Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userSpectrum Prediction and Interference Detection for Satellite Communications
113
0
0.0
(
0
)
Added by
Lissy Pellaco
Publication date
2019
fields
Electronic Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
Spectrum monitoring and interference detection are crucial for the satellite service performance and the revenue of SatCom operators. Interference is one of the major causes of service degradation and deficient operational efficiency. Moreover, the satellite spectrum is becoming more crowded, as more satellites are being launched for different applications. This increases the risk of interference, which causes anomalies in the received signal, and mandates the adoption of techniques that can enable the automatic and real-time detection of such anomalies as a first step towards interference mitigation and suppression. In this paper, we present a Machine Learning (ML)-based approach able to guarantee a real-time and automatic detection of both short-term and long-term interference in the spectrum of the received signal at the base station. The proposed approach can localize the interference both in time and in frequency and is universally applicable across a discrete set of different signal spectra. We present experimental results obtained by applying our method to real spectrum data from the Swedish Space Corporation. We also compare our ML-based approach to a model-based approach applied to the same spectrum data and used as a realistic baseline. Experimental results show that our method is a more reliable interference detector.
rate research
Read More
In this paper, we propose the joint interference cancellation, fast fading channel estimation, and data symbol detection for a general interference setting where the interfering source and the interfered receiver are unsynchronized and occupy overlapping channels of different bandwidths. The interference must be canceled before the channel estimation and data symbol detection of the desired communication are performed. To this end, we have to estimate the Effective Interference Coefficients (EICs) and then the desired fast fading channel coefficients. We construct a two-phase framework where the EICs and desired channel coefficients are estimated using the joint maximum likelihood-maximum a posteriori probability (JML-MAP) criteria in the first phase; and the MAP based data symbol detection is performed in the second phase. Based on this two-phase framework, we also propose an iterative algorithm for interference cancellation, channel estimation and data detection. We analyze the channel estimation error, residual interference, symbol error rate (SER) achieved by the proposed framework. We then discuss how to optimize the pilot density to achieve the maximum throughput. Via numerical studies, we show that our design can effectively mitigate the interference for a wide range of SNR values, our proposed channel estimation and symbol detection design can achieve better performances compared to the existing method. Moreover, we demonstrate the improved performance of the iterative algorithm with respect to the non-iterative counterpart.
Non-orthogonal multiple access (NOMA) schemes are being considered in 5G new radio developments and beyond. Although seminal papers demonstrated that NOMA outperforms orthogonal access in terms of capacity and user fairness, the majority of works have been devoted to the wireless terrestrial arena. Therefore, it is worth to study how NOMA can be implemented in other types of communications, as for instance the satellite ones, which are also part of the 5G infrastructure. Although communications through a satellite present a different architecture than those in the wireless terrestrial links, NOMA can be an important asset to improve their performance. This article introduces a general overview of how NOMA can be applied to this different architecture. A novel taxonomy is presented based on different multibeam transmission schemes and guidelines that open new avenues for research in this topic are provided.
Precoding has stood out as a promising multi-user transmission technique to meet the emerging throughput demand of satellite communication systems while awaiting the technological maturity for exploiting higher bands. Precoding enables the reduction of interference among co-channel beams through spatial processing while promoting aggressive frequency reuse and improving spectral efficiency. Satellite systems offer multitude of system and service configurations, resulting in different precoder design methodologies. This article explores the motivation for the introduction of precoding, offers an insight to their theoretical development in a diverse scenarios and presents some avenues for future development.
RF-powered backscatter communication is a promising new technology that can be deployed for battery-free applications such as internet of things (IoT) and wireless sensor networks (WSN). However, since this kind of communication is based on the ambient RF signals and battery-free devices, they are vulnerable to interference and jamming. In this paper, we model the interaction between the user and a smart interferer in an ambient backscatter communication network as a game. We design the utility functions of both the user and interferer in which the backscattering time is taken into the account. The convexity of both sub-game optimization problems is proved and the closed-form expression for the equilibrium of the Stackelberg game is obtained. Due to lack of information about the system SNR and transmission strategy of the interferer, the optimal strategy is obtained using the Q-learning algorithm in a dynamic iterative manner. We further introduce hotbooting Q-learning as an effective approach to expedite the convergence of the traditional Q-learning. Simulation results show that our approach can obtain considerable performance improvement in comparison to random and fixed backscattering time transmission strategies and improves the convergence speed of Q-Learning by about 31%.
In this paper, we investigate the use of chirp spread spectrum signaling over air-ground channels. This includes evaluation of not only the traditional linear chirp, but also of a new chirp signal format we have devised for multiple access applications. This new format is more practical than prior multi-user chirp systems in the literature, because we allow for imperfect synchronism. Specifically we evaluate multi-user chirp signaling over air-ground channels in a quasi-synchronous condition. The air-ground channels we employ are models based upon an extensive NASA measurement campaign. We show that our new signaling scheme outperforms the classic linear chirp in these air-ground settings.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
