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.

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

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In this paper we demonstrate the operation of a Wavelet Packet based multi-carrier modulation (WP-MCM) scheme in the context of Cognitive Radio. The wavelet packets are derived from multistage tree-structured paraunitary filter banks. The emphasis is on the design and development of maximally frequency selective wavelets derived from a modified Remez exchange algorithm. To enable the WP-MCM cognitive radio system to co-exist with other licensed users a common spectrum pool is maintained and the WP-MCM transmission waveform characteristics are shaped to communicate in the idle time-frequency gaps of the licensed user. This is achieved by dynamically deactivating wavelet packet carriers in and near the region of the licensed user spectrum. Through simulation results, we demonstrate the efficacy of the proposed wavelet packet based mechanism in seamlessly cohabiting with licensed users. The Bit Error rate (BER) performance is shown to be comparable, and even at times better, to conventional Fourier based OFDM system.