As the number of Internet of Things (IoT) devices continues to surge, particularly in remote areas, ensuring efficient and reliable connectivity has become a critical challenge. The integration of Narrowband IoT (NB-IoT) with Non-Terrestrial Networks (NTN) offers a promising solution. However, in Low Earth Orbit (LEO) satellite environments, existing random access (RA) procedures face significant issues, especially with high user density, leading to increased collisions and reduced access efficiency. While progress has been made in areas like delay compensation and Doppler effect management, challenges in collision mitigation remain. This paper proposes two innovative strategies to enhance RA performance in NB-IoT NTN systems: a non-orthogonal frequency hopping pattern for the narrowband physical random access channel (NPRACH) preamble, which increases the number of available preambles by allowing controlled overlap in frequency hopping sequences, thus reducing collision rates; and an adaptive access mechanism, which dynamically adjusts access parameters like backoff intervals and access barring factors based on network conditions to improve access success rates. Simulation results demonstrate the effectiveness of these improvements, especially in high-traffic environments, providing a more efficient and reliable solution for future NB-IoT deployments in NTN.

Abstract The requests of broadband coverage area and the expected user demand is satisfied by the satellite industry by using multiple spot beams of high throughput satellites with fixed multi-beam pattern and footprint planning. The technology core of high-throughput satellite is multi-beam technology, and the means to efficiently reuse spectrum is a full-frequency reuse scheme. In order to study the channel capacity limit of multi-beam satellite systems, the Wiener-Gaussian access model of terrestrial cellular systems is analyzed in this paper. This paper analyzes the Wiener-Gaussian access model of terrestrial cellular systems, then considers the difference between the spatial characteristics and gain characteristics of the multi-beam satellite system compared with the terrestrial cellular system, and proposes a Wiener model suitable for the multi-beam satellite communication system. On this basis, the channel capacity limit of multi-beam satellites under different fading conditions is deduced when using optimal linear precoding and minimum mean square error precoding. It provides theoretical support for the in-depth study of the channel capacity mechanism and system performance of multi-beam satellites.

Abstract In order to deal with the difficulty of spectrum sensing in cognitive satellite wireless networks, a large-scale cognitive network spectrum sensing algorithm based on big data analysis theory is studied, and a new algorithm using mean exponential eigenvalue is proposed. This new approach fully uses all the eigenvalues in sample covariance matrix of the sensing results to make the decision, which can effectively improve the detection performance without obtaining the prior information from licensed users. Through simulation, the performance of various large scale cognitive radio spectrum sensing algorithms based on big data analysis theory is compared, and the influence of satellite to ground channel conditions and the number of sensing nodes on the performance of the algorithm is discussed.

With the increasing demands of frequency resources, spectrum sharing technology between the satellite and terrestrial systems has received significant attention in recent years. In this paper, we investigate the outage performance of hybrid satellite-terrestrial networks with interference temperature constraints based on the underlay algorithm, where the satellite system and the terrestrial system act as the authorized network and the cognitive network, respectively. We assume that the satellite links undergo the shadowed-Rician fading and the terrestrial links follow the Rician fading. Besides, under the interference temperature constraint, the asymptotic outage probability is derived. Moreover, the numerical results demonstrate that the heavier shadowing severity of satellite interference link leads to better outage performance and the fading severity parameter of terrestrial links result in a reduced outage probability.

Abstract In order to reduce the risk of authorized users being interrupted in the cognitive satellite wireless network, a multi-step prediction approach based on a cascaded forward artificial neural network is proposed to predict user behavior in the designed scenario. This approach uses the powerful learning ability of the cascaded forward network to analyze the historical spectrum occupancy records of licensed users, and then predict the user behavior in the next few time slots. The prediction result can help the base station in the cognitive network to schedule the dynamic access process of the cognitive users, and reduce the interference caused by the cognitive user to the authorized users. Finally, compared with traditional prediction algorithms, it is verified that the proposed multi-step prediction algorithm can effectively reduce the probability of spectrum conflicts.