Inclusion of statistical knowledge of the primary user (PU) channel usage had shown to be beneficial in dynamic\nspectrum access. Motivated by this fact, this paper investigated the importance of collecting and using statistics on\nneighboring secondary users (SUs) in selecting channels in addition to the knowledge of PU channel usage. The\npaper assumed that PU traffic characteristics of the channels are included in the radio environment map in the form of\nprobabilistic suffix trees, which is a sequence predictor based on Markov property. In the proposed method, an\nintelligent sequence hopping-based common control channel and a carrier sense multiple access (CSMA)/collision\navoidance (CA)-based medium access control (MAC) protocol were introduced. As shown in the paper, selecting\nchannels using statistics of both the neighboring SUs and PUs reduced the number of packet collisions compared to a\nscheme which only uses PU statistics. Furthermore, the simulation results showed that the scheme proposed had\nbetter throughput performance with respect to both the random channel selection scheme and the scheme which\nonly uses PU statistics while having less training complexity
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