Space-Frequency Switching MIMO-OFDM ISAC Systems: Architecture, Radar Imaging Algorithm, and Testbed Experiments

Conventional integrated sensing and communication (ISAC) systems are typically unable to exploit both spatial and spectral diversity simultaneously, which limits overall system performance. To fully harness the benefits of jointly increasing spatial and spectral degrees of freedom (DoF), this paper proposes a novel multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) ISAC architecture that leverages both frequency and antenna switching. In the proposed architecture, each RF chain dynamically selects its transmit/receive antennas and frequency band in each interval, enabling improved radar resolution and offering the potential for increased communication diversity. To support sensing functionality under this dynamic configuration, we introduce a 4D radar imaging algorithm based on orthogonal matching pursuit (OMP). The algorithm achieves super-resolution in range and velocity via oversampling while simultaneously estimating azimuth and elevation angles. Notably, the formulation inherently compensates for phase variations arising from data acquisition across diverse time intervals and frequency bands, enabling accurate target detection. Simulation results demonstrate that the proposed method improves range resolution from 0.41 m to 0.08 m and velocity resolution from 5.0 m/s to 0.125 m/s, while achieving an average precision (AP) of 0.66 compared to 0.02 for the baseline under challenging conditions. On the communication side, we show that the channel gain varies by up to 7 dB across different antenna–frequency band pairs, and this diversity leads to notable improvements in communication performance. Moreover, the implemented testbed confirms the feasibility of reliable multi-band OFDM communication under dynamic switching, highlighting the practical viability of the proposed ISAC framework for next-generation wireless systems.