Turbo Message Passing Based Burst Interference Cancellation for Data Detection in Massive MIMO-OFDM Systems

This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound.

Vector Approximate Message Passing with Sparse Bayesian Learning for Gaussian Mixture Prior

Compressed sensing(CS)aims for seeking appropriate algorithms to recover a sparse vector from noisy linear observations.Currently,various Bayesian-based algorithms such as sparse Bayesian learning(SBL)and approximate message passing(AMP)based algorithms have been proposed.For SBL,it has accurate performance with robustness while its computational complexity is high due to matrix inversion.For AMP,its performance is guaranteed by the severe restriction of the measurement matrix,which limits its application in solving CS problem.To overcome the drawbacks of the above algorithms,in this paper,we present a low complexity algorithm for the single linear model that incorporates the vector AMP(VAMP)into the SBL structure with expectation maximization(EM).Specifically,we apply the variance auto-tuning into the VAMP to implement the E step in SBL,which decrease the iterations that require to converge compared with VAMP-EM algorithm when using a Gaussian mixture(GM)prior.Simulation results show that the proposed algorithm has better performance with high robustness under various cases of difficult measurement matrices.

Message from Editors

IN recent years,the electrical machines and systems have grown so rapidly with more and more applications in emerging civilian industries as well as cutting-edge areas.A group of novel and exciting technologies have been developed every year.First,the research of motors in new and extreme fields have constantly brought amazing progress to achieve better performance through new technologies such as digitalization,etc.Meanwhile,the fast development of power electronics in recent decades has also changed the overall system to be more flexible,and widely extent our boundary of research area.What is more.

BDSec:Security Authentication Protocol for BeiDou-Ⅱ Civil Navigation Message

Due to the lack of authentication mechanism in BeiDou navigation satellite system(BDS),BD-Ⅱ civil navigation message(BDⅡ-CNAV) are vulnerable to spoofing attack and replay attack.To solve this problem,we present a security authentication protocol,called as BDSec,which is designed by using China’s cryptography Shangyong Mima(SM) series algorithms,such as SM2/4/9 and Zu Chongzhi(ZUC)algorithm.In BDSec protocol,both of BDⅡ-CNAV and signature information are encrypted using the SM4 algorithm(Symmetric encryption mechanism).The encrypted result is used as the subject authentication information.BDSec protocol applies SM9 algorithm(Identity-based cryptography mechanism) to protect the integrity of the BDⅡ-CNAV,adopts the SM2 algorithm(Public key cryptosystem) to guarantee the confidentiality of the important session information,and uses the ZUC algorithm(Encryption and integrity algorithm) to verify the integrity of the message authentication serial number and initial information and the information in authentication initialization sub-protocol respectively.The results of the SVO logic reasoning and performance analysis show that BDSec protocol meets security requirements for the dual user identity authentication in BDS and can realize the security authentication of BDⅡ-CNAV.

Anti-Spoofing:Integrated Information Authentication of BeiDou-ⅡCivil Navigation Message

The BeiDou-Ⅱcivil navigation message(BDⅡ-CNAV)is transmitted in an open environment and no information integrity protection measures are provided.Hence,the BDⅡ-CNAV faces the threat of spoofing attacks,which can lead to wrong location reports and time indication.In order to deal with this threat,we proposed a scheme of anti-spoofing for BDⅡ-CNAV based on integrated information authentication.This scheme generates two type authentication information,one is authentication code information(ACI),which is applied to confirm the authenticity and reliability of satellite time information,and the other is signature information,which is used to authenticate the integrity of satellite location information and other information.Both authentication information is designed to embed into the reserved bits in BDⅡ-CNAV without changing the frame structure.In order to avoid authentication failure caused by public key error or key error,the key or public key prompt information(KPKPI)are designed to remind the receiver to update both keys in time.Experimental results indicate that the scheme can successfully detect spoofing attacks,and the authentication delay is less than 1%of the transmission delay,which meets the requirements of BDⅡ-CNAV information authentication.

