Cellular networks are projected to deal with an immense rise in data traffic, as well as an enormous and diverse device, plus advanced use cases, in the nearest future; hence, future 5G networks are being developed to consist of not only 5G but also different RATs integrated. In addition to 5G, the user’s device (UD) will be able to connect to the network via LTE, WiMAX, WiFi, Satellite, and other technologies. On the other hand, Satellite has been suggested as a preferred network to support 5G use cases. However, achieving load balancing is essential to guarantee an equal amount of traffic distributed between different RATs in a heterogeneous wireless network; this would enable optimal utilisation of the radio resources and lower the likelihood of call blocking/dropping. This study presented an artificial intelligent-based application in heterogeneous wireless networks and proposed an Enhanced Particles Optimization (EPSO) algorithm to solve the load balancing problem in 5G-Satellite networks. The algorithm uses a call admission control strategy to admit users into the network to ensure that users are evenly distributed on the network. The proposed algorithm was compared with Artificial Bee and Simulated Annealing algorithm using three performance metrics: throughput, call blocking and fairness. Finally, based on the experimental findings, results outcomes were analysed and discussed.

The beam-hopping technology can solve the problems of uneven user distribution and uneven service demand, and improve the efficiency of resource utilization. It is one of the important technologies of future satellite-ground integrated communication. However, the mobility of LEO satellites and the on-demand scheduling of beams make each satellite beam correspond to multiple ground wave positions, which brings great difficulties to data processing. In this paper, after analyzing the difficulties of the data forwarding buffer of the beam-hopping system, a double-linked list structure of user state chain and data buffer chain is proposed, which solves the problem of data forwarding between the satellite and users in the dynamic state, and provides an efficient solution for the data exchange of the beam-hopping LEO satellite.

Summary — Large Low Earth Orbit satellite constellations require Machine Learning methods for enabling autonomy in health keeping of the satellites. Autonomy in health keeping entail’s fault detection, isolation and reconfiguration. However, prior to building model building, it becomes imperative to conduct Exploratory Data Analysis of the data to gain an intuition of data and to decide the best model. Univariate Exploratory data analysis has been carried out on a BUS CURRENT sensor of Electrical Power System of a Low Earth Orbit Satellite to gain an understanding of data. Various aspects of data like presence of outliers, sampling frequency, missing values, comparison of imputation methods to fill missing values seasonality and trend analysis, stationarity test on data, rolling mean, and auto correlation and partial auto correlation plots have been made and a detailed statistical analysis of results has been conducted.

This paper presents the latest achievements concerning 3GPP Release-17 adjacent band coexistence simulation work on 5G New Radio Non-Terrestrial Networks (NTNs) for satellite communications. For the first time, 3GPP considered the introduction of Mobile Satellite Service (MSS) frequency bands for 3GPP User Equipment (UE) direct connectivity with satellites and had to consider the coexistence in adjacent bands with Terrestrial Networks (TNs). This paper will further explain the most challenging and the main surprising outcomes of this work, which opened new market opportunities for both terrestrial and non-terrestrial stakeholders. The main conclusions can be summarized as (1) NTN UE can reuse the current requirements of the TN UE, (2) the satellite connectivity does not require a dedicated satellite waveform, and (3) TN can co-exist with NTN on adjacent channels with relaxed ACIR requirements for the tested simulation scenario.

A document by Eriserdi Mollaymeri. Click on the document to view its contents.

Conventional solid-state power amplifier (SSPA) design approach isolates RF design from communication theory. In this paper, a unified SSPA design approach is proposed which optimizes SSPA parameters (bias voltage and input RF signal power) to minimize total DC power consumption while satisfying received SNR constraint specified by the link budget. The effect of SSPA nonlinearity is quantified by the error vector magnitude measured at its output and the corresponding received SNR degradation is analyzed. Using the quantitative metrics for received SNR, it is possible to evaluate highly nonlinear SSPA classes such as Class-B or deep-Class AB which are normally not considered in conventional SSPA design approach to be used in satellite communication applications.

Two subsequent World Radiocommunication Conferences, held in 2015 and 2019, have concluded the frequency allocation in VHF bands for the two-way maritime VHF Data Exchange System (VDES) via terrestrial and satellite radio frequency links respectively. The modernization and digital evolution of maritime communications was initiated in 1990’s by adopting Automatic Identification Systems (AIS) for ship to shore, ship to ship and shore to ship communications for a variety of applications, targeting safety at sea. The frequency allocation for VDES has been a significant step forward towards achieving the same goal by facilitating solutions for enhanced navigation, broadcasting essential information and many other emerging applications.

LEO satellite networks have risen to the forefront of study with the dynamic topology changes, varying service requirements and intermittent inter-satellite links (ISLs). Resource scheduling mechanism is the key to determining communication efficiency. However, the state-of-the-art cannot achieve high resource efficiency under both heavy and burst traffic loads, and the applicability of parameters design is insufficient under intermittent ISLs. Considering this, we propose a dynamic even distribution mechanism combined with network coding DENC. This novel mechanism obtains the service requirements and allocates resources dynamically through the even distribution algorithm to balance between network maintenance overhead and idle resources waste, and improves the success probability of transmission based on network coding to balance between retransmission and redundancy. In this paper, we establish performance analysis and resource efficiency optimization models to optimize the parameters such as maintenance frequency and coding coefficient. Besides, we construct a system-level simulation platform. Mathematical and simulation results indicate that the DENC performs better than SAHN-MAC, ICSMA, CSMA-TDMA and HTM under dynamic service requirements and intermittent ISLs, and the resource efficiency can be improved by about 130%.