###### Abstract
In addition, many cognitive technologies are presented, e.g., spectrum sensing [22; 23; 24; 25], smart antennas and beamforming [26; 27; 28], beacon signaling [25; 29], interference alignment [30; 31; 32], precoding [33], power control [34; 35; 36; 37; 38], beamhopping [39; 40] and network coding [41]. Although cognitive radio in terrestrial wireless systems has been deeply studied, the usage in satellite communications faces new challenges, e.g., system architecture, propagation model, round-trip delay, receiver characteristics, satellite characteristics, broad beam coverage, power level and limited possibilities of evolution due to the long system development and the fixed design space segment [37]. There are many open avenues to exploit cognitive radio in satellite communications, especially for the dual satellite network, in which the spectrum is shared between two satellite systems. In addition, most existing studies focus on the static scenarios, where the satellites are Geostationary Earth Orbit (GEO). There are tricky problems to deal with when the cognitive radio is adopted in Non-GeStationary Orbit (NGSO) satellites because of the satellite motion. The most critical issue lies in the arising of in-line interference when satellites and users from different systems are in alignment, which makes systems paralyzed [42]. To address this issue, the OneWeb system introduced an innovative technique, i.e., progressive pitch, which avoids the interference by gradually and slightly tilting the satellite as it approaches the equator [6]. Nevertheless, it is well known that adjusting the satellite attitude results in the consumption of fuel whether the propulsion is powered electrically or chemically, which will shorten the lifetime of the satellite. [PERSON] [37] reviewed the database approach and pointed out that the awareness of other systems' operational characteristics, such as frequency allocations, orbital positions, and antenna patterns, is the key for the successful coexistence between NGSO satellite systems. In this regard, Reference [38] proposed an Adaptive Power Control (APC) technique to ensure the spectral coexistence between the GEO and NGSO satellites. In addition, Reference [40] proposed a cognitive broadband satellite network based on the beamhopping and APC techniques, and the feasibility of the APC was verified by calculating how fast the power adaptation to be performed in [37]. However,the spectral efficiency of the secondary system should be declined to protect the primary system when APC is adopted. In this paper, we propose a novel spectrum-sharing method for integrated wireless multimedia sensor and cognitive satellite networks based on the dynamic frequency allocation. Specifically, the LEO satellite system functions as the auxiliary to connect the sensor nodes and the remote control host, and the LEO satellite user plays the role of the sink node. The LEO system shares the same spectrum with the incumbent GEO system, where the GEO satellite acts as the primary system, and the LEO satellite constellation serves as the secondary system. Through the interference analysis between the GEO and LEO satellites, a keep-out region is proposed to guarantee the spectral sharing, which is defined as the minimum spatial isolation distance between GEO and LEO beams. When the LEO beam approaches the keep-out region of the GEO co-channel beam, which means that the LEO and GEO beams with the same frequency overlap, the frequency will be reallocated to avoid the Co-Channel Interference (CCI). In addition, a dynamic frequency allocation algorithm is presented, which can simultaneously enhance the spectral efficiency and reduce the switching frequency of the beam frequency during the satellite motion. The remainder of this paper is organized as follows: Section 2 presents the spectrum-sharing method for the integrated wireless multimedia sensor and cognitive satellite network. The interference analysis and the dynamic frequency allocation algorithm are discussed in Section 3.