An Innovative Environment Sensing Method Exploiting the Oversampled OFDM Cyclic Prefixes

The widely applied orthogonal frequency division multiplexing (OFDM) system naturally contains oversampled cyclic prefixes (CP) in the generation process, which provide a wealth of environmental information and higher distance resolution for integrated sensing and communication (ISAC) but is underutilized. Therefore, we develop a compressed sensing (CS) model with oversampled CP, reaching the higher distance resolution limit corresponding to the sample rate of the analog-to-digital converter (ADC) than the fixed signal bandwidth. Since the measurement matrix formed by shifting adjacent oversampled CP pairs is ill-conditioned, we proposed random modulation and random extraction from multiple oversampled CP to increase the validity of the observations. To exploit the channel fading characteristics and sparsity of scattering points, we propose an element-by-element demodulator based on the orthogonal approximate message passing (OAMP) algorithm, called the element-wise OAMP (E-OAMP) algorithm. The simulation results validate the outstanding performance of the proposed algorithm over traditional CS algorithms.