A novel double-parameters sensor based on composite interference structure has been designed and implemented in this letter. It can be regarded as a cascade of the traditional single mode-multimode-single mode structure and multimode-single mode-multimode structure. The output signal is a series of interference superposition; external parameters can be measured by monitoring the spectral characteristics of interference dips. The interesting properties of the sensor include good operation linearity. In addition, simultaneous measurement of temperature and refractive index have been achieved. The sensitivities of temperature and refractive index can reach up to 0.1385 nm/°C and 100.97 nm/RIU, respectively.

An optical fiber sensor for simultaneous measurement of humidity and temperature is proposed and investigated. The sensor is composed of a pokal taper and a peanut taper spliced at both ends of a single-mode fiber, respectively. In the experiment, the variations of the dip wavelength are used to measure the parameter sensing characteristics. The sensing area is coated with a concentration of 1 mg/ml graphene dispersion by using the optical driven deposition method. Experimental results show that the sensor has a good linear relationship with temperature and humidity. When the humidity measurement range is $ 30\% {\rm{RH}} \sim 70\% {\rm{RH}} $, the sensitivities are 0.059 nm/%RH and 0.133 nm/%RH, respectively. When the temperature measurement range is $ {0^ \circ }{\rm C} \sim {40^ \circ }{\rm C} $, the sensitivities are 0.254 nm/°C and 0.269 nm/°C, respectively. This sensor has the advantages of small size, low cost, and high response.

The high peak-to-average power ratio (PAPR) deteriorates the performance of coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems. Machine learning (ML) has evolved into a powerful technology to reduce PAPR with its flexible learning ability. We propose a joint scheme which adopts iterative partial transmission sequence (IPTS) scheme cascading a feedforward neural network (FNN) trained on iterative $\pmb {\mu }$ -law companding and filtering (IMCF) algorithm. The proposed scheme greatly reduces the complexity of partial transmission sequence (PTS) scheme, which has excellent PAPR reduction effect and BER performance. Our method achieves a 5.03 dB PAPR reduction for $10\pmb {^{-4}}\,\,\pmb {CCDF}$ and an additional transmission distance of 200 km SMF for $10\pmb {^{-3}}\,\,\pmb {BER}$ , compared with the original OFDM signal. Meanwhile, the computational complexity of proposed scheme is reduced by 32.4%, compared with IPTS cascading IMCF (IPTS-IMCF) scheme.

A novel structure of photonic crystal fiber (PCF) Mach-Zehnder interferometer (MZI) for temperature and relative humidity measurement is proposed. The novel structure is composed of two sections of no core fiber (NCF) with a piece of PCF. The sensitivity of the proposed sensor is enhanced by adopting NCF coupling method. The results show that the sensitivities of temperature are 0.059 nm/°C, 0.074 nm/°C and 0.130 nm/°C in the range of 25 °C to 70 °C, and the sensitivities of relative humidity are 0.020 nm/%RH, 0.027 nm/%RH and 0.036 nm/%RH in the range of 30%RH to 70%RH. The sensor has the advantages of high stability, good linearity fit and simple structure, which indicates that the sensor has the potential of making an important contribution to the field of biology, chemistry, and medical.