Effectiveness of Short Message Service Support on Adherence to Chemotherapy Treatment among Patients Attending Cancer Treatment Facilities in Kenya

Introduction: Cancer is a chronic debilitating disease that unnerves patients, communities, and nations. At some point in cancer patient’s disease experience, chemotherapy is used, and the patient is expected to adhere to treatment to improve survival and quality of life. Methods: This multisite Cluster Randomized Trial (CRT) evaluated the effectiveness of mobile phone Short Message Service (SMS) support on the adherence to treatment schedules among adult cancer patients in Kenya. Data was collected using questionnaires. Ethical approvals were obtained from relevant Ethical Review Boards (ERBs). Results: The mean adherence was 83%. There was a significant difference between treatment arms in relation to the adherence. The intervention arm had a higher mean adherence difference, M = 3.913, 95% CI 2.632-5.193, t (402) = 6.006, p ≤ 0.001), with Cohen’s d = 0.60. Although not significant, (χ2dd = 0.151, df = 1, p = 2.064), more women were perfect adheres than males. Perfect adherers were satisfied with SMS support (χ2dd = 7.620, df = 1, p = 0.06), were in the intervention arm (χ2dd = 22.942, df = 1, p ≤ 0.001), and had trust in the care provider (χ2dd = 10.591 p ≤ 0.001). SMS support was not significant in the multivariate analysis but had an estimated effect size of 0.958 (z = 1.424, p = 0.154, CI = 0.242-3.781), indicating that mean adherence was slightly better in the presence of the intervention. Conclusions: SMS-support intervention has demonstrated superiority in influencing adherence. Further, health system-related factors have a significant influence on the adherence to chemotherapy treatment. Interventions to re-design health systems that are responsive to unmet care needs of cancer patients must be explored. .

Artificial Intelligence-Based Sentiment Analysis of Dynamic Message Signs that Report Fatality Numbers Using Connected Vehicle Data

This study presents results from sentiment analysis of Dynamic message sign (DMS) message content, focusing on messages that include numbers of road fatalities. As a traffic management tool, DMS plays a role in influencing driver behavior and assisting transportation agencies in achieving safe and efficient traffic movement. However, the psychological and behavioral effects of displaying fatality numbers on DMS remain poorly understood;hence, it is important to know the potential impacts of displaying such messages. The Iowa Department of Transportation displays the number of fatalities on a first screen, followed by a supplemental message hoping to promote safe driving;an example is “19 TRAFFIC DEATHS THIS YEAR IF YOU HAVE A SUPER BOWL DON’T DRIVE HIGH.” We employ natural language processing to decode the sentiment and undertone of the supplementary message and investigate how they influence driving speeds. According to the results of a mixed effect model, drivers reduced speeds marginally upon encountering DMS fatality text with a positive sentiment with a neutral undertone. This category had the largest associated amount of speed reduction, while messages with negative sentiment with a negative undertone had the second largest amount of speed reduction, greater than other combinations, including positive sentiment with a positive undertone.

Blockchain-Based Message Authentication Scheme for Internet of Vehicles in an Edge Computing Environment

As an important application of intelligent transportation system,Internet of Vehicles(IoV)provides great convenience for users.Users can obtain real-time traffic conditions through the IoV’s services,plan users’travel routes,and improve travel efficiency.However,in the IoV system,there are always malicious vehicle nodes publishing false information.Therefore,it is essential to ensure the legitimacy of the source.In addition,during the peak period of vehicle travel,the vehicle releases a large number of messages,and IoV authentication efficiency is prone to performance bottlenecks.Most existing authentication schemes have the problem of low authentication efficiency in the scenario.To address the above problems,this paper designs a novel reliable anonymous authentication scheme in IoV for Rush-hour Traffic.Here,our scheme uses blockchain and elliptic curve cryptography(ECC)to design authentication algorithms for message authentication between vehicles and roadside units(RSU).Additionally,we introduce the idea of edge computing into the scheme,RSU will select themost suitable vehicle as the edge computing node for message authentication.In addition,we used the ProVerif tool for Internet security protocols and applications to test its security,ensuring that it is secure under different network attacks.In the simulation experiment,we compare our scheme with other existing works.Our scheme has a significant improvement in computational overhead,authentication efficiency and packet loss rate,and is suitable for traffic scenarios with large message volume.

