The accuracy of positioning in ultra-wide band (UWB) systems can be improved by identifying the conditions of line-of-sight (LOS) and non-line-of-sight (NLOS) propagation and taking appropriate measures. At present, machine learning methods have already been extensively applied to NLOS identification. Unfortunately, those traditional methods are incapable of performing well in the cases of small samples and class-imbalance samples. In this letter, a novel method is proposed to identify LOS and NLOS components by utilizing Capsule Networks (CapsNet). As indicated by simulation results, the CapsNet-based method allows LOS and NLOS measurements to be classified with 94.63% accuracy, 95.58% precision, 94.74% recall rate, and a 0.9490 F2-score. In addition, CapsNet is compared against decision tree (DT), least squares vector machine (LS-SVM) and K nearest neighbor (KNN) based on experimental data. The comparison results show that the proposed CapsNet outperforms benchmark methods in the cases of both small samples and classimbalance samples.

With the growing demand, Wireless Multimedia Sensor Networks (WMSNs) play an increasingly important role, which enhances the capacity of typical Wireless Sensor Networks (WSNs). Additionally, integrating satellite systems into WMSNs brings about the beneficial synergy, especially in rural and sparsely populated areas. However, the available spectrum resource is scarce, which contradicts the high-speed content required for multimedia. Cognitive radio is a promising solution to address the conflict. In this context, we propose a novel spectrum-sharing method for the integrated wireless multimedia sensor and cognitive satellite network based on the dynamic frequency allocation. Specifically, the Low Earth Orbit (LEO) satellite system plays the role of the auxiliary to connect sensor nodes and the remote control host, and it shares the same frequency with the Geostationary Earth Orbit (GEO) system in the downlink. Because the altitudes of GEO and LEO satellites differ greatly, the beam size of GEO is much larger than that of LEO, which provides the opportunity for LEO beam to reuse the frequency that was allocated to the GEO beam. A keep-out region is defined to guarantee the spectral coexistence based on the interference analysis in the worst case. In addition, a dynamic frequency allocation algorithm is presented to deal with the dynamic configuration caused by the satellite motion. Numerical results demonstrate that the dynamic spectrum-sharing method can improve the throughput.

This work studied the event-detection problem in an Internet of Things (IoT) system, where a group of sensor nodes are placed in the region of interest to capture sparse active event sources. Using compressive sensing (CS), the event-detection problem is modeled as recovering the high-dimensional integer-valued sparse signal from incomplete linear measurements. We show that the sensing process in IoT system produces an equivalent integer CS using sparse graph codes at the sink node, for which one can devise a simple deterministic construction of a sparse measurement matrix and an efficient integer-valued signal recovery algorithm. We validated the determined measurement matrix, uniquely determined the signal coefficients, and performed an asymptotic analysis to examine the performance of the proposed approach, namely event detection with integer sum peeling (ISP), with the density evolution method. Simulation results show that the proposed ISP approach achieves a significantly higher performance compared to existing literature at various simulation scenario and match that of the theoretical results.

Based on the signal characteristics of the existing weighted fractional fourier transform (WFRFT) communication, this paper studies the equivalent signal to noise ratio (SNR) and bit error rate (BER) of the non-target receiver under the condition of the transformation parameter errors, with the purpose of measuring the anti-parameter scanning characteristics of the single-parameter WFRFT signal. The constellation splitting characteristics of multi-parameter WFRFT signal are further studied.Multi-parameter WFRFT modulation can not only improve the resistance of single-parameter system to parameter scanning detection, but also effectively hide the original modulation mode due to its characteristic of splitting modulation constellation.