Ultra-dense indoor next-generation networks suffer severe interference from mobility-induced blockages and localized multi-user hotspots that conventional digital twins~(DTs) cannot anticipate. We propose a generative AI~(GenAI)-enhanced DT framework employing a conditional generative adversarial network~(cGAN) with a spatio-temporal generator and PatchGAN discriminator for proactive rare-event channel synthesis. A worst-case zero-forcing~(WC-ZF) beamformer driven by Monte Carlo synthetic trajectories realizes distributionally robust precoding, with control-channel overhead bounded to $\approx$2.1\,kB per 10\,ms slot. Sionna-based simulations confirm a 5--8\,dB median signal-to-interference-plus-noise-ratio (SINR) gain, 60--70\% packet-loss reduction, and 60--85\% closure of the perfect channel state information (CSI) oracle gap within a 2.8--4.1\,ms inference overhead.
In this paper, the problem of the trajectory design for an intent-based drone operating in resource-constrained, dynamic wireless network environments is studied. In the considered model, the drone acts as a supplementary base station that navigates among ground user clusters to…
Digital twin channel (DTC) aims to establish a real-time digital counterpart of physical wireless channels for reproducing and predicting site-specific propagation characteristics. As a high-precision channel computation method for realistic propagation scenarios, ray tracing (RT…
Artificial intelligence (AI) and machine learning (ML)-based channel estimators silently degrade when propagation conditions drift from their training distributions. This letter proposes a model-agnostic cognitive digital twin (CDT) framework that combines a variational autoencod…
Fast ray tracing (RT) has stimulated the Digital Twin (DT) as an emerging technology for environment-aware communications. Since wireless propagation is governed by the interaction between site geometry and electromagnetic (EM) properties of the environment, DT-based approaches c…
Due to the continuous increase in communication bandwidth and the use of highly efficient yet nonlinear power amplifiers, Digital Predistortion (DPD) algorithms are becoming increasingly complex. In particular, neural network (NN) based DPD approaches using Phase-Normalized NN ar…
Accurate and timely channel state information (CSI) is essential for next-generation wireless systems, yet existing works treat CSI compression and CSI prediction as separate problems, both in academia and in current 3GPP studies. Consequently, channel aging remains insufficientl…