Environment Mapping Based on mmWave MIMO OFDM Communication Systems towards 6G Integrated Communication and Sensing

We focus on environment mapping (EM) based on millimeter-wave (mmWave) multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) towards 6G integrated communication and sensing (ICAS), which is indispensable for location-aware intelligent services. However, mmWave MIMO-based EM is challenging due to random channel fading and complex problem structures. To address these challenges, we propose an efficient mmWave MIMO-based EM scheme for 6G ICAS. Firstly, a channel equalization-enhanced EM scheme is devised, where environment reflectors are detected, and fading coefficients are simultaneously estimated. Based on this, the disturbance from random fading is alleviated via channel equalization. Secondly, a hybrid-criterion-driven grid sampling-based Bayesian inference scheme is developed in our EM solution to address the challenge from complex problem structures. As a result, the associated EM performance is improved. It is verified by our simulations that the proposed EM method outperforms state-of-the-art baselines, due to our problem-specific development for addressing those challenges.