Improved Multiplex Chaos for Integrated Sensing and Communications (ISAC)

Most integrated sensing and communication (ISAC) systems literature focuses on hardware architecture. However, a single waveform that can sense the environment and communicate simultaneously is a better alternative considering the efficiency of electronics. Very few ISAC waveforms have balanced performance between radar and communications. In this work, we propose the chaotic oscillators for ISAC systems. We consider N 2-dimensional chaotic maps that have a set of control parameters that are varied to generate optimized chaotic signals. Each chaotic signal is filtered and segmented to encode the digital information ±1. The encoded signals are superimposed to obtain a multiplexed signal, significantly improving the data rate compared to other ISAC waveforms. The multiplexing approach proposed here does not involve orthogonalization techniques, thereby saving computational resources and time. The generated multiplexed signal s(n) is used for ISAC transmission. Statistical analysis shows that s(n) is similar to the Gaussian noise. Synchronization is established at the communication receiver using a preamble propagated ahead of s(n). Once synchronized, we generate N chaotic filtered signals at the receiver. Segments of the received signal are further correlated with the segments of synchronized chaotic filtered signals to decode the information. The decoding decision is based on the correlation peak values. Through numerical analysis, we show that the proposed communication approach's bit-error-rate (BER) curve matches the BPSK waveform, an optimal antipodal communication waveform. For the radar, a correlation between the transmitted s(n) and the target reflection has a sharp mainlobe that decorrelates within two samples, with sidelobes below -18 dB. Additionally, the ambiguity function has a thumbtack shape, indicating high-resolution radar imaging capabilities.