Abstract
The design of smart terminals able to detect reachable frequency bands and configure them according to the available channel state information is a major focus of current research. Two main approaches are addressed in the literature: cooperative scenario and blind methods whom transmission parameters are unknown. Blind spectrum sensing and parameters estimation (at the receiver side) may guarantee a more intensive and efficient spectrum use, a higher quality of service and more flexibility in devices self-configuration. This scenario, which can be viewed as a brick of a Cognitive Radio (CR) (Mitola, 2000) is considered throughout this chapter. We consider the more general case of Direct-Sequence (DS) spread spectrum signals in multiuser multirate CDMA systems where spreading sequences may be longer than the duration of a symbol. An easy way to view the multirate CDMA transmission is to consider the variable spreading length (VSL) technique where all users employ sequences with the same chip period. Moreover, the data rate is tied to the length of the spreading code of each user. Many researches aiming at spectrum sensing in cognitive radio context have been proposed, such as blind cyclostationary approaches (Hosseini et al., 2010), SOS approaches (Cheraghi et al., 2010), Student’s t-distribution testing problem (Shen et al., 2011). Authors proved that these methods exhibited very good performances in discriminating against noise due to their robustness to the uncertainty in noise power. Nevertheless, they could be computationally complex since they may require significantly long observation time. Several blind approaches (i.e., when the process of recovering data from multiple simultaneously transmitting users without access to any training sequences) have been addressed in the literature (Buzzi et al., 2010; Khodadad, Ganji & Mohammad, 2010; Khodadad, Ganji & Safaei, 2010; Meng et al., 2010; Yu et al., 2011; Zhang et al., 2011). However, most of them require some prior knowledge about users parameters such as signature waveform, processing gain, pseudo-noise code (for a particular group of active users) or chip rate. These parameters may be unknown in a realistic non-cooperative context. Besides, a PARAFAC based method was addressed in (Kibangou & de Almeida, 2010), but in the single user case in a no noisy environment. Furthermore, in multiuser asynchronous systems both problems of blind 6
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