Towards the Application of Neuromorphic Computing to Satellite Communications

in Towards the Application of Neuromorphic Computing to Satellite Communications (2022, October)

Artificial intelligence (AI) has recently received significant attention as a key enabler for future 5G-and-beyond terrestrial wireless networks. The applications of AI to satellite communications is also ... [more ▼]

Artificial intelligence (AI) has recently received significant attention as a key enabler for future 5G-and-beyond terrestrial wireless networks. The applications of AI to satellite communications is also gaining momentum to realize a more autonomous operation with reduced requirements in terms of human intervention. The adoption of AI for satellite communications will set new requirements on computing processors, which will need to support large workloads as efficiently as possible under harsh environmental conditions. In this context, neuromorphic processing (NP) is emerging as a bio-inspired solution to address pattern recognition tasks involving multiple, possibly unstructured, temporal signals and/or requiring continual learning. The key merits of the technology are energy efficiency and capacity for on-device adaptation. In this paper, we highlight potential use cases and applications of NP to satellite communications. We also explore major technical challenges for the implementation of space-based NP focusing on the available NP chipsets. [less ▲]

Enhanced Communications on Satellite-Based IoT Systems to Support Maritime Transportation Services

in Sensors (2022), 22(17),

Maritime transport has become important due to its ability to internationally unite all continents. In turn, during the last two years, we have observed that the increase of consumer goods has resulted in ... [more ▼]

Maritime transport has become important due to its ability to internationally unite all continents. In turn, during the last two years, we have observed that the increase of consumer goods has resulted in global shipping deadlocks. In addition, the future goes through the role of ports and efficiency in maritime transport to decarbonize its impact on the environment. In order to improve the economy and people’s lives, in this work, we propose to enhance services offered in maritime logistics. To do this, a communications system is designed on the deck of ships to transmit data through a constellation of satellites using interconnected smart devices based on IoT. Among the services, we highlight the monitoring and tracking of refrigerated containers, the transmission of geolocation data from Global Positioning System (GPS), and security through the Automatic Identification System (AIS). This information will be used for a fleet of ships to make better decisions and help guarantee the status of the cargo and maritime safety on the routes. The system design, network dimensioning, and a communications protocol for decision-making will be presented. [less ▲]

Machine Learning for Radio Resource Management in Multibeam GEO Satellite Systems

in Electronics (2022), 11(7), 992

Satellite communications (SatComs) systems are facing a massive increase in traffic demand. However, this increase is not uniform across the service area due to the uneven distribution of users and ... [more ▼]

Satellite communications (SatComs) systems are facing a massive increase in traffic demand. However, this increase is not uniform across the service area due to the uneven distribution of users and changes in traffic demand diurnal. This problem is addressed by using flexible payload architectures, which allow payload resources to be flexibly allocated to meet the traffic demand of each beam. While optimization-based radio resource management (RRM) has shown significant performance gains, its intense computational complexity limits its practical implementation in real systems. In this paper, we discuss the architecture, implementation and applications of Machine Learning (ML) for resource management in multibeam GEO satellite systems. We mainly focus on two systems, one with power, bandwidth, and/or beamwidth flexibility, and the second with time flexibility, i.e., beam hopping. We analyze and compare different ML techniques that have been proposed for these architectures, emphasizing the use of Supervised Learning (SL) and Reinforcement Learning (RL). To this end, we define whether training should be conducted online or offline based on the characteristics and requirements of each proposed ML technique and discuss the most appropriate system architecture and the advantages and disadvantages of each approach. [less ▲]

Method of Rain Attenuation Prediction Based on Long–Short Term Memory Network

in Neural Processing Letters (2022)

Rain attenuation events are one of the foremost drawbacks in satellite communications, impairing satellite link availability. For this reason, it is necessary to foresee rain events to avoid an outage of ... [more ▼]

Rain attenuation events are one of the foremost drawbacks in satellite communications, impairing satellite link availability. For this reason, it is necessary to foresee rain events to avoid an outage of the satellite link. In this paper, we propose and develop a method based on Machine Learning to predict events of rain attenuation without appealing to complex mathematical models. To be specific, we implement a Long–short term memory architecture that is a Deep Learning algorithm based on an artificial recurrent neural network. Furthermore, supervised learning is the learning task for our algorithms. For this purpose, rain attenuation time-series feed the Long–short term memory network at the input to train it. However, the lack of a rainfall database hinders the development of a reliable prediction method. Therefore, we generate a synthetic rain attenuation database by using the recommendations of the International Telecommunication Union. Each model is trained and validated by computational experiments, employing statistical metrics to find the most accurate and reliable models. Thus, the accuracy metric compares the outcomes of the proposal with other related methods and models. As a result, our best model reaches an accuracy of 91.88% versus 87.99% from the external best model, demonstrating superiority over other models/methods. On average, our proposal accuracy reaches a value of 88.08%. Finally, we find out that this proposal can contribute efficiently to improving the performance of satellite system networks by re-routing data traffic or increasing link availabilities, taking advantage of the prediction of rain attenuation events. [less ▲]

