In cognitive radio networks, the unoccupied frequency bands licensed to primary users can be opportunistically accessed by secondary (low-power or hidden) cognitive users. Secondary users can be authorized low-power users, or unauthorized (hidden) users that occupy the band illegally transmitting under the noise level. More in details, the devised method is able to detect unknown low-power constant-modulus signals in noise of unknown variance, exploiting higher order moments of the received signal. The decision variable used in the detection stage is represented (only) by the estimated power of the hidden signal. Performance analysis is carried out in comparison with conventional energy detection, in the presence of noise uncertainty. In particular, the detection probabilities of the proposed and conventional methods as well as the mean detection time are evaluated and compared. The numerical results, obtained from wide simulation trials, have evidenced the efficiency of our method for detecting the hidden user’s low-power signal in cognitive communications.
Benedetto, F., Giunta, G., Guzzon, E., Renfors, M. (2013). Detection of Hidden Users in Cognitive Radio Networks. In 24th IEEE Int. Symp. on Personal, Indoor and Mobile Radio Communications (PIMRC'13 (pp.2306-2310) [10.1109/PIMRC.2013.6666527].
Detection of Hidden Users in Cognitive Radio Networks
BENEDETTO, FRANCESCO;GIUNTA, GAETANO;
2013-01-01
Abstract
In cognitive radio networks, the unoccupied frequency bands licensed to primary users can be opportunistically accessed by secondary (low-power or hidden) cognitive users. Secondary users can be authorized low-power users, or unauthorized (hidden) users that occupy the band illegally transmitting under the noise level. More in details, the devised method is able to detect unknown low-power constant-modulus signals in noise of unknown variance, exploiting higher order moments of the received signal. The decision variable used in the detection stage is represented (only) by the estimated power of the hidden signal. Performance analysis is carried out in comparison with conventional energy detection, in the presence of noise uncertainty. In particular, the detection probabilities of the proposed and conventional methods as well as the mean detection time are evaluated and compared. The numerical results, obtained from wide simulation trials, have evidenced the efficiency of our method for detecting the hidden user’s low-power signal in cognitive communications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
