14 citations · 48 across the 32 of their papers we have counts for
41 papers
From Reactive to Agentic Resilience: Multi-Timescale AI-RAN Orchestration Under Signaling Storms
Sotiris Chatzimiltis, Mahdi Boloursaz Mashhadi, Mohammad Shojafar +1
Next-generation open radio access network (Open RAN) and AI-RAN deployments turn the RAN into a disaggregated, compute-aware platform whose service continuity depends on many contr…
From Semantic to Token Communication: The Next Paradigm for Large-Model-Driven 6G Intelligent Connectivity
Yu Ma, Zhen Gao, Li Qiao +11
The ambitious requirements of sixth-generation (6G) networks are driving communication systems from reliable bit delivery toward meaning-aware and task-oriented connectivity. Large…
Ada-TokenCom: Rate-Adaptive Token Communications via Large-Model-Driven Token Compression and Generation
Zijun Zhang, Li Qiao, Mahdi Boloursaz Mashhadi +3
Token Communications (TokenCom) has recently emerged as a new paradigm in which tokens serve as unified units for communication and computation, enabling efficient multimodal seman…
Demo: Real-time Generative Multicasting with On-Device Intent-aware Semantic Decomposition
Xinkai Liu, Mahdi Boloursaz Mashhadi, Yi Ma +1
We present a demonstration for generative multicasting with on-device, intent-aware semantic decomposition. At the transmitter, DNN-based segmentation extracts a semantic map from…
PipeSD: An Efficient Cloud-Edge Collaborative Pipeline Inference Framework with Speculative Decoding
Yunhe Han, Yunqi Gao, Bing Hu +4
Speculative decoding can significantly accelerate LLM inference, especially given that its cloud-edge collaborative deployment offers cloud workload offloading, offline robustness,…
Video TokenCom: Textual Intent-Guided Multi-Rate Video Token Communications with UEP-Based Adaptive Source-Channel Coding
Jingxuan Men, Mahdi Boloursaz Mashhadi, Ning Wang +3
Token Communication (TokenCom) is a new paradigm, motivated by the recent success of Large AI Models (LAMs) and Multimodal Large Language Models (MLLMs), where tokens serve as unif…
Talk Like a Packet: Rethinking Network Traffic Analysis with Transformer Foundation Models
Samara Mayhoub, Chuan Heng Foh, Mahdi Boloursaz Mashhadi +2
Inspired by the success of Transformer-based models in natural language processing, this paper investigates their potential as foundation models for network traffic analysis. We pr…
Agentic AI-RAN: Enabling Intent-Driven, Explainable and Self-Evolving Open RAN Intelligence
Zhizhou He, Yang Luo, Xinkai Liu +4
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-ob…
Wireless TokenCom: RL-Based Tokenizer Agreement for Multi-User Wireless Token Communications
Farshad Zeinali, Mahdi Boloursaz Mashhadi, Rahim Tafazolli
Token Communications (TokenCom) has recently emerged as an effective new paradigm, where tokens are the unified units of multimodal communications and computations, enabling effici…
Agentic AI for 6G: A New Paradigm for Autonomous RAN Security Compliance
Sotiris Chatzimiltis, Mahdi Boloursaz Mashhadi, Mohammad Shojafar +2
Agentic AI systems are emerging as powerful tools for automating complex, multi-step tasks across various industries. One such industry is telecommunications, where the growing com…
FlowMoE: A Scalable Pipeline Scheduling Framework for Distributed Mixture-of-Experts Training
Yunqi Gao, Bing Hu, Mahdi Boloursaz Mashhadi +5
The parameter size of modern large language models (LLMs) can be scaled up via the sparsely-activated Mixture-of-Experts (MoE) technique to avoid excessive increase of the computat…
Interpretable Anomaly-Based DDoS Detection in AI-RAN with XAI and LLMs
Sotiris Chatzimiltis, Mohammad Shojafar, Mahdi Boloursaz Mashhadi +1
Next generation Radio Access Networks (RANs) introduce programmability, intelligence, and near real-time control through intelligent controllers, enabling enhanced security within…
ToDMA: Large Model-Driven Massive Token Communications for Semantic Multiple Access
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao +2
Token communications (TokenCom) is an emerging generative semantic communication paradigm, where tokens serve as compact representation units across modalities. Their contextual de…
Surviving the Storm: The Impacts of Open RAN Disaggregation on Latency and Resilience
Sotiris Chatzimiltis, Mohammad Shojafar, Mahdi Boloursaz Mashhadi +1
The development of Open Radio Access Networks (Open RAN), with their disaggregated architectures and virtualization of network functions, has brought considerable flexibility and c…
Token Communications: A Large Model-Driven Framework for Cross-modal Context-aware Semantic Communications
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao +3
In this paper, we introduce token communications (TokCom), a large model-driven framework to leverage cross-modal context information in generative semantic communications (GenSC).…
Token-Domain Multiple Access: Exploiting Semantic Orthogonality for Collision Mitigation
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao +1
Token communications is an emerging generative semantic communication concept that reduces transmission rates by using context and transformer-based token processing, with tokens s…
Single Antenna Tracking and Localization of RIS-enabled Vehicular Users
Somayeh Aghashahi, Zolfa Zeinalpour-Yazdi, Aliakbar Tadaion +2
Reconfigurable Intelligent Surfaces (RISs) are envisioned to be employed in next generation wireless networks to enhance the communication and radio localization services. In this…
Generative Semantic Communications with Foundation Models: Perception-Error Analysis and Semantic-Aware Power Allocation
Chunmei Xu, Mahdi Boloursaz Mashhadi, Yi Ma +2
Generative foundation models can revolutionize the design of semantic communication (SemCom) systems allowing high fidelity exchange of semantic information at ultra low rates. In…
Communicate Less, Synthesize the Rest: Latency-aware Intent-based Generative Semantic Multicasting with Diffusion Models
Xinkai Liu, Mahdi Boloursaz Mashhadi, Li Qiao +3
Generative diffusion models (GDMs) have recently shown great success in synthesizing multimedia signals with high perceptual quality, enabling highly efficient semantic communicati…
Generative Semantic Communication via Textual Prompts: Latency Performance Tradeoffs
Mengmeng Ren, Li Qiao, Long Yang +6
This paper develops an edge-device collaborative Generative Semantic Communications (Gen SemCom) framework leveraging pre-trained Multi-modal/Vision Language Models (M/VLMs) for ul…
Semantic-Aware Power Allocation for Generative Semantic Communications with Foundation Models
Chunmei Xu, Mahdi Boloursaz Mashhadi, Yi Ma +1
Recent advancements in diffusion models have made a significant breakthrough in generative modeling. The combination of the generative model and semantic communication (SemCom) ena…
Massive Digital Over-the-Air Computation for Communication-Efficient Federated Edge Learning
Li Qiao, Zhen Gao, Mahdi Boloursaz Mashhadi +1
Over-the-air computation (AirComp) is a promising technology converging communication and computation over wireless networks, which can be particularly effective in model training,…
Latency-Aware Generative Semantic Communications with Pre-Trained Diffusion Models
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao +3
Generative foundation AI models have recently shown great success in synthesizing natural signals with high perceptual quality using only textual prompts and conditioning signals t…
MU-Massive MIMO with Multiple RISs: SINR Maximization and Asymptotic Analysis
Somayeh Aghashahi, Zolfa Zeinalpour-Yazdi, Aliakbar Tadaion +2
In this letter, we investigate the signal-to-interference-plus-noise-ratio (SINR) maximization problem in a multi-user massive multiple-input-multiple-output (massive MIMO) system…