Distributed Massive MIMO System with Dynamic Clustering in LEO Satellite Networks

Distributed massive multiple-input multiple output (mMIMO) system for low earth orbit (LEO) satellite networks is introduced as a promising technique to provide broadband connectivity. Nevertheless, several challenges persist in implementing distributed mMIMO systems for LEO satellite networks. These challenges include providing scalable massive access implementation as the system complexity increases with network size. Another challenging issue is the asynchronous arrival of signals at the user terminals due to the different propagation delays among distributed antennas in space, which destroys the coherent transmission, and consequently degrades the system performance. In this paper, we propose a scalable distributed mMIMO system for LEO satellite networks based on dynamic user-centric clustering. Aiming to obtain scalable implementation, new algorithms for initial cooperative access, cluster selection, and cluster handover are provided. In addition, phase shift-aware precoding is implemented to compensate for the propagation delay phase shifts. The performance of the proposed user-centric distributed mMIMO is compared with two baseline configurations: the non-cooperative transmission systems, where each user connects to only a single satellite, and the full-cooperative distributed mMIMO systems, where all satellites contribute serving each user. The numerical results show the potential of the proposed distributed mMIMO system to enhance system spectral efficiency when compared to noncooperative transmission systems. Additionally, it demonstrates the ability to minimize the serving cluster size for each user, thereby reducing the overall system complexity in comparison to the full-cooperative distributed mMIMO systems.

Learning-to-Learn the Wave Angle Estimation

A precise incident wave angle estimation in aerial communication is a key enabler in sixth-generation wireless communication network. With this goal, a generic 3-dimensional (3D) channel model is analyzed for air-to-air (A2A) networks under antenna misalignment, radio frequency impairments and polarization loss. The unique aspects of each aerial node are highlighted and the few-shot learning as a model agnostic meta-learning (MAML) classifier is proposed for learning-to-learn (L2L) incident wave angle estimation by utilizing the received signal strength (RSS). Additionally, a more computationally efficient technique, first order model agnostic meta-learning (FOMAML) is implemented. It has been observed that the proposed approach reaches up to 85% training accuracy and 75.4% evaluation accuracy with MAML. Regarding this, a convergence rate and accuracy trade-off have been established for several cases of MAML and FOMAML. For different L2L models trained with limited data, heuristic accuracy performance is determined by an upper bound of the probability of confidence.

Continuous Power Beaming to Lunar Far Side from EMLP-2 Halo Orbit

This paper focuses on FSO-based wireless power transmission (WPT) from Earth-Moon Lagrangian Point-2 (EMLP-2) to a receiver optical antenna equipped with solar cells that can be located anywhere on the lunar far side (LFS). Different solar-powered satellite (SPS) configurations which are EMLP-2 located single stable satellite and EMLP-2 halo orbit revolving single, double, and triple satellites are evaluated in terms of 100% LFS surface coverage percentage (SCP) and continuous Earth visibility. It is found that an equidistant triple satellite scheme on EMLP-2 halo orbit with a semi-major axis length of 15,000 km provides full SCP for LFS and it is essential for the continuous LFS wireless power transmission. In our proposed dynamic cislunar space model, geometric and temporal parameters of the Earth-Moon systems are used in affine transformations. Our dynamic model enables us to determine the full coverage time rate of a specific region such as the LFS southern pole. The outcomes show that the equidistant double satellite scheme provides SCP=100% during 88.60% time of these satellites' single revolution around the EMLP-2 halo orbit. Finally, the probability density function (PDF) of the random harvested power $P_H$ is determined and it validates the simulation data extracted from the stable EMLP-2 satellite and revolving satellite around EMLP-2 halo orbit for minimum and maximum LoS distances. Although the pointing devices to mitigate random misalignment errors are considered for the stable and revolving SPSs, better pointing accuracy is considered for the stable satellite. Our simulations show that the probability of $P_H\le$41.6 W is around 0.5 for the stable satellite whereas the CDF=0.99 for the revolving satellite case for a transmit power of 1 kW.

On the Mutuality between Localization and Channel Modeling in sub-THz

The use of sub-Terahertz (sub-THz) band is gaining considerable attention in 6G networks. In this study, we introduce hardware and propagation integrated 3D Propagation Model to describe sub-THz channels and discuss its advantages over both deterministic and stochastic 6G channel models. The unexplored mutuality of localization and communication is presented and its potential in integrated sensing and communication (ISAC) applications is highlighted. Afterward, a real-time sub-THz localization experiment is conducted to show the impact of the mispositioned and misaligned narrow beams on service quality. In continuation, we highlight the most current challenges and developments in THz localization and explore the potential of sub-THz frequencies to efficiently utilize the ultra-wideband spectrum. In the end, the open issues that need to be overcome to provide high spatial resolution and millidegree-level angle of arrival estimation in ISAC applications have been explored.

Free-Space Optical (FSO) Satellite Networks Performance Analysis: Transmission Power, Latency, and Outage Probability

In free-space optical satellite networks (FSOSNs), satellites can have different laser inter-satellite link (LISL) ranges for connectivity. Greater LISL ranges can reduce network latency of the path but can also result in an increase in transmission power for satellites on the path. Consequently, this tradeoff between satellite transmission power and network latency should be investigated, and in this work we examine it in FSOSNs drawing on the Starlink Phase 1 Version 3 and Kuiper Shell 2 constellations for different LISL ranges and different inter-continental connections. We use appropriate system models for calculating the average satellite transmission power and network latency. The results show that the mean network latency decreases and mean average satellite transmission power increases with an increase in LISL range. For the Toronto--Sydney inter-continental connection in an FSOSN with Starlink's Phase 1 Version 3 constellation, when the LISL range is approximately 2,900 km, the mean network latency and mean average satellite transmission power intersect are approximately 135 ms and 380 mW, respectively. For an FSOSN with the Kuiper Shell 2 constellation in this inter-continental connection, this LISL range is around 3,800 km, and the two parameters are approximately 120 ms and 700 mW, respectively. For the Toronto--Istanbul and Toronto--London inter-continental connections, the LISL ranges at the intersection are different and vary from 2,600 km to 3,400 km. Furthermore, we analyze outage probability performance of optical uplink/downlink due to atmosphere attenuation and turbulence.

