The exponential growth of Internet of Things (IoT) applications led to the deployment of IoT devices in remote areas beyond the reach of terrestrial networks, calling for satellite network solutions. Indeed, Low-Earth Orbit (LEO) satellites can provide global connectivity to direct-to-satellite (DtS)-IoT applications, with remarkable impact in several areas, as environmental monitoring, precision agriculture, and disaster prevention. One of the key challenges in DtS-IoT is supporting energy and spectral efficient multiple access, which has attracted a lot of attention recently. This work presents two novel multiple-access scheduling strategies for DtS-IoT networks, both inspired by the scheduling algorithm for LoRa to LEO satellites (SALSA). The latter prevents collisions by applying a first-come-first-served (FCFS) policy to allocate dedicated time slots according to the devices’ rise times. However, the effectiveness of SALSA decreases in high-density scenarios, for which the visibility time of many devices is insufficient to successfully schedule their transmission. In the proposed scheduling methods, we take advantage of the availability of multiple frequency channels and the ability to change the transmission scheduling order of some devices within a visibility time window to improve uplink efficiency. The numerical results show that the average number of uplinks per lap and per visible device increases with the number of available channels, providing an improvement of almost 80% in terms of system uplink efficiency, and the proposed scheduling methods are more effective with smaller packet sizes. Additionally, we explore that the fusion of both scheduling strategies can further boost the system performance while guaranteeing an uplink efficiency greater than 50%, as elucidated across the implementation algorithms with four, six, and eight multiple channels.

Direct-to-satellite Internet of Things (IoT) solutions have attracted a lot of attention from industry and academia recently, as promising alternatives for large scale coverage of a massive number of IoT devices. In this work, we considered that a cluster of IoT devices was under the coverage of a constellation of low-Earth orbit (LEO) satellites, while slotted Aloha was used as a medium access control technique. Then, we analyzed the throughput and packet loss rate while considering potentially different erasure probabilities at each of the visible satellites within the constellation. We show that different combinations of erasure probabilities at the LEO satellites and the IoT traffic load can lead to considerable differences in the system’s performance. Next, we introduce an intelligent traffic load distribution (ITLD) strategy, which, by choosing between a non-uniform allocation and the uniform traffic load distribution, guarantees a high overall system throughput, by allocating more appropriate amounts of traffic load at different positions (i.e., different sets of erasure probabilities) of the LEO constellation with respect to the IoT cluster. Finally, the results show that ITLD, a mechanism with low implementation complexity, allows the system to be much more scalable, intelligently exploiting the potential of the different positions of the satellite constellation.

The deployment of satellite networks is key to providing global wireless connectivity for the Internet of Things (IoT). In this line, we consider a cluster of IoT devices served by a constellation of low Earth orbit (LEO) satellites, while slotted Aloha is used as a medium access control technique in the uplink. To characterize the channel, we employ an On-Off fading channel model that estimates the quality of the links between the cluster of IoT devices and the LEO satellites within the constellation, by taking into account their relative positions. Since each relative position of the constellation with respect to the cluster of IoT devices leads to a different throughput for a given traffic load, we propose a novel traffic load distribution strategy based on successive convex approximation (SCA) to maximize the system throughput. The method adequately allocates the traffic load among the different constellation positions with respect to the IoT cluster. Finally, the results show that the proposed method outperforms other recently proposed strategies based on heuristics for traffic load allocation, while it also achieves a stable non-zero throughput even for large traffic loads.

The integration of low Earth orbit (LEO) satellites with Internet of Things (IoT) devices has driven the need for efficient, low-complexity multiple access techniques. However, most approaches based on the Slotted Aloha protocol rely on the ON-OFF channel model, which oversimplifies the physical channel phenomena and neglects critical fading effects. To overcome this limitation, the present work develops a precise closed-form analytical model for instantaneous throughput, outage, and data collision probabilities of a direct-to-satellite IoT (DtS-IoT) network operating over Nakagami-m fading channels while employing the Slotted Aloha technique. The analysis accounts for the presence of multiple satellites in orbit, each with different channel loads and elevation angles, thus providing a more realistic representation of fading conditions and inter-satellite variability. The simulation results confirm the validity of the proposed analytical expressions and show that they exhibit excellent agreement with theoretical predictions under Nakagami-m fading. Furthermore, the results indicate that dynamically adjusting the transmit power and channel load, especially when satellite position information is available, can significantly increase system throughput and provide actionable insights for system optimization in terms of energy efficiency and overall performance.

The task of offloading packets in LEO satellite networks in an IoT cluster context is often affected by excessive energy consumption, frequent loss of data packets in the medium access, limited visibility time with the ground station, and limited resources available to the satellites. Inter-satellite communication (ISC) techniques have been introduced to address these challenges. However, these techniques require high technical and strategic development to meet the requirements of the end users. In this regard, four strategies are proposed: Brief (which eliminates all redundancy); Balanced (which eliminates the redundancy but keeps the amount of information for each satellite balanced); Redundancy (which includes all the information collected on each satellite); and Coded (which provides redundancy through information coding). Our techniques are to exchange signaling or data packets between satellites via ISC to download the collected data. At the same time, one of these goals is prioritized: the lowest energy consumption, the highest reliability of information delivery, or the balance between the previous two. Consequently, the system performance is evaluated from each evolved stage and the overall system. The results show that Redundancy and Coded techniques increase the offloading rate, while Brief and Balanced techniques increase the system's energy efficiency. Since Brief and Balanced techniques avoid redundant information transmission, decreasing the slot time. The Coded technique presents a better tradeoff between energy efficiency and reliability than the Brief , Balanced , and Redundancy techniques. Finally, the results show the positive impact of ISC on satellite networks that collect information from ground IoT devices to download it to an Earth station.

Direct-to-Satellite IoT (DtS-IoT) has the potential to support multiple verticals, including agriculture, industry, smart cities, and environmental disaster prevention. However, device transmissions are affected by intrinsic factors such as satellite trajectory, limited visibility time windows, collision messages and signal reception quality. This work introduces two DtS-IoT schemes using power domain Non-Orthogonal Multiple Access (NOMA) in the uplink with either fixed (FTP) or controlled (CTP) transmit power. We consider that the IoT devices use LoRa Modulation to transmit data packets to the LEO satellite in orbit, equipped with a Successive Interference Cancellation (SIC)-enabled gateway. We also assume the IoT devices are empowered with a predictor of the satellite orbit. Using real geographic location and trajectory data, we evaluate the performance of the average number of successfully decoded transmissions, goodput (bytes/lap), and energy consumption (bytes/Joule) as a function of the number of network devices. Numerical results show the trade-off between goodput and energy efficiency for both proposed schemes. Comparing FTP and CTP with ALOHA for 100 devices, we find goodput improvements of 28% and 18%, respectively. For the same number of devices, we also achieved improvements of 234% and 207% when the proposed strategies are compared with Max Angle, a method that transmits at the maximum elevation angle only. Notably, CTP effectively leverages transmission opportunities as the network size increases, outperforming the other strategies. Moreover, CTP shows the best performance in energy efficiency.