一种基于Message Passing的并行程序设计技术

本文首先分析介绍构造并行计算机系统的两种方法：Ｍｕｌｔｉｐｒｏｃｅｓｓｏｒｓ和Ｍｕｌｔｉｃｏｍｐｕｔｅｒｓ，然后介绍一种Ｍｕｌｔｉｃｏｍｐｕｔｅｒｓ并行计算机系统中基于ｍｅｓｓａｇｅｐａｓｓｉｎｇ的并行程序设计环境以及并行程序设计方法，它具有程序设计简单、直观等特点，易于构造程序模型，并能获得较好的加速比。

基于Message Passing的并行编程环境

在分布式并行计算机系统中，由于处理机间无共事内存，因此采用了MessagePassins方式实现处理机间的通信.文中讨论了基于MessagePassing把的并行编程环境所应具备的特点，然后介绍几种被人们普遍接受的并行编程环境.

一种基于Message Passing的并行程序设计环境

并行处理技术的发展使得高性能的并行计算机系统不断地推出，而方便、灵活的并行程序设计环境在并行计算机系统的推广应用中起着重要的作用。如何编写有效的并行程序代码以及如何将现有的串行应用程序并行化已成为并行处理的重要研究课题。

QIM digital watermarkingbased on LDPC code and messagepassingunder scalingattacks

Watermarking system based on quantization index modulation （QIM） is increasingly popular in high payload applications,but it is inherently fragile against amplitude scaling attacks.In order to resist desynchronization attacks of QIM digital watermarking,a low density parity check （LDPC） code-aided QIM watermarking algorithm is proposed,and the performance of QIM watermarking system can be improved by incorporating LDPC code with message passing estimation/detection framework.Using the theory of iterative estimation and decoding,the watermark signal is decoded by the proposed algorithm through iterative estimation of amplitude scaling parameters and decoding of watermark.The performance of the proposed algorithm is closer to the dirty paper Shannon limit than that of repetition code aided algorithm when the algorithm is attacked by the additive white Gaussian noise.For constant amplitude scaling attacks,the proposed algorithm can obtain the accurate estimation of amplitude scaling parameters.The simulation result shows that the algorithm can obtain similar performance compared to the algorithm without desynchronization.

基于Message Passing的认知无线电快速资源分配

针对多用户的OFDM认知无线电系统上行链路,提出一种基于Message Passing的分布式快速资源分配算法。该算法以认知系统总发射功率最小化为优化目标,综合考虑了认知用户对授权用户的干扰、总发射功率预算以及认知用户之间的比例公平性等约束条件,将资源分配分为子信道分配与功率分配相继2个步骤,构建资源分配的因子图,通过在节点间迭代地传递信息直至最终完成分布式的资源分配。分析和仿真结果表明,该算法在保证系统通信性能及资源分配公平性的前提下降低了系统总发射功率,并且运算效率得到了明显提升。

Efficient Recovery of Structured Sparse Signals via Approximate Message Passing with Structured Spike and Slab Prior

Due to limited volume, weight and power consumption, micro-satellite has to reduce data transmission and storage capacity by image compression when performs earth observation missions. However, the quality of images may be unsatisfied. This paper considers the problem of recovering sparse signals by exploiting their unknown sparsity pattern. To model structured sparsity, the prior correlation of the support is encoded by imposing a transformed Gaussian process on the spike and slab probabilities. Then, an efficient approximate message-passing algorithm with structured spike and slab prior is derived for posterior inference, which, combined with a fast direct method, reduces the computational complexity significantly. Further, a unified scheme is developed to learn the hyperparameters using expectation maximization(EM) and Bethe free energy optimization. Simulation results on both synthetic and real data demonstrate the superiority of the proposed algorithm.

