Joint CFO estimation and interference suppression for Multi-Static sensing in ISAC systems

A fundamental technology driving the sixth-generation (6G) cellular network progress is Integrated sensing and communication (ISAC). However, carrier frequency offset (CFO), brought by local oscillator asynchronization, represents a significant problem in multi-static ISAC systems. While CFO estimation has been extensively researched in communication, the topic remains relatively unexplored for ISAC systems. Additionally, interferences from various sources in ISAC systems can lead to significant performance degradations for CFO estimation. This paper addresses the problem of joint CFO estimation and interference suppression for ISAC systems. We first consider bi-static sensing in ISAC systems, and propose a statistical optimization framework to address the CFO estimation of a signal-of-interest (SOI) arriving at an array in the presence of unknown and arbitrary spatially colored interference-and-noise, together with deriving their Cramér-Rao bounds (CRBs). We show that by assuming an arbitrary and unknown covariance matrix for the interference-and-noise, the estimator we derive attains strong interference suppression capabilities. Moreover, we extend our investigations to multi-static sensing in ISAC systems involving multiple SOIs. We introduce an estimator based on utilizing a cyclic algorithm (CA) and derive the corresponding CRBs. We also derive a decoupled approach (DA) by assuming uncorrelated SOIs to increase the computational efficiency and enable parallel processing. The estimates obtained by DA can be refined by the last step of CA to achieve both improved effectiveness and efficiency. Numerical examples are provided to validate our theoretical analysis and demonstrate the parameter estimation accuracy and interference suppression capabilities of the proposed algorithms.

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