Thin-film lithium niobate-based sensing-computing integrated photonic chip for microwave frequency discrimination

Real-time and accurate identification of microwave frequencies is of great significance for applications such as radar detection, electronic countermeasures, and future 6G wireless communications. Traditional electronic chip-based frequency discrimination schemes face severe challenges in power consumption and cost when achieving ultra-wide bandwidths, making it difficult to meet the urgent demand for ultra-wideband in applications like 6G. Based on thin-film lithium niobate photonic integration technology, this paper proposes and experimentally demonstrates a sensing-computing integrated microwave frequency discrimination photonic chip, aiming to achieve real-time microwave frequency identification in the optical domain. Firstly, the microwave signal is converted into an optical signal via an on-chip thin-film lithium niobate electro-optic modulator, and then utilizes a disordered microring lattice to construct a photonic reservoir. The incident light carrying the microwave signal information undergoes complex resonance and interference effects, mapping it into a high-dimensional optical response, thereby achieving ultra-low-power, high-speed nonlinear feature extraction at the physical layer. This architecture significantly reduces reliance on high-speed analog-to-digital converters and subsequent electronic processors. Experimental results show that the device achieves single-shot real-time frequency identification over an ultra-wide microwave frequency range from 10 MHz to 66.01 GHz, with a root mean square error of 40 MHz. Furthermore, a multi-tone signal classification and recognition task was performed, achieving an accuracy of 95%. The scheme proposed in this paper provides an efficient new approach for real-time ultra-wideband microwave frequency measurement and has potential in fields such as microwave photonic signal analysis, real-time spectrum sensing, and on-chip intelligent photonic information processing.