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.

No abstract

Abstract-In this letter, an overview of reported measurements and modeling of the ultra wide band (UWB) indoor wireless channel is presented. An introduction to UWB technology and UWB channels is provided. Different UWB channel sounding techniques are discussed and approaches for the modeling of the UWB channel are reviewed. The available indoor UWB channel measurement results are consulted and accordingly, the major UWB channel parameters are presented and compared to those of narrowband systems. The novelty of this work is the gathering of different UWB channel parameters, analysis, and comparison. Added with the influence of UWB antenna in channel-modeling as well as the frequency-dependency of the channel parameters, leading to a conclusion on the UWB radio channel modeling.Index Terms-Conventional narrowband and wide-band systems (CNWS), inverse Fourier transform (IFT), time decay constant (TDC), ultra wide band (UWB) indoor wireless channel.

Spectrum Sensing is an important functionality of Cognitive Radio (CR). Accuracy and speed of estimation are the key indicators to select the appropriate spectrum sensing technique. Conventional spectrum estimation techniques which are based on Short Time Fourier Transform (STFT) suffer from familiar problems such as low frequency resolution, high variance of estimated power spectrum and high side lobes/leakages. Methods such as Multi Taper Spectrum Estimation successfully alleviate these infarctions but exact a high price in terms of complexity. On these accounts, it appears that the filter bank spectrum estimation formulated by F. Boroujeny and wavelet based spectrum estimates are the most promising and pragmatic approaches for CR applications. This article surveys and appraises available literature on various spectrum sensing techniques and discusses spectrum sensing as a key element of CR system design.978-1-4244-4583-7/09/$25.00

No abstract