DefinePK

Abstract

The frequency spectrum of the electromagnetic radio is crowded day by day due to the expansion in wireless devices and applications. It has been additionally found that the allocated spectrum is underutilized as a result of the static portion of the spectrum. Cognitive radio (CR) allows for usage of licensed frequency bands by unlicensed users. These unlicensed users need to monitor the spectrum continuously to avoid possible interference with the licensed users. Spectrum usage regulations not permitting unlicensed users to authorized in a licensed spectrum. It has been seen that the whole licensed spectrum is not used at all places constantly. An unlicensed user can exploit advantage of such a situation to communicate thereby increasing spectrum efficiency. This is the fundamental thought behind Cognitive Radio. Demand for spectrum is expected to increasing rapidly and it would get in future. As more and more technologies are moving towards fully wireless, demand for spectrum is enhancing. In this paper, a proposed adaptive CR detection system is designed based on statistical features using neural network (multi layer perceptron) for intermediate frequency stage. Matlab simulation program is used to obtain the results. In order to evaluate the performance of the proposed CR detection systems, different modulated digital signals (2FSK, 4FSK, BPSK, QPSK, 8PSK, 4QAM, 16QAM, 64QAM and 256QAM) are generated at low SNR values. Multilayer perceptron is better than single layer due to their speed and nonlinearity solving problem. This is clearly seen in the obtained results such as Pd =100% for Pf=0.1 at SNR= -16dB, also Pd=90% at SNR= -40 dB and 95% at SNR= - 24dB with sensing time ?10?^(-4) sec at AWGN noisy channel.