Ultra-wideband (UWB) radio is a fast emerging technology with many unique attractive features that promotes major advances in wireless communications, networking, radar, imaging, and positioning systems. Research in UWB is still in its infancy stages, offering limited resources in handling the challenges facing the UWB communications. Understanding the unique properties and challenges of UWB communications as well as its application in competent signal processing techniques are vital in conquering the obstacles towards developing exciting UWB applications. UWB research and development has to cope with the challenges that limit their performance, capacity, throughput, network flexibility, implementation complexity, and cost. This tutorial focuses on UWB wireless communications at the physical layer. It overviews the state-of-the-art UWB in channel modeling, transmitters, and receivers of UWB radios, and outlines the research directions and challenges that needs to be overcome. Since a signal processing expertise is expected to have major impact in research and development of UWB systems, emphasis is placed on the DSP aspects.

Ultra-wideband communications: an idea whose time has come

Recent changes in how people consume multimedia services are causing an explosive increase in mobile traffic. With more and more people using wireless networks, the demand for the ultra-fast wireless communications systems is increasing. To date, this demand has been accommodated with advanced modulation schemes and signal-processing technologies at microwave frequencies. However, without increasing the carrier frequencies for more spectral resources, it may be quite difficult to keep up with the needs of users. Although there are several alternative bands, recent advances in terahertz-wave (THz-wave) technologies have attracted attention due to the huge bandwidth of THz waves and its potential for use in wireless communications. The frequency band of 275 ~ 3000 GHz , which has not been allocated for specific uses yet, is especially of interest for future wireless systems with data rates of 10 Gb/s or higher. Although THz communications is still in a very early stage of development, there have been lots of reports that show its potential. In this review, we will examine the current progress of THz-wave technologies related to communications applications and discuss some issues that need to be considered for the future of THz communications.

Present and Future of Terahertz Communications

A novel microstrip-line ultra-wideband (UWB) bandpass filter is proposed and implemented using a multiple-mode resonator (MMR), aiming at transmitting the signals in the whole UWB passband of 3.1-10.6GHz. In the design, the first three resonant frequencies of this MMR are properly adjusted to be placed quasiequally within the UWB. Then, the parallel-coupled lines at the two sides are longitudinally stretched so as to raise the frequency-dispersive coupling degree with the coupling peak near the center of the UWB. After optimization of this filter, a good UWB bandpass behavior with five transmission poles is theoretically realized and experimentally confirmed. Within the whole UWB passband, the return loss is found higher than 10dB, and the group delay variation is less than 0.23ns.

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Ultra-wideband (UWB) bandpass filters using multiple-mode resonator

An ultrawideband 3.1-10.6-GHz low-noise amplifier employing an input three-section band-pass Chebyshev filter is presented. Fabricated in a 0.18-/spl mu/m CMOS process, the IC prototype achieves a power gain of 9.3 dB with an input match of -10 dB over the band, a minimum noise figure of 4 dB, and an IIP3 of -6.7 dBm while consuming 9 mW.

An ultrawideband CMOS low-noise amplifier for 3.1-10.6-GHz wireless receivers

Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002–2013 of machine learning methods that were used to address common issues in WSNs. The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.

https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=3963&context=sis_research

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

The recent FCC frequency allocation for UWB has generated a lot of interest in UWB technologies. There is 7,500 MHz of spectrum for unlicensed use. The main limitations are provided by the low-power spectral density and by the fact that the transmit signal must occupy at least 500 MHz at whole times. IEEE 802.15.3a is being developed for high-bit-rate PAN applications, and UWB is the most promising technology to support the stringent requirements: 110, 200, and 480 Mb/s. Two UWB multiband systems, frequency hopping and Spectral Keying, have been described in this article. Both systems meet the stringent requirements provided by IEEE 802.15.

G.D. Rogerson

Papers

Ultra-wideband wireless systems