A Review of Wavelets for Digital Wireless Communication

Wavelets have been favorably applied in almost all aspects of digital wireless communication systems including data compression, source and channel coding, signal denoising, channel modeling and design of transceivers. The main property of wavelets in these applications is in their flexibility and ability to characterize signals accurately. In this paper recent trends and developments in the use of wavelets in wireless communications are reviewed. Major applications of wavelets in wireless channel modeling, interference mitigation, denoising, OFDM modulation, multiple access, Ultra Wideband communications, cognitive radio and wireless networks are surveyed. The confluence of information and communication technologies and the possibility of ubiquitous connectivity have posed a challenge to developing technologies and architectures capable of handling large volumes of data under severe resource constraints such as power and bandwidth. Wavelets are uniquely qualified to address this challenge. The flexibility and adaptation provided by wavelets have made wavelet technology a strong candidate for future wireless communication. Madan Kumar Lakshmanan was born in Chennai, India, in 1979. He received the B.E. (with distinction) in electrical engineering from the University of Madras, Chennai, India, in 2000. He joined the Indian Software firm, Polaris Software Labs Ltd., in 2000 where he wrote software for Telecommunication applications. At Polaris, he was awarded the “On The Spot Of Excellence Award” for his efforts. In 2003, he moved to the Indian Institute of Technology-Madras, to develop and establish a wireless communications network for rural connectivity. In 2004, he was awarded the Royal Dutch/Shell Chevning scholarship to pursue a Master degree in Telecommunications at the Delft University of Technology (TUDelft). At TUDelft he is affiliated to the International Research Center for Telecommunications-Transmission and Radar (IRCTR) where he is undertaking research in the field of wavelets applications in Wireless Communications. Homayoun Nikookar received his Ph.D. in Electrical Engineering from Delft University of Technology (TUDelft), The Netherlands, in 1995. From 1995 to 1998 he was a postdoc researcher at the International Research Center for Telecommunications-Transmission and Radar, TUDelft, where since 1999 he has been an Assistant Professor. Dr. Nikookar has done research on different areas of wireless communications, including wireless channel modeling, UWB, MIMO, multicarrier transmission, Wavelet-based OFDM and CDMA. He is a senior member of the IEEE.     

基于软件无线电的突发模式8DPSK的全数字化实现

提出了一种软件无线电中频收发机的结构和突发模式 8DPSK解调的实现框架 ,在 8DPSK解调时采用了前向初始参数估计算法 ,并证实了该算法的可行性。     

Enhancing cognitive radio systems with robust reasoning

Cognitive radio systems dynamically reconfigure the algorithms and parameters they use, in order to adapt to the changing environment conditions. However, reaching proper reconfiguration decisions presupposes a way of knowing, with high enough assurance, the capabilities of the alternate configurations, especially in terms of achievable transmission capacity and coverage. The present paper addresses this problem, firstly, by specifying a complete process for extracting estimations of the capabilities of candidate configurations, in terms of transmission capacity and coverage, and, secondly, by enhancing these estimations with the employment of a machine learning technique. The technique is based on the use of Bayesian Networks, in conjunction with an effective learning and adaptation strategy, and aims at extracting and exploiting knowledge and experience, in order to reach robust (i.e. stable and reliable) estimations of the configurations' capabilities. Comprehensive results of the proposed method are presented, in order to validate its functionality. Copyright © 2007 John Wiley & Sons, Ltd.     

Electronic Emissions Security: Danger in the Air

Most organizations have measures to protect their network infrastructure from intruders. With the growth AND AVAILABILITY of wireless, some intruders now are aiming their attacks there. The potential for damage from these types of attacks is significant due to their nature. However, there is another type of wireless attack on organizational resources that also poses a significant vulnerability. That is electromagnetic radiation, also called radio frequency emissions (RFE), from unprotected systems and networks.     

Method of increasing the output signal-to-noise ratio in passive multi-element antenna arrays

A method of processing complex signals in passive multi-element antenna arrays based on an analysis of the natural values of the correlation matrix of the signal is considered. By means of the method it is possible to substantially increase the output signal-to-noise ratio. An iterational process by means of which optimal estimators of both the signal and the amplitude-phase distribution may be obtained, is proposed. Theoretical estimators of the efficiency of the method are given. It is proved that, in terms of the efficiency, the approach considered in the article comes close to the technique of matched filtration. Results of statistical modeling that confirm the statistical results are presented.     

无线电引信贮存可靠性研究

研究了无线电引信电子系统的贮存可靠性问题，深入分析了无线电引信的电子系统的失效模式和失效规律，探讨了用引战配合效率的改变来描述无线电引信的失效规律的方法，并提出了预防无线电引信失效的措施。     

数字微波无线通信系统中的中频自适应均衡器

在数字微波无线通信系统中，由于多径衰落引起码间干扰，使系统性能恶化，必须采用抗多径衰落的措施．中频频域均衡器（ＩＦＥ）由于结构简单而且经济，在衰落不十分严重的情况下性能良好，因而在数字微波系统中被广泛采用．本文比较了几种常用的ＩＦＥ，并着重对自适应谐振武中频均衡器的两种调节方法作了研究．模拟计算得到的ｓｉｇｎａｔｕｒｅ曲线表明，这种均衡器对非最小相位（ＭＭＰ）信道的传输性能有很大的改进，且两种调节法可达到相近的结果，如选择其中较简单的调节法，可以简化硬件结构．     

关于集群系统中无线信道数的确定

准确估算集群系统所需无线信道数是工程设计中的一个重要的关键环节。本文从讨论系统业务、系统话务量出发,提出了一种正确使用爱尔兰—B公式(或巴姆表)确定集群系统中无线信道数的新方法。继而,较为详细地定量分析了集群方式对系统话务量的影响。最后,针对实际工程设计,推荐了一个集群系统容量计算的经验公式。     

SDH微波接力通信系统差错性能指标的分配和预测方法

本文根据ＩＴＵ－ＴＧ．８２６建议和ＩＴＵ－Ｒ有关文件，分析了Ｇ．８２６指标在ＳＤＨ微波接力通信系统中的分配方法；提出了ＳＤＨ微波接力通信系统差错性能指标的预测方法；介绍了在ＳＤＨ微波接力通信系统中主要的抗衰落措施及其对差错性能指标的改善效果。     

无线通信技术在沙漠油田安全生产中的应用

介绍无线通信技术在沙漠油田安全生产中的应用。