A Novel Adaptive Spreading Waveform for Integrated Sensing and Communication - Singh D.; Kumar A.; Joshi H.D.; Singh A.K.; Sarestoniemi M.; Myllyla T.; Magarini M. (My University, 2025)
The increasing demand for radar and communication systems sharing the same hardware platform as well as frequency band has given birth to integrated sensing and communication (ISAC). As both radar and communication systems function on analogous physical phenomena, therefore, they may use the same equipment, spectrum, and signals which effectively improves the spectral efficiency, hardware efficiency, and information processing efficiency of the overall system. Moreover, a combination of communication and sensing is expected to be a main feature of 6G cellular technology. This paper proposes a novel waveform for ISAC applications. The proposed waveform offers adaptive symbol spreading in both time as well as frequency domains and can adapt to real-time channel conditions and given system requirements. Further, it is well-recognized that carrier frequency offset (CFO) destroys the orthogonality between the sub-carriers, generating inter-carrier interference (ICI), while the presence of symbol timing offset (STO) introduces intersymbol interference (lSI), between successive symbols, and phase rotations in the frequency domain, within the same symbol. Motivated by this, the proposed waveform is designed to combat both ICI and lSI and therefore offers superior communication as well as sensing performance. The proposed waveform is compared with traditional waveforms utilized in ISAC applications such as Orthogonal Frequency Division Multiplexing (OFDM), Fractional Fourier Transform based OFDM (FrFT-based OFDM), Orthogonal Chirp Division Multiplexing (OCDM), and Generalized Frequency Division Mul-tiplexing (GFDM) using numerous Monte Carlo simulations. It is observed that the proposed waveform outperforms all existing waveforms for communication performance in terms of average bit error rate (ABER) and sensing performance in terms of Peak to Sidelobe Level (PISL) of ambiguity function (AF). © 2024 IEEE.