Integrated sensing and communication (ISAC) is a key enabler of fifth-generation and beyond networks and a multitude of futuristic applications. However, the coexistence, scheduling and  scarcity issues due to additional sensing signals are valid concerns. If a communicating device also requires sensing, it can use its communication signal for sensing. But if a non-communicating device requires sensing, the additional sensing signals will cause extra traffic in the network. Thus, in this letter, a novel integrated sensing and communication with iterative channel estimation (ISAC-ICE) method is proposed to provide spectral efficiency while maintaining sensing and communication performance. The simulation results and complexity analysis demonstrate that the proposed method with a linearithmic complexity enables non-orthogonal multiple accessing (NOMA) of ISAC.

Orthogonal frequency division multiplexing (OFDM) is widely used and works efficiently for the communication, but emerging applications requires OFDM to be flexible to meet sensing requirements. The time-frequency waveform design of OFDM for dual-functional radar-communications (DFRC) is critical to achieve the future communication and sensing requirements. Therefore, we propose a novel method to minimize Cram\’{e}r-Rao bounds (CRBs) of the delay and Doppler estimation to improve radar performance of an OFDM DFRC system. Although some methods are proposed in the literature to improve the CRBs, these methods either require feedforward signaling or subcarrier reservation. However, it is possible to exploit the constellation extension of quadrature amplitude modulation (QAM)  to achieve lower CRBs without these requirements. Therefore, the proposed method provides a transparent communication along with the CRB minimization for conventional OFDM systems. For the evaluation of the proposed method, CRB and symbol error rate (SER) are considered in the simulation results. Furthermore, the theoretical SER  analysis of the proposed method is derived to understand the effects of CRB minimization on the communication performance.