Satellite Edge Computing (SEC) is seen as a promising solution to content caching onboard by reducing retrieval latency and improving user experience. Deciding content type, number of copies, and where to cache it in a satellite con-stellation remains challenging, requiring careful consideration of many factors, such as satellite coverage, content popularity, and resource constraints. In this paper, we study resource-aware onboard content caching strategies in a multi-layer hierarchical satellite network that includes Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and Geostationary Orbit (GEO) satellites. The primary objective is to design a cache placement strategy that maximizes resource utilization ratio while determining the optimal number of content copies, all within the context of a time-varying network topology that primarly occurs due to the mobility of non-geostationary (NGSO) satellites. We model a novel proximity-based hierarchical hybrid content popularity model and formulate the problem as an Integer Linear Programming (ILP) problem to utilize the resources in a network. To solve the ILP problem, we propose two algorithms: Greedy based Content Cache Placement (G_CCP) and Simulated Annealing based Content Cache Placement (SA_CCP). Extensive simulations demonstrate that both G_CCP and SA_CCP are near-optimal and outperform the benchmark in terms of cache-hit ratio, resource utilization ratio, and cache fetching duration.

High capacity satellite networks utilize beamforming as a critical pillar to ensure efficient and reliable communication. This paper presents a scalable and constrained clustering algorithm for downlink MEO beamforming with detailed attention to load balancing. We propose a three-step approach to address the challenges of grouping users under minimum load constraints as well as antenna requirements. The low-complexity algorithm operates by first sampling available user-traffic-data while respecting Must-Link (ML) and Cannot-Link (CL) constraints such that the sampled subset is representative of the entire dataset. In the second step, a Bivariate Gaussian Mixture Model (BGMM) is applied to cluster the sampled data, incorporating the ML/CL constraints directly into an expectation-maximization (EM) process. The user/beam assignments are computed by considering both spatial proximity and operator linkage constraints to address beams compliance with the defined relationships between users. The final step involves populating these clusters with the remaining data points using a modified stable marriage algorithm, ensuring each component meets the minimum load requirements. Critical iterative refinements are performed to optimize the cluster assignments while guaranteeing convergence to a balanced and efficient beamforming solution. The effectiveness of the proposed solution is tested against a payload system with/without power flexibility, which is often hard to parameterize optimally.

Through the transition from 5G to 6G, a significant rise in the number of Internet of Things (IoT) devices is anticipated, enabling pervasive and uninterrupted connectivity for several applications, in different verticals. Coping with the substantial influx of IoT devices and fulfilling the high capacity demands of different IoT technologies, such as NB-IoT, will necessitate the involvement of Non-Terrestrial Networks (NTNs), which will serve as crucial complements to terrestrial systems, enhancing the availability, resilience, and coverage of the network and will guarantee cost/benefit for some services and will fully satisfy some key requirements. Nevertheless, a primary obstacle to be faced when integrating IoT terrestrial communication systems in NTN, in particular with Non-Geostationary (NGSO) satellites, lies in the short visibility time of the flying platform due to its high speed. The latter introduces criticalities in various communication phases, including the Random Access (RA) procedure. In a highly congested scenario, the large Round Trip Delay and a limited visibility window, which varies for each user within the satellite’s coverage area, contribute to reducing the number of users successfully concluding the RA procedure. In this paper, to enhance the percentage of users who successfully conclude the RA, we introduce the concept of Coverage Enhancement Levels in time and a novel backoff mechanism, namely Smart Backoff, that leverages the beam coverage visibility period of individual users to adjust the random backoff interval. The numerical results obtained from our proposed scheme substantiate significant improvements compared to the standard backoff scheme. Specifically, our approach yields an increase of up to 16% per channel in the percentage of users who successfully complete the RA process.

