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Linghui Miao

Publications and source records attributed to Linghui Miao.

2 recordsLinked to original sources

Toward Service-Balanced ISAC: From Coupled RAN to De-Coupled RAN

Sixth-generation (6G) applications require radio access networks (RANs) to support reliable communication and seamless sensing across their operating regions. In coupled RAN deployments, shared downlink transmitting and uplink receiving sites constrain the network's ability to accommodate asymmetric links and different sensing geometries. De-Coupled RAN (DC-RAN) separates these functions, allowing independently deployed and coordinated base stations to extend uplink and downlink communication and sensing coverage. How this flexibility translates into balanced communication and sensing services, however, remains insufficiently explored. This article revisits the evolution from coupled to DC-RAN from the perspective of service-balanced integrated sensing and communication (ISAC). It examines how architectural choices affect the availability of both services, with communication-sensing coverage symmetry capturing their spatial alignment under application-specific quality requirements. Practical challenges include preserving communication consistency, maintaining sensing continuity, and coordinating distributed resources. Two case studies illustrate how DC-RAN can support coverage symmetry alongside consistent communication, and how complementary observations can sustain continuous and accurate sensing. These examples inform a discussion of future research toward service-balanced ISAC.

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UAV Swarming for Air-Ground ISAC via Cross-Region Cooperation

To serve the volumetric air-ground space, uncrewed aerial vehicles (UAVs) are urgently needed. Yet, relying on them for integrated sensing and communication (ISAC) introduces two key challenges: 1) dynamic and imbalanced ground communication demand, and 2) limited observation diversity for sensing. To address these issues, a cross-region cooperative framework is designed to coordinate UAV swarms. Specifically, a service-driven regional partitioning scheme is proposed to support traffic-aware UAV communication, and an adaptive handshaking mechanism is introduced to improve cooperative sensing accuracy by mitigating residual inter-region phase errors with controlled synchronization overhead. Based on these designs, a region-level multi-agent proximal policy optimization (MAPPO) framework with centralized training and decentralized execution (CTDE) is developed for cross-region cooperative decision-making. Simulation results demonstrate that the proposed method achieves a communication quality-of-service (QoS) of approximately 90% and reduces the Cramér-Rao bound (CRB) by about 45% compared to conventional baselines.

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