Generative Models for Modeling and Synthesizing MIMO Channels in Adverse Weather Conditions

The push for broader coverage in future cellular networks depends on reliable service, yet this is increasingly harder to do as we encounter more instances of extreme weather conditions. In extreme weather conditions, we have difficulty evaluating coverage due to limited access to channel measurements. In this paper, we generate channel state information (CSI) in low and moderate weather conditions to synthesize realistic MIMO CSI under adverse weather conditions. Our primary contributions are to (1) synthesize MIMO channel datasets incorporating three weather types, each with three intensity levels, representative of practical 5G/6G scenarios; (2) train a diffusion model conditioned on weather using channel samples obtained through conventional pilot-based estimation under low and moderate weather intensities, and subsequently use it to generate channel realizations for severe weather conditions; and (3) evaluate the downlink Bit Error Rate (BER) and Outage Probability measures using the generated channels. The results show that diffusion-based generative models provide a scalable, data-driven alternative for channel modeling in harsh environments and can generalize to severe weather conditions using only low- and moderate-intensity training data.

MIMO Zak-OTFS: Channel Estimation, Detection, and Throughput Analysis

Zak-Orthogonal Time Frequency Space (Zak-OTFS) modulation has demonstrated substantial performance gains over cyclic-prefix orthogonal frequency-division multiplexing (CP-OFDM) in highly time- and frequency-selective channels. In this paper, we extend Zak-OTFS to a multiple-input multiple-output (MIMO) framework. We first derive a complete system model for MIMO Zak-OTFS based directly on the physical multipath channel; ours is the first work to do so. We then propose an efficient channel estimation method using structured pilot placement in the delay-Doppler (DD) domain. The proposed approach is evaluated under the standardized CDL-C channel model, demonstrating that the advantages of Zak-OTFS observed in SISO scenarios extend to MIMO systems, particularly its robustness to Doppler and inter-carrier interference (ICI). We identify a fundamental crossover behavior: CP-OFDM performs slightly better at low SNR and low Doppler, while Zak-OTFS excels at higher SNR or under severe Doppler dispersion. Furthermore, we show that the crossover points for SNR and Doppler shift inversely to each other. We also observe that Zak-OTFS, particularly with MIMO, exhibits increased sensitivity to high values of pilot-to-data power ratio (PDR), but has a similar optimal PDR as CP-OFDM.