Adaptive Pilot Pattern Design for Ultra-Low Latency Communication in Beyond 5G and 6G Systems

This paper introduces an adaptive pilot design for wireless communication systems, dynamically adjusting the number of pilot symbols based on historical channel information. Focusing on Orthogonal Frequency Division Multiplexing (OFDM) systems formally adopted in 5G networks and is a potential candidate for future 6G systems, we employ Generative Adversarial Networks (GAN) to model and predict channel states by leveraging spectral and temporal correlations within the OFDM resource grid. The predicted channel state is then used alongside the available pilots to perform channel estimation. As the accuracy of channel predictions improves, fewer pilots are needed to achieve the desired channel estimation accuracy. Thus, we propose a scheme to estimate the GAN prediction accuracy, which is essential for determining the required number of pilots. Additionally, the proposed method supports ultra-low latency communication by performing channel estimation within the duration of a single OFDM symbol, making it highly suitable for beyond 5G and 6G networks. Simulation results demonstrate significant improvements in channel estimation accuracy compared to traditional fixed-pilot schemes, thereby reducing the number of required pilots to achieve a target channel accuracy.