## 1 Introduction
Thus, in terms of discovering the vacant spectrum, CR will provide a competitive approach to obtain frequency for MSSs autonomously. Recently, the application of CR in hybrid/integrated Satellite-Terrestrial communication systems has received important attention lately in the research community. In 2012, [PERSON] et al. [12] summarized research papers devoted to the application of CR to satellite communications from 2007 to 2012, with special attention to the implementation of the spectrum sensing technique; [PERSON] et al. [13] introduced three application scenarios involving satellite acts PU or SU within the terrestrial system and defined the operational limits for interference management in the aforementioned scenarios regarding spectrum sensing. Based on the foregoing, it can be concluded that the application of CR techniques to satellite communication systems has obvious potential to improve spectral efficiency. Concretely, \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**L/S Band** & **Uplink (MHz)** & **Downlink (MHz)** & **Bandwidth (MHz)** & **Area** & **Operational Systems** \\ \hline \multirow{3}{*}{L band (1–2 GHz)} & 1610.0–1626.5 & 2483.5–2500.0 & 16.5 & Global & Iridium, Globalstar \\  & 1626.5–1660.5 & 1525.0–1559.0 & 34.0 & Global & Inmarsat, MSAI, SkyTerra, \\  & 1668.0–1675.0 & 1518.0–1525.0 & 7.0 & Global & AlphaStat I-XL \\ \hline \multirow{3}{*}{S band (2–4 GHz)} & 1980–2010 & 2170–2200 & 30 & Global & TerreStar, ICO \\  & 2670–2690 & 2500–2520 & 20 & Region III & Insat, N-STAR \\  & 2655–2670 & 2520–2535 & 15 & Region III & N-STAR \\ \hline \hline \end{tabular}
\end{table} 
Table 1: L/S band allocation for MSSs by ITU-R.  
[PERSON] et al. [14] performed spectrum sensing to find the signal of GSM Thuraya mobile satellite system for both uplink and downlink communication in the frequency ranges 1626.5-1660.5 MHz and 1525-1559 MHz, respectively. [PERSON] et al. [15] considered a real-world scenario involving spectrum sharing between terrestrial mobile wireless and meteorological satellite services in the band of 1695-1710 MHz with the total 15 MHz bandwidth. [PERSON] [16] focused on the secondary use of the satellite spectrum in the band of 2.17-2.2 GHz by a terrestrial system accompanied by 30 MHz bandwidth. [PERSON] et al. [17] presented cyclostationary analysis of real time satellite signals and its detection technique within a bandwidth of 4 MHz, in which the signal of interest is scanned and captured. These studies focused on the spectrum sharing within narrow band in the scenario of single satellite system. Furthermore, in 2015, [PERSON] et al. [18] investigated the potential of applying CR techniques in the scenario of Ka band multibeam satellite communications to increase the spectrum opportunities for future generations of satellite networks without interfering with the operation of incumbent services, in which the spectrum opportunities can potentially amount to 2.4 GHz of bandwidth in the downlink and 2 GHz of bandwidth in the uplink for fixed satellite services. However, those explorations of CR applied in satellite communication system from the latest scientific literature face the problem of sensing technology implementation in wideband signal detection. Actually, wideband sensing techniques are required for detecting wideband satellite signals. The most representative solution is based on filter banks to actualize spectrum sensing in each narrowband at a time. However, this approach requires a large number of RF components and introduces large latency [19; 20]. Besides, current analog-to-digital hardware technology faces tremendous challenge posed by conventional spectral estimation method, which operates equal or greater than the Nyquist sampling rate. As the efficient method to achieve real-time spectrum estimation of wideband signal at a sub-Nyquist sampling rate, compressed sensing (CS) combined sampling with compression operations has obtained substantial research efforts.