Improved Spread Spectrum Aloha Protocol and Beam-Hopping Approach for Return Channel in Satellite Internet of Things.

This paper examines potential performances of the Spread Spectrum-based random access technique and proposes an Improved Spread Spectrum Aloha (ISSA) protocol for the return channel in satellite Internet of Things (IoT) based on the beam-hopping technique. The key design driver and detailed solution of ISSA protocol are presented in this work and it is shown that the proposed protocol achieves high throughput and low collision probability. To match user/traffic distribution, delay requirement and channel condition with beam allocation better, a low-complexity heuristic beam scheduling algorithm and a more effective Maximum-Weighted Clique (MWC) algorithm have been proposed. The heuristic algorithm considers the user/traffic distribution, inter-beam interference, and fairness primarily. However, the MWC algorithm gives considerations not only on above factors, but also on delay requirement and channel condition (path loss and rain attenuation) to maximize system capacity. The beam angle and interference avoidance threshold are proposed to measure the inter-beam interference, and the link propagation loss and rain attenuation are considered meanwhile in the channel condition. In the MWC algorithm, we construct an auxiliary graph to find the maximum-weighted clique and derive the weighting approach to be applied in different application scenarios. The performance evaluation of our ISSA protocol compared with the SSA protocol is presented, which achieves a gain of 16.7%. The simulation of the ISSA protocol combined with round robin, heuristic, and MWC beam scheduling for the return link in beam-hopping satellite IoTs is also provided. The results indicate that the throughput in nonuniform user distribution is much lower than in the uniform case without the beam scheduling algorithm. Through the application of the scheduling algorithm, the throughput performance can approach the uniform distribution. Finally, the degree of user satisfaction with different scheduling approaches is presented, which validates the effectiveness of heuristic and MWC algorithms.

Sensing-Based Dynamic Spectrum Sharing in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks.

This paper presents a cognitive satellite communication based wireless sensor network, which combines the wireless sensor network and the cognitive satellite terrestrial network. To address the conflict between the continuously increasing demand and the spectrum scarcity in the space network, the cognitive satellite terrestrial network becomes a promising candidate for future hybrid wireless networks. With the higher transmit capacity demand in satellite networks, explicit concerns on efficient resource allocation in the cognitive network have gained more attention. In this background, we propose a sensing-based dynamic spectrum sharing scheme for the cognitive satellite user, which is able to maximize the ergodic capacity of the satellite user with the interference of the primary terrestrial user below an acceptable average level. Firstly, the cognitive satellite user monitors the channel allocated to the terrestrial user through the wireless sensor network; then, it adjusts the transmit power based on the sensing results. If a terrestrial user is busy, the satellite user can access the channel with constrained power to avoid deteriorating the communication quality of the terrestrial user. Otherwise, if the terrestrial user is idle, the satellite user allocates the transmit power based on its benefit to enhance the capacity. Since the sensing-based dynamic spectrum sharing optimization problem can be modified into a nonlinear fraction programming problem in perfect/imperfect sensing conditions, respectively, we solve them by the Lagrange duality method. Computer simulations have shown that, compared with the opportunistic spectrum access, the proposed method can increase the channel capacity more than 20 % for P a v = 10 dB in a perfect sensing scenario. In an imperfect sensing scenario, P a v = 15 dB and Q a v = 5 dB, the optimal sensing time achieving the highest ergodic capacity is about 2.34 ms when the frame duration is 10 ms.

A Novel Dynamic Spectrum-Sharing Method for Integrated Wireless Multimedia Sensors and Cognitive Satellite Networks.

With the growing demand, Wireless Multimedia Sensor Networks (WMSNs) play an increasingly important role, which enhances the capacity of typical Wireless Sensor Networks (WSNs). Additionally, integrating satellite systems into WMSNs brings about the beneficial synergy, especially in rural and sparsely populated areas. However, the available spectrum resource is scarce, which contradicts the high-speed content required for multimedia. Cognitive radio is a promising solution to address the conflict. In this context, we propose a novel spectrum-sharing method for the integrated wireless multimedia sensor and cognitive satellite network based on the dynamic frequency allocation. Specifically, the Low Earth Orbit (LEO) satellite system plays the role of the auxiliary to connect sensor nodes and the remote control host, and it shares the same frequency with the Geostationary Earth Orbit (GEO) system in the downlink. Because the altitudes of GEO and LEO satellites differ greatly, the beam size of GEO is much larger than that of LEO, which provides the opportunity for LEO beam to reuse the frequency that was allocated to the GEO beam. A keep-out region is defined to guarantee the spectral coexistence based on the interference analysis in the worst case. In addition, a dynamic frequency allocation algorithm is presented to deal with the dynamic configuration caused by the satellite motion. Numerical results demonstrate that the dynamic spectrum-sharing method can improve the throughput.

Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.

This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.