Tham khảo tài liệu 'recent advances in wireless communications and networks part 6', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 140 Recent Advances in Wireless Communications and Networks called spectrum holes or white spaces. If these bands are further used by a licensed user the cognitive radio device has the alternative of either moving to another spectrum hoe or staying in the same band but altering its transmission power lever or modulation scheme in order to avoid the interference. Hence it is clear that an important requirement of any cognitive radio network is the ability to sense such spectrum holes. As the most recent literature suggests right now Akyildiz et al. 2008 Haykin et al. 2009 the most efficient way to detect spectrum holes is to detect the primary users that are receiving data within the communication range of a cognitive radio user. This approach is called transmitter detection which is based on the detection of the weak signal from a primary transmitter through the local observations of cognitive users. The hypotheses cab be defined as Í Ho n t x t 1 H1 hs t n t where x t is the signal received by the cognitive user s t is the transmitted signal of the primary user n t is the AWGN and h is the amplitude gain of the channel. Ho is a null hypothesis which states that there is no licensed user signal in a certain spectrum band. On the other hand H1 is an alternative hypothesis which states that there exist some licensed user signal. Three very famous models exist in order to implement transmitter detection according to the hypotheses model Poor Hadjiliadis 2008 . These are the matched filter detection the energy detection and the cyclostationary feature detection. Matched filter detection When the information about the primary user signal is known to the cognitive user the optimal detector in stationary Gaussian noise is the matched filter since it maximizes the received signal to noise ratio SNR . While the main advantage of the matched filter is that it requires less time to achieve high processing gain due to coherency it requires a priori knowledge of the primary