Satellite Edge Computing (SEC) is seen as a promising solution for deploying network functions in orbit to provide ubiquitous services with low latency and bandwidth. Software Defined Networks (SDN) and Network Function Virtualization (NFV) enable SEC to manage and deploy services more flexibly. In this paper, we study a dynamic and topology-aware VNF mapping and scheduling strategy within an SDN/NFV-enabled SEC infrastructure. Our focus is on meeting the stringent requirements of mission-critical (MC) applications, recognizing their significance in both satellite-to-satellite and edge-to-satellite communications while ensuring service delay margin fairness across various time-sensitive service requests. We formulate the VNF mapping and scheduling problem as an Integer Nonlinear Programming problem (INLP), with the objective ofminimaxfairness among specified requests while considering dynamic satellite network topology, traffic, and resource constraints. We then propose two algorithms for solving theINLPproblem: Fairness-Aware Greedy Algorithm for Dynamic VNF Mapping and Scheduling (FAGD_MASC) and Fairness-Aware Simulated Annealing-Based Algorithm for Dynamic VNF Mapping and Scheduling (FASD_MASC) which are suitable for low and high service arrival rates, respectively. Our extensive simulations demonstrate that bothFAGD_MASCandFASD_MASCapproaches are very close to the optimization-based solution and outperform the benchmark solution in terms of service acceptance rates.

Satellite edge computing (SEC) has emerged as a promising technology to deliver network services to remote users. Coupled with software-defined networking (SDN) and network function virtualization (NFV), SEC can provide flexibility, agility, and efficiency when allocating computing and storage resources. However, there still remain a number of technical challenges in terms of fairness and efficiency of the allocation of physical resources in service provisioning, especially in a satellite network with limited resources and dynamic traffic demands. In this paper, we investigate a dynamic virtual network function (VNF) mapping and scheduling in an SDN/NFV-enabled SEC environment to maximize the fairness between competing services in terms of the E2E delay safe margin to enhance the service acceptance rates in the network. We mathematically formulate the VNF mapping and scheduling problem as a nonlinear integer optimization problem, which is NP-hard. In order to effectively solve the problem, this paper proposes a two-stage heuristic dynamic VNF mapping and scheduling algorithm: i) the path selection algorithm returns all possible paths for a given service request with multiple VNFs, which are sorted in ascending order based on their E2E service delay and executed offline, and ii) the dynamic VNF mapping and scheduling algorithm performs online dynamic remapping and rescheduling of VNFs. Finally, numerical results are provided to demonstrate that the proposed algorithm offers a higher service acceptance rate, computing resource utilization efficiency, and higher fairness compared to a benchmark scheme.

The satellite component is recognized as a promising solution to complement and extend the coverage of future Internet of Things (IoT) terrestrial networks (TNs). In this context, a study item to integrate satellites into narrowband-IoT (NB-IoT) systems has been approved within the 3rd Generation Partnership Project (3GPP) standardization body. However, as NB-IoT systems were initially conceived for TNs, their basic design principles and operation might require some key modifications when incorporating the satellite component. These changes in NB-IoT systems, therefore, need to be carefully implemented in order to guarantee a seamless integration of both TN and nonterrestrial network (NTN) for a global coverage. This article addresses this adaptation for the random access (RA) step in NB-IoT systems, which is in fact the most challenging aspect in the NTN context, for it deals with multiuser time-frequency synchronization and timing advance for data scheduling. In particular, we propose an RA technique which is robust to typical satellite channel impairments, including long delays, significant Doppler effects, and wide beams, without requiring any modification to the current NB-IoT RA waveform. Performance evaluations demonstrate the proposal’s capability of addressing different NTN configurations recently defined by 3GPP for the 5G new radio system.

The narrowband Internet-of-Things (NB-IoT) standard is a new cellular wireless technology, which has been introduced by the 3rd generation partnership project (3GPP) with the goal to connect massive low-cost, low-complexity and long-life IoT devices with extended coverage. In order to improve power efficiency, 3GPP proposed a new random access (RA) waveform for NB-IoT based on a single-tone frequency-hopping scheme. RA handles the first connection between user equipments (UEs) and the base station (BS). Through this, UEs can be identified and synchronized with the BS. In this context, receiver methods for the detection of the new waveform should satisfy the requirements on the successful user detection as well as the timing synchronization accuracy. This is not a trivial task, especially in the presence of radio impairments like carrier frequency offset (CFO) which constitutes one of the main radio impairments besides the noise. In order to tackle this problem, we propose a new receiver method for NB-IoT physical RA channel (NPRACH). The method is designed to eliminate perfectly the CFO without any additional computational complexity and supports all NPRACH preamble formats. The associated performance has been evaluated under 3GPP conditions. We observe a very high performance compared both to 3GPP requirements and to the existing state-of-the-art methods in terms of detection accuracy and complexity.