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Modern 5G/6G radio access networks are increasingly programmable through O-RAN, yet their operational complexity has grown with disaggregation, open interfaces, and fine-grained control parameters. While RAN-side analytics and telemetry…
Open RAN (O-RAN) exposes rich control and telemetry interfaces across the Non-RT RIC, Near-RT RIC, and distributed units, but also makes it harder to operate multi-tenant, multi-objective RANs in a safe and auditable manner. In parallel,…
The Open Radio Access Network (O-RAN) architecture is reshaping telecommunications by promoting openness, flexibility, and intelligent closed-loop optimization. By decoupling hardware and software and enabling multi-vendor deployments,…
Context distillation compresses contextual information into model parameters, yet existing methods often ignore how multiple distilled latent memories should be stored, retrieved, and safely activated in non-oracle settings. We formulate…
The complexity of emerging sixth-generation (6G) wireless networks has sparked an upsurge in adopting artificial intelligence (AI) to underpin the challenges in network management and resource allocation under strict service level…
Recent advances in deep learning has lead to rapid developments in the field of image retrieval. However, the best performing architectures incur significant computational cost. Recent approaches tackle this issue using knowledge…
The concept of AI-RAN as specified by the AI-RAN alliance is geared to explore a converged 6G platform that can support management, orchestration, and deployment of both AI and RAN workloads. This concept is central to the development of a…
With growing mobile-network complexity, management and optimization have become increasingly difficult. Centralized algorithms face high control-data overhead and computational load, while distributed approaches often perform far from…
Densely deployed base stations are responsible for the majority of the energy consumed in Radio access network (RAN). While these deployments are crucial to deliver the required data rate in busy hours of the day, the network can save…
The management of networks is automated by closed loops. Concurrent closed loops aiming for individual optimization cause conflicts which, left unresolved, leads to significant degradation in performance indicators, resulting in sub-optimal…
The transition toward softwarized Radio Access Networks (RANs), driven by the Open RAN (O-RAN) paradigm, enables flexible, vendor-neutral deployments through disaggregation and virtualization of base station functions. However, this shift…
Knowledge distillation offers a transformative pathway to developing powerful, yet efficient, small language models (SLMs) suitable for resource-constrained environments. In this paper, we benchmark the performance and computational cost of…
Future networks are envisioned to connect massive artificial intelligence (AI) agents, enabling their extensive collaboration on diverse tasks. Compared to traditional entities, these agents naturally suit the semantic communication (SC),…
The open radio access network (O-RAN) architecture supports intelligent network control algorithms as one of its core capabilities. Data-driven applications incorporate such algorithms to optimize radio access network (RAN) functions via…
Extremely large-scale multiple-input multiple-output (XL-MIMO) enables the formation of narrow beams, effectively mitigating path loss in high-frequency communications. This capability makes the integration of wideband high-frequency…
Despite substantial progress in multilingual extractive Question Answering (QA), models with high and uniformly distributed performance across languages remain challenging, especially for languages with limited resources. We study…
An adaptive standardized protocol is essential for addressing inter-slice resource contention and conflict in network slicing. Traditional protocol standardization is a cumbersome task that yields hardcoded predefined protocols, resulting…
Open Radio Access Network (RAN) architectures will enable interoperability, openness, and programmatic data-driven control in next generation cellular networks. However, developing scalable and efficient data-driven algorithms that can…
The optimization of Precoding Matrix Indicators (PMIs) is crucial for enhancing the performance of 5G networks, particularly in dense deployments where inter-cell interference is a significant challenge. Some approaches have leveraged AI/ML…
This demo paper presents a dApp-based real-time spectrum sharing scenario where a 5th generation (5G) base station implementing the NR stack adapts its transmission and reception strategies based on the incumbent priority users in the…