Tensor-based Space Debris Detection for Satellite Mega-constellations

Thousands of satellites, asteroids, and rocket bodies break, collide, or degrade, resulting in large amounts of space debris in low Earth orbit. The presence of space debris poses a serious threat to satellite mega-constellations and to future space missions. Debris can be avoided if detected within the safety range of a satellite. In this paper, an integrated sensing and communication technique is proposed to detect space debris for satellite mega-constellations. The canonical polyadic (CP) tensor decomposition method is used to estimate the rank of the tensor that denotes the number of paths including line-of-sight and non-line-of-sight by exploiting the sparsity of THz channel with limited scattering. The analysis reveals that the reflected signals of the THz can be utilized for the detection of space debris. The CP decomposition is cast as an optimization problem and solved using the alternating least square (ALS) algorithm. Simulation results show that the probability of detection of the proposed tensor-based scheme is higher than the conventional energy-based detection scheme for the space debris detection.

Terahertz Communication Testbeds: Challenges and Opportunities

This study investigates an experimental software defined radio (SDR) implementation on 180 GHz. Rate scarcity and frequency sparsity are discussed as hardware bottlenecks. Experimental challenges are explained along with the derived system model of such a cascaded structure. Multiple error metrics for the terahertz (THz) signal are acquired, and various case scenarios are subsequently compared. The SDR-THz testbed reaches 3.2 Mbps with < 1 degree skew error. The use of a reflector plate can fine-tune the frequency error and gain imbalance in the expense of at least 14.91 dB signal-to-noise ratio. The results demonstrate the complete feasibility of SDR-based baseband signal generation in THz communication, revealing abundant opportunities to overcome hardware limitations in experimental research.

Secure and Robust Communications for Cislunar Space Networks

There is no doubt that the Moon has become the center of interest for commercial and international actors. Over the past decade, the number of planned long-term missions has increased dramatically. This makes the establishment of cislunar space networks (CSNs) crucial to orchestrate uninterrupted communications between the Moon and Earth. However, there are numerous challenges, unknowns, and uncertainties associated with cislunar communications that may pose various risks to lunar missions. In this study, we aim to address these challenges for cislunar communications by proposing a machine learning-based cislunar space domain awareness (SDA) capability that enables robust and secure communications. To this end, we first propose a detailed channel model for selected cislunar scenarios. Secondly, we propose two types of interference that could model anomalies that occur in cislunar space and are so far known only to a limited extent. Finally, we discuss our cislunar SDA to work in conjunction with the spacecraft communication system. Our proposed cislunar SDA, involving heuristic learning capabilities with machine learning algorithms, detects interference models with over 96% accuracy. The results demonstrate the promising performance of our cislunar SDA approach for secure and robust cislunar communication.

Quality of Service-Constrained Online Routing in High Throughput Satellites

High Throughput Satellites (HTSs) outpace traditional satellites due to their multi-beam transmission. The rise of low Earth orbit mega constellations amplifies HTS data rate demands to terabits/second with acceptable latency. This surge in data rate necessitates multiple modems, often exceeding single device capabilities. Consequently, satellites employ several processors, forming a complex packet-switch network. This can lead to potential internal congestion and challenges in adhering to strict quality of service (QoS) constraints. While significant research exists on constellation-level routing, a literature gap remains on the internal routing within a singular HTS. The intricacy of this internal network architecture presents a significant challenge to achieve high data rates. This paper introduces an online optimal flow allocation and scheduling method for HTSs. The problem is treated as a multi-commodity flow instance with different priority data streams. An initial full time horizon model is proposed as a benchmark. We apply a model predictive control (MPC) approach to enable adaptive routing based on current information and the forecast within the prediction time horizon while allowing for deviation of the latter. Importantly, MPC is inherently suited to handle uncertainty in incoming flows. Our approach minimizes packet loss by optimally and adaptively managing the priority queue schedulers and flow exchanges between satellite processing modules. Central to our method is a routing model focusing on optimal priority scheduling to enhance data rates and maintain QoS. The model's stages are critically evaluated, and results are compared to traditional methods via numerical simulations. Through simulations, our method demonstrates performance nearly on par with the hindsight optimum, showcasing its efficiency and adaptability in addressing satellite communication challenges.

Evolution of High Throughput Satellite Systems: Vision, Requirements, and Key Technologies

High throughput satellites (HTS), with their digital payload technology, are expected to play a key role as enablers of the upcoming 6G networks. HTS are mainly designed to provide higher data rates and capacities. Fueled by technological advancements including beamforming, advanced modulation techniques, reconfigurable phased array technologies, and electronically steerable antennas, HTS have emerged as a fundamental component for future network generation. This paper offers a comprehensive state-of-the-art of HTS systems, with a focus on standardization, patents, channel multiple access techniques, routing, load balancing, and the role of software-defined networking (SDN). In addition, we provide a vision for next-satellite systems that we named as extremely-HTS (EHTS) toward autonomous satellites supported by the main requirements and key technologies expected for these systems. The EHTS system will be designed such that it maximizes spectrum reuse and data rates, and flexibly steers the capacity to satisfy user demand. We introduce a novel architecture for future regenerative payloads while summarizing the challenges imposed by this architecture.