高速衰落多径信道中时间/尺度分集接收机的分析

在高速衰落多径信道中,传统的Ｒａｋｅ接收机的性能会大大降低。本文基于自子波变换和时间、尺度分辨率的概念,从理论和仿真实验两方面对信道建模和时间／尺度Ｒａｋｅ接收机进行了分析,并与传统的Ｒａｋｅ接收机进行了比较,结果表明时间／尺度联合分集能有效地克服高速衰落多径信道的影响。     

基于数字AGC的控制算法

提出了一种新的数字自动增益控制(Automatic Gain Control,AGC)控制算法,这种算法弥补了AGC芯片控制范围和控制精度不满足工程要求的缺陷,解决了其他算法没有处理的问题。阐述了输入信号能量提取算法、输入信号的能量滤波算法以及控制范围和控制精度调整算法,给出了基于新算法的AGC控制过程框图,分析了输入信号能量提取算法的性能和原理,对能量滤波算法进行了仿真,并对控制范围和控制精度算法进行了设备测试和验证。     

GPS接收机多径抑制算法研究

研究了窄相关、多径估计延迟锁相环算法(MEDLL)和基于斜率估计(ELS)的GPS接收机多径抑制算法,重点研究了ELS算法,该算法可以在一定的预相关带宽的前提下,通过对相关峰两边的斜率进行估计,达到抑制多径造成的跟踪误差的效果。仿真结果表明,ELS的算法在性能上比窄相关技术更好,接近于MEDLL算法。该算法相对于窄相关技术资源规模增加不大,比MEDLL算法资源规模和计算量都要小很多,易于在硬件上实时实现。     

Load balancing multipath routing protocol for mass remote sensing data downlink in LEO satellite network

LEO satellite networks can provide seamless real-time data communication for all kinds of users,which developed rapidly in recent years.At the mean time,the massive payload data down-link system of space data sources,such as remote sensing satellites,still make use of traditional storage and forward mode.The real-time performance of space mission data will be improved effectively,if such satellites are connected to LEO satellite networks equipped with inter satellite links.However,it is necessary to design a specialized satellite network load balancing routing algorithm.Satellite parallel edge-disjoint multipath routing protocol (SPEMR) was designed for remote sensing satellite real-time down-link applications.OPNET simulation results indicate that the performance degradation index(DI) of the multipath scheme implemented by SPEMR is 0.32,which is only 32% of the TLR and 21% of the traditional DSP scheme.It is demonstrated that SPEMR has the better capability of transmitting massive data in real time.     

迭代硬判决反馈的LDPC级联MDPSK解调译码算法

该文给出了瑞利衰落信道条件下LDPC级联MDPSK的接收机结构,研究了在不考虑信道状态条件下基于硬判决反馈的迭代检测译码算法,该算法相对于传统的差分解调和译码,复杂度几乎没有增加。仿真结果表明,这种方法在迭代4次的情况下,在误比特率为10-4时与传统的解调方法相比,可以提供2.2dB的增益。     

无线通信中的空时分组码

空时分组码技术结合信道编码、调制和天线分集技术,当发送天线一定时,他的解码复杂度正比于发送速率,在3G标准中,该技术有着重要的地位。对空时分组码及相关知识进行了介绍,并对可变速率的空时分组码设计进行了探讨,最后展望了空时分组码技术的应用前景。     

数字视音频传输中的光纤通道网络技术

随着数字技术的发展，数字视音频数据量迅速增加，这就需要一种新的视音频网络技术来提高数字视音频文件传输的速度，数字视音频的光纤通道网络技术解决了这个难题。主要介绍数字视音频的光纤通道网络技术的性能、优势以及网络环境建设。     

浅谈有线电视系统增补频道

有线电视系统采用大量的增补频道,结合实际应用分析增补频道的使用情况,介绍增补频道在有线电视系统传输频带中的划分和范围,以及新老型号电视接收机增补频道的设置情况,详细阐述利用老型号电视接收机接收增补频道节目的方法。     

An Artificial Autonomic Nervous System That Implements Heart and Pupil as Controlled by Artificial Sympathetic and Parasympathetic Nerves

The autonomic nervous system maintains homeostasis in organisms through complex neural pathways and responds adaptively to changes in the external and internal environment. The fabrication of an artificial autonomic nervous system is reported that replicates combined effects of sympathetic and parasympathetic nerves on cardiac activity and pupillary control, to mimic the regulation of autonomic nervous system to external changes. The artificial autonomic nerve-controlled pupil contraction and relaxation, modulating the rate of heartbeats for normal cardiac rhythm and arrhythmia as reflected by blink rates of a signal indicator. These functions are switched by using a parallel-channeled synaptic transistor with a special n-i-p heterostructure that has a 2D h-BN insulator in the middle to provide barrier against ion injection into the 2D MoS₂ bottom n-channel and enable short-term plasticity as induced by acetylcholine, and the electrochemical doping reaction occurred at the P3HT nanowire p-channels on top to enable relatively long-term plasticity as induced by noradrenaline. Low-energy consumption down to femtojoule and an ultrahigh paired-pulse facilitation index up to ≈455% are demonstrated. An artificial neural network based on device characteristics achieves a high recognition accuracy for electrocardiogram patterns. This study extends insights into artificial nerves-inspired biological signal processing and recognition.     

Room-Temperature-Processable Highly Reliable Resistive Switching Memory with Reconfigurability for Neuromorphic Computing and Ultrasonic Tissue Classification

Reversible metal-filamentary mechanism has been widely investigated to design an analog resistive switching memory (RSM) for neuromorphic hardware-implementation. However, uncontrollable filament-formation, inducing its reliability issues, has been a fundamental challenge. Here, an analog RSM with 3D ion transport channels that can provide unprecedentedly high reliability and robustness is demonstrated. This architecture is realized by a laser-assisted photo-thermochemical process, compatible with the back-end-of-line process and even applicable to a flexible format. These superior characteristics also lead to the proposal of a practical adaptive learning rule for hardware neural networks that can significantly simplify the voltage pulse application methodology even with high computing accuracy. A neural network, which can perform the biological tissue classification task using the ultrasound signals, is designed, and the simulation results confirm that this practical adaptive learning rule is efficient enough to classify these weak and complicated signals with high accuracy (97%). Furthermore, the proposed RSM can work as a diffusive-memristor at the opposite voltage polarity, exhibiting extremely stable threshold switching characteristics. In this mode, several crucial operations in biological nervous systems, such as Ca²⁺ dynamics and nonlinear integrate-and-fire functions of neurons, are successfully emulated. This reconfigurability is also exceedingly beneficial for decreasing the complexity of systems—requiring both drift- and diffusive-memristors.