Speech Enhancement Based on Approximate Message Passing

To overcome the limitations of conventional speech enhancement methods, such as inaccurate voice activity detector(VAD) and noise estimation, a novel speech enhancement algorithm based on the approximate message passing(AMP) is adopted. AMP exploits the difference between speech and noise sparsity to remove or mute the noise from the corrupted speech. The AMP algorithm is adopted to reconstruct the clean speech efficiently for speech enhancement. More specifically, the prior probability distribution of speech sparsity coefficient is characterized by Gaussian-model, and the hyper-parameters of the prior model are excellently learned by expectation maximization(EM) algorithm. We utilize the k-nearest neighbor(k-NN) algorithm to learn the sparsity with the fact that the speech coefficients between adjacent frames are correlated. In addition, computational simulations are used to validate the proposed algorithm, which achieves better speech enhancement performance than other four baseline methods-Wiener filtering, subspace pursuit(SP), distributed sparsity adaptive matching pursuit(DSAMP), and expectation-maximization Gaussian-model approximate message passing(EM-GAMP) under different compression ratios and a wide range of signal to noise ratios(SNRs).

Parametric message passing-based relative navigation in joint tactical information distribution system

Relative navigation is a key feature in the joint tactical information distribution system（JTIDS）.A parametric message passing algorithm based on factor graph is proposed to perform relative navigation in JTIDS.First of all,the joint posterior distribution of all the terminals＇ positions is represented by factor graph.Because of the nonlinearity between the positions and time-of-arrival（TOA） measurement,messages cannot be obtained in closed forms by directly using the sum-product algorithm on factor graph.To this end,the Euclidean norm is approximated by Taylor expansion.Then,all the messages on the factor graph can be derived in Gaussian forms,which enables the terminals to transmit means and covariances.Finally,the impact of major error sources on the navigation performance are evaluated by Monte Carlo simulations,e.g.,range measurement noise,priors of position uncertainty and velocity noise.Results show that the proposed algorithm outperforms the extended Kalman filter and cooperative extended Kalman filter in both static and mobile scenarios of the JTIDS.

Thread-Oriented Message-Passing Interface

In this paper the limitations of the standard Message Passing Interface (MPI) are analyzed, then the technique of multithreading is introduced and a stand alone LWP (light weight process) extension to MPI is implemented. Experimental results show that system overhead is considerably diminished.

Message Passing Based Detection for Orthogonal Time Frequency Space Modulation

The orthogonal time frequency space(OTFS)modulation has emerged as a promis⁃ing modulation scheme for wireless communications in high-mobility scenarios.An efficient detector is of paramount importance to harvesting the time and frequency diversities promised by OTFS.Recently,some message passing based detectors have been developed by exploiting the features of the OTFS channel matrices.In this paper,we provide an overview of some re⁃cent message passing based OTFS detectors,compare their performance,and shed some light on potential research on the design of message passing based OTFS receivers.

Hybrid simulation of q=1 high-order harmonics driven by passing energetic particles in tokamak plasmas

High-order harmonics q(ψ_(s))=1 energetic particle modes(EPMs)have been observed in toroidal plasmas experiments with neutral beam injection.To investigate these phenomena,linear properties and nonlinear dynamics of these EPMs driven by passing energetic particles(EPs)are studied via the global hybrid kinetic-magnetohydrodynamic code M3D-K.Simulation results demonstrate that passing EPs'effects on high mode-number harmonics(q(ψ_(s))=m/n=2/2,3/3,4/4)instability are more obvious than the q(ψ_(s))=1/1 mode,especially when q-profile is sufficiently flat in the core region.Furthermore,the effects of the pitch angleΛ_0 and beam ion pressure P_(hot)/P_(total)on the features of high n components are also analyzed specifically.It is found that there exists only one resonant condition for these EPMs.In the nonlinear phase,these high mode-number harmonics can induce significant energetic ions redistribution and chirping up phenomena,which differs from the classical fishbone excited by passing EPs.These discoveries are conducive to better apprehend the underlying physical mechanisms of the highorder harmonics driven by passing EPs.

注意力感知的边−节点交换图神经网络模型

提出了一种注意力感知的边-节点交换图神经网络(attention aware edge-node exchange graph neural network,AENN)模型,在图结构化数据表示框架下,使用边-节点切换卷积的图神经网络算法进行图编码,用于半监督分类和回归分析。AENN是一种通用的图编码框架,用于将图节点和边嵌入一个统一的潜在特征空间。具体地,基于原始无向图,不断切换边与节点的卷积,并在卷积过程中通过注意力机制分配不同邻居的权重,从而实现特征传播。在3个数据集上的实验研究表明,所提方法较已有方法在半监督分类和回归分析中具有明显的性能提升。