有关无线数字通信中的盲源分离技术的探析中英互译.doc

//有关无线数字通信中的盲源分离技术的探析中英互译The blind source separation technology in wireless digital communication into English in the article Before the speech 虽然目前公众媒体将无线通信炒的很热，但这个领域从1897年马可尼成功演示无线电波开始，已经有超过一百年的历史。到1901年就实现了跨大西洋的无线接收，表明无线通信技术曾经有过一段快速发展时期。在之后的几十年中，众多的无线通信系统生生灭灭。Stir-fry wireless communication though the media is very hot, but in this field since Marconi successfully demonstrated radio waves in 1897, has more than one hundred years of history. By 1901 realized the transatlantic wireless receive and indicates that the wireless communication technology has a rapid development period. After several decades, many wireless communication systems have come out. 20世纪80年代以来，全球范围内移动无线通信得到了前所未有的发展，与第三代移动通信系统（3G）相比，未来移动通信系统的目标是，能在任何时间、任何地点、向任何人提供快速可靠的通信服务。因此，未来无线移动通信系统应具有高的数据传输速度、高的频谱利用率、低功耗、灵活的业务支撑能力等。但无线通信是基于电磁波在自由空间的传播来实现信息传输的。信号在无线信道中传输时，无线频率资源受限、传输衰减、多径传播引起的频域选择性衰落、多普勒频移引起的时间选择性衰落以及角度扩展引起的空间选择性衰落等都使得无线链路的传输性能差。和有线通信相比，无线通信主要由两个新的问题。一是通信行道经常是随时间变化的，二是多个用户之间常常存在干扰。无线通信技术还需要克服时变性和干扰。由于这个原因，无线通信中的信道建模以及调制编码方式都有所不同。Since the 1980 s, global mobile wireless communication got unprecedented development, and the third generation (3 g) mobile communication systems, the future mobile communication systems goal is, can at any time, any place, providing fast and reliable communications services to anyone. Therefore, the future wireless mobile communication system should have higher data transmission speed, high frequency spectrum utilization ratio, low power consumption, flexible business support ability, etc. But the spread of the wireless communication is based on the electromagnetic wave in free space to realize the information transmission. Signal transmission in wireless channel, the limited radio frequency resources, transmission attenuation, frequency selective fading caused by multipath propagation and time selective fading caused by doppler frequency shift and the Angle of extended space selective fading caused by such makes the transmission performance of the wireless link is poor. Compared with cable communication, wireless communication is mainly composed of two new problems. One is the communication vehicle is often change over time, there is often interference between multiple users. Wireless communication technology also need to overcome when degeneration and interference. For this reason, in the wireless communication channel modeling and modulation coding method is different. 1.无线数字通信中盲源分离技术分析1. The blind source separation technology in the wireless digital communication analysis 盲源分离（BSS：Blind source separation），是信号处理中一个传统而又极具挑战性的问题，BSS指仅从若干观测到的混合信号中恢复出无法直接观测的各个原始信号的过程，这里的“盲”，指源信号不可测，混合系统特性事先未知这两个方面。在科学研究和工程应用中，很多观测信号都可以看成是多个源信号的混合，所谓“鸡尾酒会”问题就是个典型的例子。其中独立分量分析ICA（Independent component analysis）是一种盲源信号分离方法，它已成为阵列信号处理和数据分析的有力工具，而BSS比ICA适用范围更宽。目前国内对盲信号分离问题的研究，在理论和应用方面取得了很大的进步，但是还有很多的问题有待进一步研究和解决。盲源分离是指在信号的理论模型和源信号无法精确获知的情况下，如何从混迭信号（观测信号）中分离出各源信号的过程。盲源分离和盲辨识是盲信号处理的两大类型。盲源分离的目的是求得源信号的最佳估计，盲辨识的目的是求得传输通道混合矩阵。盲源信号分离是一种功能强大的信号处理方法，在生物医学信号处理，阵列信号处理，语音信号识别，图像处理及移动通信等领域得到了广泛的应用。Blind source separation (BSS: Blind source separation), is a traditional in signal processing and challenging problem, BSS refers only to recover from some observed mixed-signal process cant direct observation of the original signal, the Blind, refers to the source signal is unpredictable, the hybrid system features both unknown in advance. In scientific research and engineering application, a lot of observed signals can be seen as multiple sources of mixture, the so-called cocktail problem is a typical example. Independent component analysis ICA (Independent component analysis) is a kind of blind source separation method, it has become a powerful array signal processing and data analysis tools, and BSS than the ICA is more wide application scope. The current domestic study of fanaticism, separation problem, has made great progress