Abstract
Cognitive radio (CR) is considered to be an effective approach to eliminate the dilemma of spectrum shortage. To meet the ever-increasing demands of instant and accurate spectrum sensing in CR with wideband and multi-frequency-slots, a novel wideband spectrum sensing algorithm based on bidirectional decision of normalized spectrum (BDNP) is proposed in this paper. The proposed algorithm takes the normalized power spectrum within the frequency slot as the detection statistics, and finds out all of the occupied frequency slots in the range of the target bandwidth by searching forward and backward in sequence. The asymptotic normality and independence of Fourier transform is proved firstly, and based on which the false alarm probability of single decision is derived. Additionally, the closed-form expression of decision threshold is obtained by using Neyman-Pearson criterion. Theoretical analysis and simulation results show that the BDNP algorithm can accurately identify occupied frequency slots, which provides the base of avoiding interference to the primary users. Furthermore, comparing with the spectrum sensing algorithm based on conventional spectral estimation (CSE), BDNP algorithm can effectively overcome noise uncertainty in spectrum sensing.
Highlights
With the boosting growth of mobile wireless applications, mobile data traffic is expected to reach 48.3 EB per month by 2021 [1]
In the presence of noise uncertainty, the multi-signal sensing performance of the bidirectional decision of normalized spectrum (BDNP) algorithm is significantly better than the multi-taper method (MTM) algorithm
In this paper, we proposed a spectrum-sensing algorithm based on bidirectional decision of normalized spectrum (BDNP) for the requirements of wideband, multiple frequency slots and real-time sensing in cognitive radio (CR) systems
Summary
With the boosting growth of mobile wireless applications, mobile data traffic is expected to reach 48.3 EB (one billion GB) per month by 2021 [1]. When using the quickest sequential search algorithm [18], [19] for spectrum sensing, the frequency band of interest is divided into a number of subbands, and secondary users acquire the timedomain samples from each subband one by one to determine the existence of primary users It requires a superheterodyne receiver for multiple mixing or digital filter bank for narrowband filtering to obtain the signal samples when applying this algorithm to the CR networks with wide bandwidth and narrow frequency slots, which leads to highly complex hardware platform and poor real-time performance. The simulation results show that the proposed algorithm is able to effectively overcome the influence of noise uncertainty on spectrum sensing performance, and achieve a low false alarm probability and a high detection probability in a wide range of signal-to-noise ratio to complete the in-band multi-signal sensing.
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