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.

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。

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。

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.

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.

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.

基于CGA的MPI程序分支覆盖测试套件生成

针对程序的分支覆盖测试,元启发式搜索技术已经被广泛应用于测试数据生成中。然而,当前的研究成果主要适用于串行程序。因此,为覆盖消息传递接口(Message Passing Interface,MPI)程序的分支,该文研究基于协同进化遗传算法(Co-evolutionary Genetic Algorithm,CGA)的测试套件生成方法(简称为:CGA生成法),该方法具有不受不可行分支影响的优势。首先,基于收集覆盖信息的探针,定义最小归一化分支距离,并以此设计出相应的适应度值函数;然后,使用CGA生成进化个体,并基于设计的适应度值函数,计算这些个体的适应值;最后,基于计算的适应值,选择子种群中代表个体,以构成合作种群。所提CGA生成法应用于7个基准MPI程序,并与其他多种方法进行比较。实验结果表明,CGA生成法的覆盖率通常高于其他搜索算法。

Analysis of MP Message Communication in English Majors by Winmax2000a

Mobile phone(MP in the following) message is used routinely to communicate, yet the discourse analysis of it is relatively undeveloped. This new communication channel merits detailed discourse analysis, especially the interaction differences among phone users. Using discourse analyze software Winmax2000 a to analyze the interaction code, this paper tries to shed light on the unique features of MP message communication and writing proficiency of English majors.

MPI:大有希望的massage_passing标准

message-passing是一个被广泛应用的并行计算模型,但至今,无论从语法或语义上message-Passing都还没有形成一个标准.并行计算机厂商在提供标准串行语言的同时,提供了各自不同的专有message一passing库,并行程序设计难免依赖于具体的系统和应用,这既限制了可移植性,也限制了听取用户对某些不易获得或对当前的应用不合适的系统的意见。没有一个标准,厂商们非常自然地把他们的专有库的优点视为有竟争力的优势,更加着力与众不同(因而不可移植)。为了应付可移植问题,研究团体已经开发了许多库来收集其它库之间的不同点.

An MPI parallel DEM-IMB-LBM framework for simulating fluid-solid interaction problems

The high-resolution DEM-IMB-LBM model can accurately describe pore-scale fluid-solid interactions,but its potential for use in geotechnical engineering analysis has not been fully unleashed due to its prohibitive computational costs.To overcome this limitation,a message passing interface(MPI)parallel DEM-IMB-LBM framework is proposed aimed at enhancing computation efficiency.This framework utilises a static domain decomposition scheme,with the entire computation domain being decomposed into multiple subdomains according to predefined processors.A detailed parallel strategy is employed for both contact detection and hydrodynamic force calculation.In particular,a particle ID re-numbering scheme is proposed to handle particle transitions across sub-domain interfaces.Two benchmarks are conducted to validate the accuracy and overall performance of the proposed framework.Subsequently,the framework is applied to simulate scenarios involving multi-particle sedimentation and submarine landslides.The numerical examples effectively demonstrate the robustness and applicability of the MPI parallel DEM-IMB-LBM framework.

基于MPI的鲲鹏CPU核间通信研究

核间通信延时是影响高性能计算系统整体运行效率的重要因素.国产鲲鹏CPU在高性能计算领域应用日益广泛,针对鲲鹏CPU的缓存架构及多核间接口互联进行分析,研究影响鲲鹏CPU核间通信延时的因素.在消息传递接口(MPI)环境下进行节点内核间通信实验,对包括跨三级缓存、跨物理CPU通信等不同模式下通信延时进行对比,发现通信数据包大于500 KB后,跨L3 Cache TAG的通信延时反优于共享L3 Cache TAG的通信延时.针对通信数据包在64 KB大小时的通信延迟异常,分析得出是MPI的Eager模式和Rendezvous模式的默认切换阈值所造成.对这两种模式进行实验对比,验证不同大小的通信数据包在不同模式下和跨核通信时的延时特征,Eager模式更适合低延时的小消息发送.在实际应用中可根据通信数据包大小调整两种模式的默认切换阈值,以达到更好的传输效果.实验结果表明由于鲲鹏CPU存在复杂的多核结构,在并行计算程序设计时可以进行针对性优化,以提升程序的运行效率.

基于GA-MP的低复杂度OTFS检测算法

针对正交时频空(Orthogonal Time Frequency Space,OTFS)通信系统信号检测复杂度高的问题,提出一种改进的高斯近似消息传递(Gaussian Approximate Message Passing,GA-MP)检测算法。依据最大后验概率检测准则,对发送信号及隐变量进行逐符号高斯近似,基于置信传播算法与联合因子图进行消息传递,用边缘后验概率替代GA-MP中的外部信息以减少运算量,结合阻尼因子提升收敛速度,同时引入概率阈值减少后续更新的节点数,从而使运算复杂度得到有效降低。实验结果表明,改进后的GA-MP算法在保证误码率性能的前提下具有更低的复杂度。

Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed memorysystems.However, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.

复杂地形环境下基于GAMP-STAP的低空风切变风速估计方法

针对机载气象雷达在复杂的地形环境下探测低空风切变时,地杂波呈现非均匀特征和难以获取足够的独立同分布(IID)样本,导致空时自适应处理(STAP)杂波抑制性能变差,使得风切变风速估计不准的问题。该文基于杂波信号稀疏特性,提出一种广义近似消息传递(GAMP)STAP方法,GAMP-STAP仅利用少量的样本在复杂地形环境下实现了风速较准确的估计。该方法首先利用杂波脊的先验信息构造稀疏字典,然后在贝叶斯框架下利用GAMP算法估计杂波幅度,恢复杂波功率谱,进而计算杂波协方差矩阵,最后构造STAP滤波器实现杂波抑制以及风切变风速估计。后续实验仿真结果证明了该方法的有效性。

基于OAMP算法辅助稀疏连接神经网络的MIMO信号检测

最大似然检测(Maximum likelihood detection,ML)是传统多输入多输出(Multi-input Multi-output,MIMO)信号检测中的最优算法,但是受到天线数量、收发天线比例以及调制信号的约束,致使其仅适用于天线数量少、天线比例较低且调制信号阶数较低的场景。作为一种新型的解决方案,目前基于深度学习(DL)的信号检测算法得到了广泛关注,但同样存在收发天线规模相近时检测性能恶化问题。该文将正交近似消息传递(OAMP)算法与稀疏连接神经网络(ScNet)结合成为可训练的网络结构,提出一种新的适用于MIMO系统上行链路的信号检测算法,称作ScNet-OAMP。该算法通过神经网络提供精确的信号传输参数初始解,改善OAMP过程的线性估计和非线性估计,由此增强其降噪能力,达到提高检测精度的目的,相比于ScNet和OAMP,其能够在同等实验参数下获得最佳检测性能。实验结果表明,此算法适用于QPSK、4QAM及16QAM等不同调制信号,能够处理不同比例收发天线及数量规模的系统配置,尤其是在收发天线数量相近的情况下亦能表现出较好的性能,并且在10-3误码率上有至少0.5 dB,甚至2.2 dB以上的性能增益。