in theory and application, but there are still many problems remain to be further research and resolution. Blind source separation refers to the theoretical model and the source signals in the signal cant accurate know the situation, how to mix overlapping signal (signal) to isolate the source signal process. Blind source separation and blind faith is blind identification number two types. Blind source separation is a best estimate of the source signal is obtained, the purpose of blind identification of the purpose of the transport channel mixing matrix is obtained. Blind sources separation is a powerful method of signal processing in the biomedical signal processing, array signal processing, speech recognition, image processing and mobile communications and other fields has been widely used. 根据源信号在传输信道中的混合方式不同，盲源分离算法分为以下三种模型：线性瞬时混合模型、线性卷积混合模型以及非线性混合模型。According to the source signals in the transmission channel mixing in a different way, blind source separation algorithm is divided into the following three models: linear instantaneous mixing model, linear convolution mixture model and nonlinear mixed models. 1.1 线性瞬时混合盲源分离1.1 linear instantaneous mixture blind source separation 线性瞬时混合盲源分离技术是一项产生、研究最早，最为简单，理论较为完善，算法种类多的一种盲源分离技术，该技术的分离效果、分离性能会受到信噪比的影响。盲源分离理论是由鸡尾酒会效应而被人们提出的，鸡尾酒会效应指的是鸡尾酒会上，有音乐声、谈话声、脚步 声、酒杯餐具的碰撞声等，当某人的注意集中于欣赏音乐或别人的谈话，对周围的嘈杂声音充耳不闻时，若在另一处有人提到他的名字，他会立即有所反应，或者朝 说话人望去，或者注意说话人下面说的话等。该效应实际上是听觉系统的一种适应能力。当盲源分离理论提出后很快就形成了线性瞬时混合模型。线性瞬时混合盲源分离技术是对线性无记忆系统的反应，它是将N个源信号在线性瞬时取值混合后，由多个传感器进行接收的分离模型。Instantaneous linear mixture blind source separation technology is a production, research the earliest, the most simple, relatively perfect theory and algorithm of variety a blind source separation technique, separation efficiency, separation performance of the technology are influenced by the signal-to-noise ratio. Blind source separation theory is the cocktail party effect and has been put forward, the cocktail party effect refers to a cocktail party, there is the music sound, voices and footsteps, glass tableware, crash, such as when someones attention focused on the appreciate music or other peoples conversations, turned a deaf ear on the surrounding noisy sound, if anyone mentions his name in another place, he would immediately respond to, or toward the speaker, or to pay attention to the following words, etc. This effect is actually the auditory system of a kind of ability to adapt. When the blind source separation theory is raised quickly to form the linear instantaneous mixing model. Instantaneous linear mixture blind source separation technology is a response to the linear memoryless systems, it is N source signal in the linear instantaneous values after mixing, the separation model of multiple sensors to receive. 20世纪八、九十年代是盲源技术迅猛发展的时期，在1986年由法国和美国学者共同完了将两个相互独立的源信号进行混合后实现盲源分离的工作，这一工作的成功开启了盲源分离技术的发展和完善。在随后的数十年里对盲源技术的研究和创新不断加深，在基础理论的下不断有新的算法被提出和运用，但先前的算法不能够完成对两个以上源信号的分离；之后在1991年，法国学者首次将神经网络技术应用到盲源分离问题当中，为盲源分离提出了一个比较完整的数学框架。到了1995年在神经网络技术基础上盲源分离技术有了突破性的进展，一种最大化的随机梯度学习算法可以做到同时分辨出10人的语音，大大推动了盲源分离技术的发展进程。S and ninety s of the 20th century is blind source technology rapid development period, finished in 1986 by the French and American scholars mix two separate source signals for realize blind source separation, after the success of a work on the development and perfection of blind source separation technology. In subsequent decades the deepening research of blind source technology and innovation, under the basic theory of constantly have new algorithms have been proposed and applied, but the previous algorithm will not be able to complete separation of two or more source signal; Then, in 1991, French scholar first the neural network technology is applied to the problem of blind source separation, blind source separation is proposed for a more complete mathematical framework. In 1995 in blind source separation technology on the basis of neural network technique has made breakthrough progress, a maximum stochastic gradient learning algorithm can discern the voice of 10 people at the same time, greatly promotes the development of blind source separation technology. 