Current Issue : October - December Volume : 2019 Issue Number : 4 Articles : 5 Articles
Frequency diverse array- (FDA-) based directional modulation (DM) is a promising technique for physical layer security, due to\nits angle-range dependent transmit beampattern. However, the existing schemes are not suitable for the broadcasting scenario,\nwhere there are multiple legitimate users (LUs) to receive the confidential message. In this paper, we propose a novel random\nfrequency diverse array- (RFDA-) based DM scheme to realize the point to multi-point broadcasting secure transmission in both\nangle and range dimension. In the first stage, the beamforming vector is designed to maximize the artificial noise (AN) power,\nwhile satisfying the power requirement of LUs for transmitting the confidential message simultaneously. In the second stage, the\nAN projection matrix is obtained by maximizing signal-to-interference-plus-noise ratio (SINR) at the LUs. The proposed scheme\nonly broadcasts the confidential message to the locations of LUs while the other regions are covered by AN, which promotes the\nsecurity of the wireless broadcasting system. Moreover, it is energy efficient since the power of each LU is under accurate control.\nNumerical simulations are presented to validate the performance of the proposed scheme....
With the growing development of smartphones equipped with Wi-Fi technology and\nthe need of inexpensive indoor location systems, many researchers are focusing their efforts on\nthe development of Wi-Fi-based indoor localization methods. However, due to the difficulties in\ncharacterizing the Wi-Fi radio signal propagation in such environments, the development of universal\nindoor localization mechanisms is still an open issue. In this paper, we focus on the calibration of\nWi-Fi-based indoor tracking systems to be used by smartphones. The primary goal is to build\nan accurate and robust Wi-Fi signal propagation representation in indoor scenarios.We analyze\nthe suitability of our approach in a smartphone-based indoor tracking system by introducing a\nnovel in-motion calibration methodology using three different signal propagation characterizations\nsupplemented with a particle filter. We compare the results obtained with each one of the three\ncharacterization in-motion calibration methodologies and those obtained using a static calibration\napproach, in a real-world scenario. Based on our experimental results, we show that the use of an\nin-motion calibration mechanism considerably improves the tracking accuracy....
In the problem of target tracking, different types of biases can enter into the measurement collected by sensors due to various\nreasons. In order to accurately track the target, it is essential to estimate and correct the measurement bias. Considering practical\nbackgrounds, the bias is assumed to be locally stationary Gaussian distributed and an iterative estimation algorithm is proposed.\nFirstly, a mechanism is established to detect whether the bias switches between different Gaussian distributions. Secondly, the\nexpectation maximization algorithm with the assistance of extended Kalman filtering and smoothing is proposed to iteratively\nestimate the bias and target state in an offline manner. Simulations show the proposed algorithm can suppress the impact of the\nmeasurement bias on target tracking....
Due to data loss and sparse sampling methods utilized inWSNs to reduce energy consumption, reconstructing the raw sensed data\nfrompartial data is an indispensable operation. In this paper, a real-time data recovery method is proposed using the spatiotemporal\ncorrelation among WSN data. Specifically, by introducing the historical data, joint low-rank constraint and temporal stability are\nutilized to further exploit the data spatiotemporal correlation. Furthermore, an algorithmbased on the alternating directionmethod\nof multipliers is described to solve the resultant optimization problem efficiently. The simulation results show that the proposed\nmethod outperforms the state-of-the-artmethods for different types of signal in the network....
The shared storage is essential in the decentralized system. A straightforward storagemodel with guaranteed privacy protection on\nthe peer-to-peer network is a challenge in the blockchain technology.The decentralized storage system should provide the privacy\nfor the parties since it contains numerous data that are sensitive and dangerous if misused by maliciously. In this paper, we present a\nmodel for shared storage on a blockchain network which allows the authorized parties to access the data on storage without having\nto reveal their identity. Ring signatures combined with several protocols are implemented to disguise the signer identity thereby\nthe observer is unlikely to determine the identity of the parties.We apply our proposed scheme in the healthcare domain, namely,\ndecentralized personal health information (PHI). In addition, we present a dilemma to improve performance in a decentralized\nsystem....
Loading....