LDPC译码器信道似然比信息存储模块优化设计

以CCSDS(太空数据系统咨询委员会)标准中1/2码率的LDPC码为例,分析了低密度奇偶校验码(LDPC)译码算法的特点,提出了在译码器的FPGA实现中采用乒乓操作的设计方法,优化译码器信道似然比信息存储模块结构,交替接收两帧数据,使译码器不间断地工作,提高了硬件资源利用率,使译码器的吞吐量增加一倍.     

基于信道分段平滑的外辐射源雷达非平稳杂波抑制方法

复杂电磁环境下,外辐射源雷达中多径杂波可能具备非平稳的跳变特性。该文针对这种跳变型非平稳杂波,结合辐射源信号的正交频分复用(OFDM)调制特性,提出一种基于信道分段平滑的杂波抑制方法。首先建立了跳变杂波的时域信号模型,然后结合OFDM信号结构将其变换到子载波域,接着在子载波域对各OFDM符号进行信道估计与分段平滑,最后利用该信道平滑值和对应段的参考信号抑制非平稳杂波。仿真和实测数据表明,该文方法能够有效抑制跳变型的非平稳杂波。

     

基于OFDM技术的无线通信系统仿真与分析

正交频分复用（OFDM）能够有效地对抗频率选择性衰落,插入循环前缀作为保护间隔可以消除符号间干扰,而采用信道估计能够很好地跟踪无线信道的时变特性,从而减弱信道对系统的影响。文章首先阐述了OFDM系统基本模型,并给出OFDM通信系统仿真模型。在频率选择性信道下用Matlab仿真软件完成对OFDM系统发送、信道、接收等部分以及循环前缀与信道估计关键技术的设计,结合计算机仿真重点研究了循环前缀及信道估计对系统误码率性能的影响,得出了采用循环前缀和信道估计技术可以显著地提高系统性能。     

Capacity and SER Analysis of MIMO MRC Systems in an Interference-Limited Environment

The effect of co-channel interference (CCI) is considered in multiple-input multiple-output (MIMO) systems employing maximal ratio combining (MRC) under independent and identically distributed Rayleigh fading. Closed-form capacity and symbol error rate expressions are presented to evaluate the performance without any numerical integrations or statistical simulations. The analytical results are compared with Monte Carlo simulations and the good agreement is obtained.

低轨星座卫星通信系统中多业务条件下的非充分保证切换策略

该文提出了一种适用于低轨星座卫星通信系统多业务条件下的非充分保证切换策略。该策略在小于一个小区最大驻留时间的时间间隔内为到达小区的呼叫安排和预定信道,在呼叫结束环节作为补充策略对存在切换失败风险的信道进行调整。提出了策略在多业务条件下具体的实施方法,根据实时的切换呼叫性能调整策略的非充分程度。通过仿真,分析比较了不同程度非充分保证切换策略的QoS性能,验证了动态自适应调整非充分程度值的IGH策略的有效性。仿真结果表明,相对于保证切换策略,新策略以存在微小切换失败概率为代价,换取了新呼叫阻塞概率的显著降低,是一种适用于多业务低轨卫星通信系统的信道分配策略。     

MIMO-OFDM系统中一种链式加权LS信道估计算法

该文对多输入多输出正交频分复用系统中的信道估计进行研究,提出了一种链式加权LS信道估计算法。该算法基于频域正交循环导频序列,首先采用LS算法获得信道响应初始估值,然后对不同时刻的信道初值进行链式加权改善信道估值。由于循环导频结构保证了任何发射天线在训练周期内所有载波位置都有导频符号可供参考,该算法能够有效地抑制载波边界效应,提高信道估计的精度;同时它不需要信道先验信息以及矩阵求逆运算,因而实现简单。     

Global attention retinex network for low light image enhancement

Most low-light image enhancement methods only adjust the brightness, contrast and noise reduction of low-light images, making it difficult to recover the lost information in darker areas of the image, and even cause color distortion and blurring. To solve the above problems, a global attention-based Retinex network (GARN) for low-light image enhancement is proposed in this paper. We propose a novel global attention module which computes multiple dimensional information in the channel attention module to help facilitate inference learning. Then the global attention module is embedded into different layers of the network to extract richer shallow texture features and deep semantic features. This means that the rich features are more conducive to learning the mapping relationship between low-light images to normal-light images, so that the detail recovery of dark regions is enhanced in low-light images. We also collected a low/normal light image dataset with multiple scenes, in which the images paired as training set can succeed to be applied to low-light image enhancement under different lighting conditions. Experimental results on publicly available datasets show that our method has better effectiveness and generality than the state-of-the-art methods in terms of evaluations metrics such as PSNR, SSIM, NIQE, Entropy.     

Addition of phytochemical-rich plant extracts mitigate the antimicrobial activity of essential oil/wine mixtures against Escherichia coli O157:H7 but not against Salmonella enterica

Marinades for preparing raw meats for cooking are frequently made of wine and herbs. We simulated several formulations of potential antimicrobial marinades with these components and other food compatible/food derived extracts. Red wine formulations containing essential oils from oregano or thyme, or their primary active components carvacrol and thymol, respectively, and a mixture of plant extract powders from phytochemical-rich apple skin, green tea, and olive, were evaluated for inhibitory activity against the foodborne pathogens Escherichia coli O157:H7 and Salmonella enterica. Red wine alone exhibited low activity, as did the plant extract suspended in the wine. Surprisingly, the high activity of oregano or thyme essential oils in red wine was reduced in E. coli, but not in Salmonella, by addition of the plant extract. This study shows that essential oils in red wine can be an effective antimicrobial in food, however the possibility exists that phytochemicals, added to the treatment solution or natively present in the food itself, could adversely impact the antimicrobial activity and should be addressed with future studies.     

Performance evaluation of an adaptive GSM receiver with frequency-selective fading and adjacent- and co-channel interference

This study represents the sequel and conclusion of a previous one already published in this Journal a few issues ago.¹ In that article, we tackled the problem of evaluating theoretically the performance of an adaptive MLSE receiver for MSK signals on a frequency-selective stationary radio propagation channel, and we validated the theoretical findings (in the form of upper and lower bounds to the BER of the receiver) by means of computer simulations. In the present paper, we report on the performance of the very same scheme of channel-estimator-plus-Viterbi-equalizer receiver for mobile communications in a more realistic operating environment. In particular, we completely encompass here the groupe spécial mobile (GSM) transmission format, based on the Gaussian minimum shift keying (GMSK) modulation scheme and on narrowband time-division multiple access (TDMA) transmission. Also, we remove the assumption of a time-invariant propagation channel, assuming the recommended standard GSM channels as benchmark transmission conditions. Finally, with the aid of extensive computer simulations, we analyse the sensitivity of the MLSE receiver to unwanted co-channel and adjacent-channel interference coming from other users of the mobile cellular GSM system.     

一种基于神经网络的矢量量化零冗余度信道编码方法

本文提出一种新的基于神经网络的矢量量化零冗余度信道编码方法,该方法能有效地降低矢量量化编码系统在有噪信道下的平均失真。