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Integrated sensing and communication (ISAC) is a promising technology tosimultaneously provide high-performance wireless communication and radarsensing services in future networks. In this paper, we propose the concept of\emph{integrated super-resolution sensing and communication} (ISSAC), whichuses super-resolution algorithms in ISAC systems to achieve extreme sensingperformance for those critical parameters, such as delay, Doppler, and angle ofthe sensing targets. Based on practical fifth generation (5G) New Radio (NR)waveforms, the signal processing techniques of ISSAC are investigated andprototyping experiments are performed to verify the achievable performance. Tothis end, we first study the effect of uneven cyclic prefix (CP) lengths of 5GNR orthogonal frequency division multiplexing (OFDM) waveforms on varioussensing algorithms. Specifically, the performance of the standard Periodogrambased radar processing method, together with the two classical super-resolutionalgorithms, namely, MUltiple SIgnal Classification (MUSIC) and EstimatingSignal Parameter via Rotational Invariance Techniques (ESPRIT) are analyzed interms of the delay and Doppler estimation. To resolve the uneven CP issue, anew structure of steering vector for MUSIC and a new selection of submatricesfor ESPRIT are proposed. Furthermore, an ISSAC experiment platform is setup tovalidate the theoretical analysis, and the experimental results show that theperformance degradation caused by unequal CP length is insignificant andhigh-resolution delay and Doppler estimation of the target can be achieved with5G NR waveforms.

Integrated Super-Resolution Sensing and Communication with 5G NR Waveform: Signal Processing with Uneven CPs and Experiments