Multi-modal sensing has demonstrated remarkable efficacy for intra-site beam prediction. However, generalizing trained models to unseen environments remains a significant challenge, primarily due to the inherent environment-specific wireless propagation characteristics. Existing cross-environment works rely on either r...
Lei Wang, Chang-Yi Li, Kai Dong et al.· IEEE International Symposium...· 0 citations
Grant-free random access in massive machine-type communications requires detecting a small active set from length-<inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> uplink pilots received at an <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula>-antenna base station. C...
Xin-Jue Wang, Zhi-Yong Wang, S. A. Vorobyov et al.· IEEE Transactions on Wireles...· 0 citations
Large Language Model (LLM) reprogramming-based beam prediction demonstrates strong data efficiency by adapting pretrained language models for vehicle-to-infrastructure (V2I) beam prediction, yet the resulting model complexity makes such approaches impractical for latency-sensitive deployment. We propose LLMBP-Lite, a c...
Kai Dong, Lei Wang, Chang-Yi Li et al.· 0 citations
A nonconvex energy cost minimization problem is introduced by considering a user-specific energy cost ratio coefficient that explicitly balances UE-AP energy consumption according to heterogeneous device energy states and a double-loop framework combining successive convex approximation and alternating direction method...
Kai Dong, Lei Wang, S. Vorobyov et al.· IEEE Transactions on Wireles...· 0 citations
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