1.2 线性卷积混合盲源分离1.2 linear convolution mixture blind source separation 相比瞬时混合盲源分离模型来说，卷积混合盲源分离模型更加复杂。在线性瞬时混合盲源分离技术不断发展应用的同时，应用中也有无法准确估计源信号的问题出现。常见的是在通信系统中的问题，通信系统中由于移动客户在使用过程中具有移动性，移动用户周围散射体会发生相对运动，或是交通工具发生的运动都会使得源信号在通信环境中出现时间延迟的现象，同时还造成信号叠加，产生多径传输。正是因为这样问题的出现，使得观测信号成为源信号与系统冲激响应的卷积，所以研究学者将信道环境抽象成为线性卷积混合盲源分离模型。线性卷积混合盲源分离模型按照其信号处理空间域的不同可分为时域、频域和子空间方法。Compared with the instantaneous mixture blind source separation model, more complicated convolution mixture blind source separation model. Linear instantaneous mixture blind source separation technology in the development application at the same time, the applications are unable to accurately estimate the source signals. Is common problem in the communication system, communication system due to the mobile customers in the use process have mobility, scattering around mobile user experience of relative movement occurs, or the traffic tool movement will make the source signal, the phenomenon of the time delay in the communication environment, at the same time also cause signal superposition, to produce multipath transmission. Because of that problem, makes observation signal source signal and the system impulse response of convolution, so study scholars abstract channel will become linear convolution mixture blind source separation model. Linear convolution mixture blind source separation model according to the different signal processing spatial domain can be divided into the time domain, frequency domain method and subspace. 1.3 非线性混合盲源分离1.3 the nonlinear mixture blind source separation 非线性混合盲源分离技术是盲源分离技术中发展、研究最晚的一项，许多理论和算法都还不算成熟和完善。在卫星移动通信系统中或是麦克风录音时，都会由于乘性噪声、放大器饱和等因素的影响造成非线性失真。为此，就要考虑非线性混合盲源分离模型。非线性混合模型按照混合形式的不同可分为交叉非线性混合、卷积后非线性混合和线性后非线性混合模型三种类型。在最近几年里非线性混合盲源分离技术受到社会各界的广泛关注，特别是后非线性混合模型。目前后非线性混合盲源分离算法中主要有参数化方法、非参数化方法、高斯化方法来抵消和补偿非线性特征。Mixed nonlinear blind source separation technology is a blind source separation technology in the development, research, one of the most late, many theories and algorithms are not mature and perfect. In satellite mobile communication system or the microphone recording, are due to the multiplicative noise and saturation amplifier nonlinear distortion caused by the influence of such factors. To this end, consider the nonlinear mixture blind source separation model. Nonlinear mixed models in accordance with the mixed form of different can be divided into nonlinear mixing, cross convolution nonlinear mixed linear and nonlinear mixed models after three types. The nonlinear mixture blind source separation technology in recent years received extensive attention of social from all walks of life, especially after the nonlinear mixed models. After the nonlinear mixture blind source separation algorithms are mainly parametric method and nonparametric method, gauss method to offset compensation and nonlinear characteristics. 2.无线通信技术中的盲源分离技术2. The blind source separation technology in the wireless communication technology 在无线通信系统中通信信号的信号特性参数复杂多变，实现盲源分离算法主要要依据高阶累积量和峭度两类参数。如图一所示，这是几个常见的通信信号高阶累积量。Communication signals in wireless communication system of signal characteristic parameters is complicated, mainly to realize the blind source separation algorithm based on higher-order cumulant and kurtosis parameter. As shown in figure a, this is a few common signal high-order cumulants. 在所有的通信系统中，接收设备处总是会出现白色或是有色的高斯噪声，以高阶累积量为准则的盲源分离技术在处理这一问题时稳定性较强，更重要的是对不可忽略的加性高斯白噪声分离算法同时适用。因此，由高阶累积量为准则的盲源分离算法在通信系统中优势明显。In all of the communication system, receiving equipment place will always appear white or colored gaussian noise, by the high order cumulant of the blind source separation technology in addressing the problem of the stability