by up to 7dB, spectral efficiency by up to 15%, and overall system throughput by up to 20%.

The 5G network promised transformative services across various industries, yet its integration has mostly been limited to existing 4G services like IMS-based multimedia and IoT. This paper identifies two key reasons for this underutilization: first, the stringent, multi-dimensional requirements of next-generation verticals like AR/VR, mobile gaming, and robotics, and the limitations of traditional Quality of Service (QoS) approaches in meeting these needs. We argue for a shift towards Quality of Experience (QoE), which better captures user perception and instantaneous application state. To meet stringent QoE demands and optimize network utilization, we emphasize the importance of application state and context awareness within the network. As a solution, we propose AppNet, a novel framework that integrates application awareness into the networking stack via RAN Intelligent Controllers (RICs) of the Open-RAN platform, enabling dynamic QoS adjustments based on application context. This paper highlights 5G private networks as an ideal testing ground, focusing on multi-user scenarios to deliver optimal real-time interactive services at scale.

NextG cellular networks must support diverse applications, such as interactive media streaming or robot control that have strict requirements on throughput, latency and reliability. These requirements must be met via optimizing wireless resources by utilizing application layer information, such as media streaming stall counts or robot pose estimates, along with network information, such as channel qualities and backlogs.