A novel method was proposed for the moving load identi¯cation of bridges based on the in°uence line theory and distributed optical¯ber sensing technique. The method of load and vehicle speed identi¯cation was¯rstly theoretically studied, and then numerical simulation was also performed to study its accuracy and robustness. The numerical results showed that this method was characterized by high accuracy and excellent resistance to noise. Finally, the load identi¯cation of an actual continuous pre-stressed concrete beam bridge was carried out with the proposed method. The bridge consists of four pre-stressed box beams. At the same time, a weigh-in-motion system was also installed about 200 m in front of the bridge to measure the speed and moving loads with a purpose of comparing the load identi¯cation of the proposed method. Long gaugē ber Bragg grating (FBG) sensors with a gauge length of 1.0 m were adhered to the bottom of the beams. The individual loaded vehicles and the corresponding structure response were mainly monitored as standard samples, and the speed and weight of the sample vehicles were monitored and identi¯ed with the proposed method. The results revealed that the distributed long gauge FBG sensors were capable of sensing the structure response precisely and identifying the tra±c load. On the basis of the design information and ambient vibration testing results, a re¯ned model was established and the response under unit moving load was acquired for load identi¯cation. It was also shown that the sensors in di®erent positions can achieve accurate vehicle speed and weight, the relative error of which are within 10% and 15%, respectively.

This letter investigates the secure communication in a reconfigurable intelligent surface (RIS)-aided multiuser massive multiple-input multiple-output (MIMO) system exploiting artificial noise (AN). We first derive a closed-form expression of the ergodic secrecy rate under spatially correlated MIMO channels. By using this derived result, we further optimize the power fraction of AN in closed form and the RIS phase shifts by developing a gradient-based algorithm, which requires only statistical channel state information (CSI). Our analysis shows that spatial correlation at the RIS provides an additional dimension for optimizing the RIS phase shifts. Numerical simulations validate the analytical results which show the insightful interplay among the system parameters and the degradation of secrecy performance due to high spatial correlation at the RIS.

In this paper, the performance of a secure massive multiple-input multiple-output (MIMO) system adopting lowresolution digital-to-analog converters (DACs) is analyzed over spatially correlated wireless channels. A tight lower bound for the achievable secrecy rate is derived with artificial noise (AN) transmitted in the null space of the user channels. Using the analytical results, the impact of spatial correlation on the secrecy rate is explicitly evaluated in the presence of low-resolution DACs. The analytical observations reveal that using low-resolution DACs can be beneficial to the secrecy performance compared with ideal DACs, when the channels are strongly correlated and optimal power allocation is not employed.

No abstract