Xidian University

About: Xidian University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Antenna (radio) & Computer science. The organization has 32099 authors who have published 38961 publications receiving 431820 citations. The organization is also known as: University of Electronic Science and Technology at Xi'an & Xīān Diànzǐ Kējì Dàxué.

Blockchain Enabled Trust-Based Location Privacy Protection Scheme in VANET

Abstract: While enjoying the convenience brought by Location Based Service (LBS), the location privacy of vehicles in VANET may be disclosed. Distributed k -anonymity, as one of the most popular privacy protection methods, fails to take the trustworthiness of participants into account, resulting in malicious tracing of vehicles, which further leads to the sensitive information leakage, and even the safety threat of personal property. To address this issue, we propose a blockchain enabled trust-based location privacy protection scheme in VANET. Specifically, by analyzing the different requirements of the request vehicle and the cooperative vehicle during the process of constructing the anonymous cloaking region, as well as combining the characteristics of these two roles, we devise the trust management method based on Dirichlet distribution , such that both the requester and the cooperator will only cooperate with the vehicles they trust. Moreover, by employing blockchain, we also proposed the data structure to record the trustworthiness of vehicles on publicly available blocks timely, so that any vehicle can access the historical trust information of counterparties whenever necessary. Finally, the construction process of anonymous cloaking region is presented. Security analysis and extensive experiments indicate that the proposal is resilient to various trust model attacks, it can effectively detect the malicious vehicles, and preserve the location privacy of vehicles in the anonymous cloaking region construction, while the required time delay is limited.

Performance analysis for NOMA energy harvesting relaying networks with transmit antenna selection and maximal-ratio combining over Nakagami- m fading

Abstract: Non-orthogonal multiple access (NOMA), which is an effective solution to improve spectral efficiency, has been considered as an emerging candidate for the fifth generation multiple access. In addition, simultaneous wireless information and power transfer, which aims to maximise energy efficiency, has received significant attention. In this study, the authors design NOMA for downlink energy harvesting (EH) multiple-antenna relaying networks. The base station communicates with multiple mobile users simultaneously via an EH relay node. In the first slot, the relay node harvests energy from the received signals; and in the second slot, the relay node uses the harvested energy to broadcast the received signals to all mobile users. Antenna selection is adopted at the base station while maximal-ratio combining is applied at the mobile users. The outage performance for the NOMA-EH relaying networks is studied over Nakagami- m fading and closed-form expressions for the outage probability are obtained. In addition, the presented simulation results demonstrate the correctness of the authors' analysis and the advantage of NOMA over conventional orthogonal multiple access.

Identification and elimination of redundant control places in petri net based liveness enforcing supervisors of FMS

Abstract: In the past two decades, a number of Petri-net-based approaches were proposed for deadlock prevention in flexible manufacturing systems (FMS). An FMS is modeled as a Petri net, and then the controller or the liveness enforcing supervisor (LES) is computed as a Petri net. A live Petri net (LPN) guarantees deadlock-free operations of the modeled FMS. An LES consists of a number of control places (CPs) and their related arcs. To-date most of the attention has been paid to make the underlying Petri net models live without questioning whether or not all of the computed CPs are necessary. It is often the case that the number of CPs determined by these approaches is not minimal. Reducing it in order to reduce the complexity of the controlled system is an important issue that was not tackled before. To address this problem, this paper proposes a redundancy test for an LES of an FMS. The proposed approach takes an LPN model, controlled by n CPs, as input and in the existence of any redundant CPs it produces redundant and necessary CPs. The proposed approach is applicable to any LPN consisting of a Petri net model (PNM), controlled by means of a set of CPs.

STDP-Based Unsupervised Spike Pattern Learning in a Photonic Spiking Neural Network With VCSELs and VCSOAs

Abstract: We propose a photonic spiking neural network (SNN) consisting of photonic spiking neurons based on vertical-cavity surface-emitting lasers (VCSELs). The photonic spike timing dependent plasticity (STDP) is implemented in a vertical-cavity semiconductor optical amplifier (VCSOA). A versatile computational model of the photonic SNN is presented based on the rate equation models. Through numerical simulation, a spike pattern learning and recognition task is performed based on the photonic STDP. The results show that the post-synaptic spike timing (PST) is eventually converged iteratively to the first spike timing of the input spike pattern via unsupervised learning. Additionally, the convergence rate of the PST can be accelerated for a photonic SNN with more pre-synaptic neurons. The effects of VCSOA parameters on the convergence performance of the unsupervised spike learning are also considered. To the best of our knowledge, such a versatile computational model of photonic SNN for unsupervised learning and recognition of arbitrary spike pattern has not yet been reported, which would contribute one step forward toward numerical implementation of a large-scale energy-efficient photonic SNN, and hence is interesting for neuromorphic photonic systems and spiking information processing.