ABSTRACT
In this paper, a slotted conical patch connected to a small triangular patch multiband antenna for both microwave and millimeter-wave applications is presented. The designed antenna has three characteristics. The proposed antenna is a multiband, having a compact size of 0.35λ0 × 0.35λ0 × 0.004λ0 at its lowest operational frequency, i.e., 2.4 GHz, and more importantly, it can cover both the microwave and millimeter-wave bands with a single feeding. According to the -10 dB matching bandwidth, experimental results show that the antenna operates at (2.450-2.495) GHz, (5.0-6.3) GHz, and (23-28) GHz. The reduced size, simple design, and multiband large bandwidth are some of the advantages over the reported designs in the latest literature. Both simulated and experimental results show a good agreement, and the proposed antenna can be used for wireless local area network (WLAN) applications and fifth-generation (5G) wireless communication devices.
ABSTRACT
As a dedicated communication protocol for Internet-of-Things, narrowband internet of things (NB-IoT) needs to establish the communication link rapidly and reduce retransmissions as much as possible to achieve low power consumption and stable performance. To achieve these targets, the low-power scheme of the initial cell search and frequency tracking is investigated in this paper. The cell search process can be subdivided into narrowband primary synchronization signal (NPSS) detection and narrowband secondary synchronization signal (NSSS) detection. We present an NPSS detection method whose timing metric is composed of symbol-wise autocorrelation and a dedicated normalization factor. After the detection of NPSS, the symbol timing and fractional frequency offset estimation is implemented in a resource-efficient way. NSSS detection is conducted in the frequency domain with a calculation-reduced algorithm based on the features of NSSS sequences. To compensate the accumulated frequency offset during uplink transmission, a pilot-aided rapid frequency tracking algorithm is proposed. The simulation results of the proposed cell search scheme are outstanding in both normal coverage and extended coverage NB-IoT scenarios, and the accumulated frequency offset can be estimated with high efficiency.
ABSTRACT
A NTC thermistor-based wearable body temperature sensor was designed. This paper described the design principles and realization method of the NTC-based body temperature sensor. In this paper the temperature measurement error sources of the body temperature sensor were analyzed in detail. The automatic measurement and calibration method of ADC error was given. The results showed that the measurement accuracy of calibrated body temperature sensor is better than ± 0.04 degrees C. The temperature sensor has high accuracy, small size and low power consumption advantages.
Subject(s)
Body Temperature , Calibration , Monitoring, Physiologic/methods , HumansABSTRACT
The designed sensor enables accurate reconstruction of chest-wall movement caused by cardiopulmonary activities, and the algorithm enables estimation of respiration, heartbeat rate, and some indicators of heart rate variability (HRV). In particular, quadrature receiver and arctangent demodulation with calibration are introduced for high linearity representation of chest displacement; 24-bit ADCs with oversampling are adopted for radar baseband acquisition to achieve a high signal resolution; continuous-wavelet filter and ensemble empirical mode decomposition (EEMD) based algorithm are applied for cardio/pulmonary signal recovery and separation so that accurate beat-to-beat interval can be acquired in time domain for HRV analysis. In addition, the wireless sensor is realized and integrated on a printed circuit board compactly. The developed sensor system is successfully tested on both simulated target and human subjects. In simulated target experiments, the baseband signal-to-noise ratio (SNR) is 73.27 dB, high enough for heartbeat detection. The demodulated signal has 0.35% mean squared error, indicating high demodulation linearity. In human subject experiments, the relative error of extracted beat-to-beat intervals ranges from 2.53% to 4.83% compared with electrocardiography (ECG) R-R peak intervals. The sensor provides an accurate analysis for heart rate with the accuracy of 100% for p = 2% and higher than 97% for p = 1%.