Optimization of cost and capacity of broadband satellite system and resources management using Machine Learning techniques

Doctoral thesis (2021)

Very High Throughput Satellite (VHTS) systems have an important role to play as a complement to future 5G terrestrial networks to meet the growing traffic demand. In the near future, VHTS systems are ... [more ▼]

Very High Throughput Satellite (VHTS) systems have an important role to play as a complement to future 5G terrestrial networks to meet the growing traffic demand. In the near future, VHTS systems are expected to reach a transmission capacity of 1 Tbps based on frequency reuse/polarization and multibeam coverage schemes. However, the traffic demand in the service area is not uniform and is also changing throughout the day. This means that with a traditional payload, some beams have insufficient resources and others have wasted resources. One solution to this problem is flexible payloads that allow satellite resources to be modified according to traffic demand. According to operators, the main challenges in Satellite Communications (SatComs) is to achieve new generation VHTS systems capable of satisfying traffic demand and to know how to manage resources in an optimal and autonomous way, thus emerging the problem of Dynamic Resource Management (DRM). With this in mind, this thesis studies the optimization for the design of new generation VHTS systems. The study is divided into two parts, satellites with fixed payload and satellites with flexible payload. For the first part, an optimization method is developed that minimizes the cost per Gbps in orbit and maximizes the capacity per beam, as a function of the number of beams, user G/T and annual availability. As an intermediate step between flexibility and a fixed system, the possibility of having a payload that provides coverage with irregularly sized beams depending on traffic demand is studied. While, for flexible systems, new optimization techniques belonging to Machine Learning are studied to manage resources dynamically and autonomously in the system. The results of this thesis provide new contributions for the design of new generations of VHTS broadband satellites and open a possibility for new research lines [less ▲]

Optimization in VHTS Satellite System Design with Irregular Beam Coverage for Non-Uniform Traffic Distribution

in Remote Sensing (2021), 13(13),

Very High Throughput Satellites (VHTS) have a pivotal role in complementing terrestrial networks to increase traffic demand. VHTS systems currently assume a uniform distribution of traffic in the service ... [more ▼]

Very High Throughput Satellites (VHTS) have a pivotal role in complementing terrestrial networks to increase traffic demand. VHTS systems currently assume a uniform distribution of traffic in the service area, but in a real system, traffic demands are not uniform and are dynamic. A possible solution is to use flexible payloads, but the cost of the design increases considerably. On the other hand, a fixed payload that uses irregular beam coverage depending on traffic demand allows maintaining the cost of a fixed payload while minimizing the error between offered and required capacity. This paper presents a proposal for optimizing irregular beams coverage and beam pattern, minimizing the costs per Gbps in orbit, the Normalized Coverage Error, and Offered Capacity Error per beam. We present the analysis and performance for the case study and compare it with a previous algorithm for a uniform coverage area. [less ▲]

Forward Link Optimization for the Design of VHTS Satellite Networks

in Electronics (2020), 9(3),

The concept of geostationary VHTS (Very High Throughput Satellites) is based on multibeam coverage with intensive frequency and polarization reuse, in addition to the use of larger bandwidths in the ... [more ▼]

The concept of geostationary VHTS (Very High Throughput Satellites) is based on multibeam coverage with intensive frequency and polarization reuse, in addition to the use of larger bandwidths in the feeder links, in order to provide high capacity satellite links at a reduced cost per Gbps in orbit. The dimensioning and design of satellite networks based on VHTS imposes the analysis of multiple trade-offs to achieve an optimal solution in terms of cost, capacity, and the figure of merit of the user terminal. In this paper, we propose a new method for sizing VHTS satellite networks based on an analytical expression of the forward link CINR (Carrier-to-Interference-plus-Noise Ratio) that is used to evaluate the trade-off of different combinations of system parameters. The proposed method considers both technical and commercial requirements as inputs, including the constraints to achieve the optimum solution in terms of the user G/T, the number of beams, and the system cost. The cost model includes both satellite and ground segments. Exemplary results are presented with feeder links using Q/V bands, DVB-S2X and transmission methods based on CCM and VCM (Constant and Variable Coding and Modulation, respectively) in two scenarios with different service areas. [less ▲]