In this paper, we investigate the outage probability (OP) performance of amplify-and-forward (AF) cognitive hybrid satellite-terrestrial overlay networks (CHSTONs) with the non-orthogonal multiple access (NOMA) scheme, in which half-duplexing terrestrial secondary networks cooperate with a primary satellite network for dynamic spectrum access. In order to improve the fairness of overlay paradigm, a NOMA-based power allocation profile is determined by instantaneous channel conditions. Considering the generalized Shadowed-Rician fading for satellite links, and Nakagami-m fading for terrestrial links, we derive the closed-form OP expressions for both the primary and secondary users. Then, asymptotic OP expressions at the high signal-to-noise ratio (SNR) regime are also obtained to evaluate the achievable diversity order and coding gain. Finally, numerical simulations are provided to validate the theoretical results as well as the superiority of the NOMA scheme in CHSTONs, and proclaim the effect of key parameters on the performance of NOMA users, such as fading configurations and the power split factor.

Due to the emergence of non-terrestrial platforms with extensive coverage, flexible deployment, and reconfigurable characteristics, the hybrid satellite-aerial-terrestrial networks (HSATNs) can accommodate a great variety of wireless access services in different applications. To effectively reduce the transmission latency and facilitate the frequent update of files with improved spectrum efficiency, we investigate the performance of cache-enabled HSATN, where the user retrieves the required content files from the cache-enabled aerial node (AN) or the satellite with the non-orthogonal multiple access (NOMA) scheme. If the required content files of the user are cached in the AN, the cache-enabled node would serve directly. Otherwise, the user would retrieve the content file from the satellite system, where the satellite system seeks opportunities for proactive content pushing to ANs during the user content delivery phase. Specifically, taking into account the uncertainty of the number and location of ANs, along with the channel fading of terrestrial users, the outage probability and hit probability of the considered network are, respectively, derived based on stochastic geometry. Numerical results unveil the effectiveness of the cache-enabled HSATN with the NOMA scheme and proclaim the influence of key factors on the system performance. The realistic, tractable, and expandable framework, as well as associated methodology, provide both useful guidance and a solid foundation for evolved networks with advanced configurations in the performance of cache-enabled HSATN.

In this paper, the performance of non-orthogonal multiple access (NOMA) based cooperative spectrum sharing in hybrid satellite-terrestrial networks (HSTNs) is investigated, where the primary satellite network recruits the secondary terrestrial network as a cooperative relay. To improve the fairness and spectrum utilization under cooperative spectrum sharing (i.e. overlay paradigm of cognitive radio), the NOMA power allocation profile is determined by instantaneous channel conditioning at the second temporal phase. The closed-form outage probability and approximated ergodic capacity expressions for the primary user (PU) and the secondary user (SU) are derived by decode-and-forward (DF) relay protocols, where the generalized Shadowed-Rician fading and Nakagami-m fading are considered for satellite links and terrestrial links, respectively. Simulation results are conducted for validation of the theoretical derivation and analysis of the impact of key parameters, and prove the superiority of NOMA comparing to conventional orthogonal multiple access (OMA) schemes on cooperative spectrum sharing in HSTNs. Besides, the fairness analysis between the PU and the SU is introduced by Jain’s fairness index (JFI).

In this article, we introduce a potential game-based approach to implement collaborative user scheduling and power allocation in the uplink multibeam satellite-based Internet of things (S-IoT) networks. First of all, a framework of the multibeam uplink S-IoT system is proposed, where full frequency reuse and co-channel interference among different spot beams are considered. To provide broadband S-IoT service effectively, we formulate an initial optimization problem of maximizing uplink sum transmission capacity and then transform it into an interference avoidance problem to address the mathematical intractability. Specifically, a game-theoretic model is implemented to solve the transformed optimization problem, which is proved to be a potential game and existence of Nash equilibriums (NEs). Moreover, an iterative algorithm with low computational complexity, motivated by the finite improvement property, is designed to implement collaborative user scheduling and power allocation to NE point. Finally, the simulation results prove the convergence and effectiveness of the proposed potential game-based approach.

In this paper, we consider the resource allocation problem in uplink cognitive satelliteterrestrial networks, where the cognitive satellite users reuse the frequency band of terrestrial cellular networks. In this scenario, the joint radio resource allocation strategy has to be reasonably designed to satisfy the interference constraint required by the incumbent terrestrial network (ITN). We formulate the optimization model of joint resource allocation with the perspective of efficiency and fairness, where the interference constraint is defined as the maximum tolerable interference outage probability of the ITN. Then, we simplify the proposed optimization problem into a tractable convex optimization form by some necessary mathematical simplification, wherein the simplification of the probability constraint takes the outdated channel state information into account. By analyzing the conditions of the optimal solution for the joint resource allocation problem in detailed, we derive the closed-form expression for both power allocation and subchannel allocation. Besides, we design an iterative algorithm for the joint resource allocation based on these closed-form solutions. Finally, some supporting results are given to verify the correctness and efficiency of the proposed algorithm.