Agentic UE-CoMIMO is introduced, in which device micro-agents, a smartphone or CPE hub agent, and edge/network agents coordinate device participation, relay modes, traffic splitting and duplication, compute placement, semantic-token exchange, and topology reconfiguration.
Abstract
End-user-centric collaborative MIMO (UE-CoMIMO) lets nearby devices form a virtual multi-antenna terminal to overcome the antenna limitations of individual user equipment. Extending such cooperation to communication, sensing, computing, and task-relevant information exchange requires a control layer that can interpret user intent, select cooperation mechanisms, and replan as conditions change. This article introduces Agentic UE-CoMIMO, in which device micro-agents, a smartphone or CPE hub agent, and edge/network agents coordinate device participation, relay modes, traffic splitting and duplication, compute placement, semantic-token exchange, and topology reconfiguration. Two system-level scenario studies on creator-centric live streaming and wearable-collaborative blind-spot sensing compare the proposed controller with capability-matched adaptive baselines. The results show that, by anticipating changes and preparing cooperation and fallback actions in advance, agentic control sustains high-quality streaming for longer and maintains blind-spot warnings through device outages. We also discuss the associated standardization, interoperability, trust, and validation challenges.
A versatile DS2D system that supports cooperative task offloading and non-cooperative access monitoring, and Transformer-based models to enable blind signal detection and automatic modulation classification (AMC) are proposed.
Sai Huang, Wanli Ni, Ke Lv et al.· IEEE Vehicular Technology Ma...· 0 citations
DEBKA is developed, a training-free optimizer that assigns different search roles to two complementary mechanisms: a BKA-inspired Cauchy-Gaussian attack for local refinement and adaptive DE/current-to-pbest migration for population-difference exploration, and results support the contribution of the coupled search and c...
Wen-Jian Zhang, Ping Li· Discover Internet of Things· 0 citations
The evaluation results show that the proposed system improves channel capacity under dynamic station combinations, avoids unnecessary re-optimization under transient blockages, and triggers re-optimization after sustained environmental changes such as continuous blockage and device relocation.
This paper places the terrestrial-satellite UAV handover decision inside the near-real-time RIC as an xApp, using a deep reinforcement learning (DRL) framework that combines a Deep Q-Network (DQN) with Prioritized Experience Replay (PER) and a reward shaped to weigh the long-term cost of switching against the reliabili...
Anirudh Warrier, Saba Al-Rubaye· IEEE Access· 0 citations
This paper proposes a novel user-centric (UC) cell-free massive MIMO (CF-mMIMO) architecture empowered by six-dimensional movable antennas (6DMA) and flexible intelligent metasurfaces (FIM), integrated with a two-layer rate-splitting multiple access (RSMA) framework. Unlike conventional fixed-position deployments, the...
Kamran Ebrahimi, Farbod Borhani, Zahra Mehrzad et al.· IEEE Transactions on Communi...· 0 citations
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