The usable satellite spectrum is becoming scarce due to static spectrum allocation policies. Cognitive radio approaches have already demonstrated their potential towards spectral efficiency for providing more spectrum access opportunities to secondary user (SU) with sufficient protection to licensed primary user (PU). Hence, recent scientific literature has been focused on the tradeoff between spectrum reuse and PU protection within narrowband spectrum sensing (SS) in terrestrial wireless sensing networks. However, those narrowband SS techniques investigated in the context of terrestrial CR may not be applicable for detecting wideband satellite signals. In this paper, we mainly investigate the problem of joint designing sensing time and hard fusion scheme to maximize SU spectral efficiency in the scenario of low earth orbit (LEO) mobile satellite services based on wideband spectrum sensing. Compressed detection model is established to prove that there indeed exists one optimal sensing time achieving maximal spectral efficiency. Moreover, we propose novel wideband cooperative spectrum sensing (CSS) framework where each SU reporting duration can be utilized for its following SU sensing. The sensing performance benefits from the novel CSS framework because the equivalent sensing time is extended by making full use of reporting slot. Furthermore, in respect of time-varying channel, the spatiotemporal CSS (ST-CSS) is presented to attain space and time diversity gain simultaneously under hard decision fusion rule. Computer simulations show that the optimal sensing settings algorithm of joint optimization of sensing time, hard fusion rule and scheduling strategy achieves significant improvement in spectral efficiency. Additionally, the novel ST-CSS scheme performs much higher spectral efficiency than that of general CSS framework.

In LEO mobile satellite network, the L/S frequency availability is an essential task for global communication but entails several major technical challenges: high sampling rate required for wideband sensing, limited power and computing resources for processing load, and frequency-selective wireless fading. This paper investigates the issue of frequency availability in LEO mobile satellite system, and a novel wideband spectrum compressed signal detection approach is proposed to obtain active primary users (PUs) subbands and their locations that should be avoided during frequency allocation. We define the novel wideband spectrum compressed sensing method based on discrete sine transform (DST-WSCS), which significantly improves the performance of spectrum detection and recovery accuracy compared with conventional discrete Fourier transform based wideband spectrum compressed sensing scheme (DFT-WSCS). Additionally, with the help of intersatellite links (ISL), the scheme of multiple satellites cooperative sensing according to OR and MAJ decision fusion rules is presented to achieve spatial diversity against wireless fading. Finally, in-depth numerical simulations are performed to demonstrate the performance of the proposed scheme in aspect of signal detection probability, reconstruction precision, processing time, and so forth.