AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Sensing-aided beam prediction can reduce the beam-training overhead of millimeter-wave (mmWave) systems by leveraging environmental information from complementary modalities such as vision and position. However, the resulting sensing and inference pipeline can be energy-intensive, motivating the use of energy-efficient...
This paper investigates a reconfigurable intelligent surface (RIS)-aided hybrid beamforming (HBF) framework for downlink multi-user millimeter-wave systems operating under practical hardware constraints, and develops a hardware-constrained optimization problem to maximize the geometric mean (GM) of user rates, thereby...
In this paper, we investigate the sum rate maximization problem for integrated sensing and communication (ISAC) systems enabled by a flexible intelligent metasurface (FIM) deployed at the base station. By enabling element movement through surface morphing, the FIM introduces additional spatial degrees of freedom that c...
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