The main challenges for massive machine type communication in 5G system are to support random access users and control signaling overhead data processing complexity. To address these challenges, we propose a novel compressed sensing (CS)-based non-orthogonal multiple (NOMA) scheme, called CS-NOMA, which introduces low coherence spreading (LCS) signatures enable joint activity detection without requiring the information of advance. We present sufficient condition construction LCS ensure that...

A key technology in the 5th generation (5G) wireless communications is non-orthogonal multiple access (NOMA) which can effectively support massive random access. Since a 5G system number of active users generally does not exceed 10% total practice, main challenge for multi-user detection (MUD) joint sparse and their data. To address this challenge, we propose novel compressed sensing based NOMA (CS-NOMA) scheme be deployed CDMA or an OFDM have control signaling overhead need no knowledge...

The introduction of 5G and beyond systems brings new challenges for efficiently supporting the random access a massive number users with ultra-reliable low-latency requirements. To address these challenges, we propose novel compressed sensing (CS)-based nonorthogonal multiple (NOMA) multiple-input multiple-output (MIMO) scheme, called CS-NOMA MIMO downlink mission-critical machine-type communication (mmcMTC). By taking advantage tensor CS techniques, CS-based packet (frame) structure, TCS...

To meet the need of data-intensive continuous monitoring, recent research on energy-efficient data gathering in wireless sensor networks (WSNs) has explored use compressive sensing (CS) to exploit both spatial and temporal correlations data. However, performance CS-based methods been limited since most work only considers structured sparsity natural signals ignores amplitude signals. In this paper, are considered jointly by assuming spatially temporally correlated satisfies simultaneous...

The topic of the rank minimization problem with affine constraints has been well studied in recent years. However, many applications data can exhibit other structures beyond simply being low rank. For example, images and videos present complex spatio-temporal structures, which are largely ignored by current (ARM) methods. In this paper, we propose a novel approximate message passing (AMP)-based approach that is capable capturing additional matrix entries, be implemented wide range little or...

This paper considers a compressive sensing (CS) approach for hyperspectral data acquisition, which results in practical compression ratio substantially higher than the state-of-the-art. Applying simultaneous low-rank and joint-sparse (L&S) model to data, we propose novel algorithm joint reconstruction of based on loopy belief propagation that enables exploitation both structured sparsity amplitude correlations data. Experimental with real datasets demonstrate proposed outperforms...

In order to reduce the amount of hyperspectral imaging (HSI) data transmission required through remote sensing (HRS), we propose a structured low-rank and joint-sparse (L&S) compression reconstruction method. The proposed method exploits spatial spectral correlations in HSI using sparse Bayesian learning compressive (CS). By utilizing simultaneously L&S model, employ information principal components reconstruct images. simulation results demonstrate that is superior LRMR SS&LR methods terms...

Through the investigation of current situation talent training mode product design specialty in higher vocational colleges, it is found that has some problems, such as lack pertinence curriculum setting, inaccurate orientation objectives, and insufficient practical teaching conditions. Therefore, context new era, colleges must establish a system oriented by job demand, strengthen construction "double qualified" teachers conditions, optimize structure system, pay attention to links, actively...

The main challenges for machine type communication (MTC) are not only supporting the random access of massive users, but also increasing spectral efficiency in future 5G system. To address these challenges, we propose a novel compressed sensing (CS) based non-orthogonal multiple (NOMA) input output (MIMO) scheme, called CS-NOMA MIMO downlink MTC. In proposed version low mutual coherence spreading signatures, named CS is introduced to enable system overloading. Furthermore, CS-based tensor...

In order to meet the demands of data-intensive continuous monitoring in wireless body area network, we address a structured sparse signal recovery method exploit both spatial and temporal correlations data using compressive sensing (CS). Using simultaneously low-rank joint-sparse (L&S) model, employ Bayesian learning treatment by incorporating an L&S-inducing prior over appropriate hyperpriors all hyperparameters, resulting effective reconstruction L&S data. Simulation results suggest that...

ERP system which is based on the systematic management thinking provides decision-making and staff with platform. However, facing many difficulties challenges in Project Management, including high costs inadequate training, etc. This article focuses enterprises, conditions of limited resources, giving full play to features process project implementation, multi-angle(from budget, cost, quality) analyzing importance introduction system. It that plays a considerable role improving efficiency...

UHV transmission lines are characterized by small distributed resistance and inductance, large capacitance, long lines, etc., their overvoltage is more serious. The multiple an important basis for determining the insulation level of system. Therefore, restraining we can reduce level, construction investment damage to various power equipment. In this paper, noload switching 1000kv taken as research object. By using MATLAB software, trategies,such as, circuit breakers with closing resistances,...

E-health monitoring signals collected from wireless body area networks (WBANs) usually have some highly correlated structures in a certain transform domain (e.g., discrete cosine (DCT)). We exploit these and propose fast recovery algorithm for low-rank joint-sparse (L&S) structured WBAN signal the framework of compressed sensing (CS). By using simultaneously L&S model, we employ number bigger singular values Bayesian learning which incorporates an L&S-inducing prior over appropriate...

Abstract When no-load closing or the voltage recovers after external fault removal of transformer, inrush current will be caused due to saturation iron core, which may lead misoperation relay protection device, overvoltage and damage equipment insulation. It is necessary find a method restrain harm transformer. In this paper, Matlab / PSB used simulate three-phase transformer under conditions switching on removal, simulation research carried out by changing angle connection group suppress...

In this paper, we consider the reconstruction of a high-dimensional seismic volume with randomly missing traces. Seismic data in frequency-space domain are represented via high-order tensor. Applying parallel matrix factorization model to underlying tensor, propose an iterative approximate message passing (AMP) approach interpolation based on loopy belief propagation. particular, extend bilinear generalized AMP (BiG-AMP) incorporate low-rank factorizations by using "turbo" framework,...

This paper considers a compressive sensing (CS) approach for hyperspectral data acquisition, which results in practical compression ratio substantially higher than the state-of-the-art. Applying simultaneous low-rank and joint-sparse (L&S) model to data, we propose novel algorithm joint reconstruction of based on loopy belief propagation that enables exploitation both structured sparsity amplitude correlations data. Experimental with real datasets demonstrate proposed outperforms...

We study the node isolation probability of two coexisting wireless ad hoc networks (a primary network vs. a secondary network) that operate in same geographic region and share spectrum, where users can communicate if signal-to-interference ratio (SIR) at receiver is larger than threshold. Assuming are distributed as Poisson Point Process (PPP) Matern Cluster (MCP), we investigate impact parameters on probability. Upper lower bounds for heterogeneous overlaid given. Numerical simulation...

The dynamic responses of TTRs in the deep water were studied considering coupled random heave platform and VIV. parametric excitation is set up motion platform. vortex lift force calculated with time-varying coefficient based on Van der Pol drafting oscillator model. equation VIV vibration (PEV) established program solving PEV developed. response induced by parametrical for TTR Truss Spar, characteristics are investigated. results show that can magnify TTRs, it will change main frequency vibration.

In this paper, ATPDraw software is used to simulate the opening overvoltage and its suppression of 750 kV no-load transmission line under arc non reignition multiple reignition. The simulation results show that when not reburning, over-voltage amplitude caused by operation will increase, maximum about 1.2 times power supply voltage amplitude. reburning occurs, increase rapidly at moment contact reburning. With times, greater. Installation shunt reactors both ends reduces possibility re...