Overview of Existing and Future Advanced Satellite Systems

This chapter presents an overview of legacy, existing, and future advanced satellite systems for future wireless communications. The overview uses top-down approach, starting with a comparison between a typical commercial regular satellite system and a high-throughput satellite (HTS) system, following by a discussion on commonly used satellite network topologies. A discussion on the design of satellite payload architectures supporting both typical regular satellite and HTS with associated network topologies will be presented. Four satellite payload architectures will be discussed, including legacy analog bent-pipe satellite (ABPS); existing digital bent-pipe satellite (DBPS) and advanced digital bent-pipe satellite using digital channelizer and beamformer (AdDBPS-DCB); and future advanced regenerative on-board processing satellite (AR-OBPS) payload architectures. Additionally, various satellite system architectures using AdBP-DCBS and AR-OBPS payloads for the fifth-generation (5G) cellular phone applications will also be presented

フレキシブルな大容量衛星通信システムの性能評価に関する研究

Tohoku University加藤寧課

Convolutional Neural Networks for Flexible Payload Management in VHTS Systems

Very high throughput satellite (VHTS) systems are expected to have a large increase in traffic demand in the near future. However, this increase will not be uniform throughout the service area due to the nonuniform user distribution, and the changing traffic demand during the day. This problem is addressed using flexible payload architectures, enabling the allocation of the payload resources in a flexible manner to meet traffic demand of each beam, leading to dynamic resource management (DRM) approaches. However, DRM adds significant complexity to the VHTS systems, which is why in this article, we are analyzing the use of convolutional neural networks (CNNs) to manage the resources available in flexible payload architectures for DRM. The VHTS system model is first outlined, for introducing the DRM problem statement and the CNN-based solution. A comparison between different payload architectures is performed in terms of DRM response, and the CNN algorithm performance is compared by three other algorithms, previously suggested in the literature to demonstrate the effectiveness of the suggested approach and to examine all the challenges involved

Machine Learning for Radio Resource Management in Multibeam GEO Satellite Systems

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

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system

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

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

Proceedings of the Fifth International Mobile Satellite Conference 1997

Satellite-based mobile communications systems provide voice and data communications to users over a vast geographic area. The users may communicate via mobile or hand-held terminals, which may also provide access to terrestrial communications services. While previous International Mobile Satellite Conferences have concentrated on technical advances and the increasing worldwide commercial activities, this conference focuses on the next generation of mobile satellite services. The approximately 80 papers included here cover sessions in the following areas: networking and protocols; code division multiple access technologies; demand, economics and technology issues; current and planned systems; propagation; terminal technology; modulation and coding advances; spacecraft technology; advanced systems; and applications and experiments

8-12 GHz pHEMT MMIC Low-Noise Amplifier for 5G and Fiber-Integrated Satellite Applications

The fifth-generation (5G) radio access technology promises to revolutionise integrated earth-space communications applications for ubiquitous, seamless and broadband services. The assigned sub-6 GHz and millimetre-wave 5G frequencies require the sensitivity of the receiver front-end subsystem(s) to detect and amplify the desired signal at a noise floor of less than -90 dBm for a cost-effective infrastructure deployment. This paper presents a broadband monolithic microwave integrated circuit (MMIC) low-noise amplifier (LNA) design based on a 0.15 µm gate length Indium Gallium Arsenide (InGaAs) pseudomorphic high electron mobility transistor (pHEMT) technology for 5G and fiber-integrated satellite communications applications. The designed three-stage 8-12 GHz LNA implements a common-source topology. The MMIC LNA subsystem performance demonstrates an industry-leading in-band gain response of 40 dB; a noise figure of 1.0 dB; and a power dissipation of 43 mW. For a constant bandwidth receiver, the sensitivity changes by approximately 1.5 dB over the operating satellite signal frequency. Similarly, for a variable bandwidth receiver, the sensitivity changes by approximately 1.5 dB over the channel bandwidth. Moreover, the sensitivity margin of the designed LNA is 40 dB and this holds a great promise for real-time radio access component-level reconfiguration applications