## 1 Introduction  
Wireless sensor networks (WSNs) have been highly developed, which have lowered costs along with the rapid development of wireless communications and electronics technologies, and are widely used in various areas [1]. The researchers focused on different issues appropriate for particular WSN applications. WSNs have been applied to many fields and even cannot be replaced, in the areas of target tracking [2], disaster warning [3], wildlife monitoring [4], military applications [5; 6], health monitoring [7], monitoring and navigation [8; 9; 10], etc. Obviously, the communications are very important to WSNs, as the sensing information must be transmitted to the remote monitoring hosts (RMHs). Multiple input and multiple output (MIMO) has been regard as the important technology application for the future high data rate wireless communication networks [11; 12]. Therefore, [13; 14; 15; 16; 17; 18] investigated the MIMO transmission for the WSNs. The work in [13] studied the cooperative MIMO (C-MIMO) technology and adopted the low density parity check (LDPC) code as the error-correcting code, while [14; 15] analyzed the virtual MIMO (V-MIMO) for WSNs. The former configured the minimum energy consuming route and satisfied the end-to-end data rate and bit error rate (BER) requirements, and the latter analyzed the impact of the modulation techniques for the cooperative V-MIMO of WSNs. The work in [16] proposed an adaptive multi-node MIMO transmission to improve the transmission reliability and capacity of mobile sink nodes for the WSNs. The work in [17] presented an efficient and adaptive mutual authentication framework for the heterogeneous WSNs. Meanwhile, [18] introduced the nonlinear MIMO networks with the characteristics of low cost and low complexity for the WSNs. However, the research in [13; 14; 15; 16; 17; 18] has mainly focused on the terrestrial network applications, such as the lack of terrestrial networks coverage or where terrestrial networks were challenged by the operating environment, e.g., forest, wilderness and military environments. Since the multibeam satellite communication networks have the advantages of global coverage, unrestricted geography, low cost, quick response [19], and so on, satellite-based sensor networks have been investigated for various application scenarios [20; 21; 22]. The satellite networks can be considered as an important auxiliary to WSNs and may be used as the transmission link of the integrated wireless sensor and multibeam satellite networks (IWMSMSNs). Multibeam satellite networks share some of the same characteristics, such as low cost, low complexity and unrestricted geography, which are very suitable for WSNs. Like terrestrial WSNs, the satellite-based WSNs can also be applied to many fields, such as target detection and tracking, vehicular navigation and environmental monitoring [23; 24; 25]. The work in [23] proposed a hybrid architecture for which the first category performed detection and tracking functions and the second category transmitted sensing data through the satellite communication networks. The work in [24] proposed a data fusion technique based on radial basis function neural networks, which integrated a global positioning network with terrestrial sensor networks. The work in [25] presented a sink selection algorithm for the satellite-based environmental monitoring networks against the fading, noise and component failure. In particular, [26] investigated the architectures and scenarios for satellite-based WSNs and the potential role of satellite/space networks might play in certain WSN applications to provide integrated configurations. Then, [27] addressed four integrated sensor-satellite network architectures and analyzed the performance of packet loss rate, average end-to-end packet delay and overall energy consumption. The work in [28] evaluated the remote sensor and satellite network capacity and attempted to optimize the integrated wireless sensor and satellite network schedules.