Open AccessDesigning non‐contiguous orthogonal frequency division multiplexing transceiver based on wavelet transform and removable cyclic prefix for spectrum sharing in cognitive radio systems
Author(s) -
Shahbaztabar Damoon,
Farrokhi Hamid
Publication year - 2014
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2013.0982
Subject(s) - cyclic prefix , orthogonal frequency division multiplexing , cognitive radio , computer science , wavelet , algorithm , fast wavelet transform , wavelet transform , electronic engineering , interference (communication) , bit error rate , filter (signal processing) , equalization (audio) , intersymbol interference , telecommunications , mathematics , channel (broadcasting) , discrete wavelet transform , artificial intelligence , engineering , wireless , computer vision
Non‐contiguous orthogonal frequency division multiplexing (NC‐OFDM) technique has been proposed in cognitive radio literature in which the Fourier transform is used to provide orthogonality between subcarriers and a cyclic prefix (CP) with temporal length greater than channel delay spread is added to each NC‐OFDM symbol to mitigate intersymbol interference. Using CP, however, degrades spectrum efficiency since it does not carry useful information. Besides, in traditional NC‐OFDM‐based cognitive radio systems, CP is an effective source of interference with adjacent primary users. To cope with these issues, a cognitive radio system based on wavelet transform and NC‐OFDM is proposed. Wavelets have appropriate localisation, limited length and orthogonality both in time and frequency domains. Analysis of signal‐to‐noise ratio (SNR) show that the SNR gain increases when the number of nullified subcarriers assigned to the secondary users is increased. Also, simulation results of the proposed scheme indicate that the nullifying process improves the system performance in terms of bit error rate. To select the optimum wavelet filter order, the effect of filter order in orthogonal wavelet families is also investigated. Simulation results show that a wavelet transform with a lower filter order should be used.