Satellite communications (SatComs) have recently entered a period of renewed interest motivated by technological advances and nurtured through private investment and ventures. The present survey aims at capturing the state of the art in SatComs, while highlighting the most promising open research topics. Firstly, the main innovation drivers are motivated, such as new constellation types, on-board processing capabilities, non-terrestrial networks and space-based data collection/processing. Secondly, the most promising applications are described, i.e., 5G integration, space communications, Earth observation, aeronautical and maritime tracking and communication. Subsequently, an in-depth literature review is provided across five axes: i) system aspects, ii) air interface, iii) medium access, iv) networking, v) testbeds & prototyping. Finally, a number of future challenges and the respective open research topics are described.

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Satellite Communications in the New Space Era: A Survey and Future Challenges

Whenever multibeam satellite systems target very aggressive frequency reuse in their coverage area, inter-beam interference becomes the major obstacle for increasing the overall system throughput. As a matter of fact, users located at the beam edges suffer from a very large interference for even a moderately aggressive planning of reuse-2. Although solutions for inter-beam interference management have been investigated at the satellite terminal, it turns out that the performance improvement does not justify the increased terminal complexity and cost. In this article, we pay attention to interference mitigation techniques that take place at the transmitter (i.e. the gateway). Based on this understanding, we provide our vision on advanced precoding techniques and user clustering methods for multibeam broadband fixed satellite communications. We also discuss practical challenges to deploy precoding schemes and the support introduced in the recently published DVB-S2X standard. Future challenges for novel configurations employing precoding are also provided.

Precoding in Multibeam Satellite Communications: Present and Future Challenges

The cascading of a discrete Fourier transform processor and a digital polyphase network is shown to reduce the computation rate in frequency multiplexing-demultiplexing systems to a value close to minimum. Implementation advantages of that technique are pointed out. The highest efficiency is achieved when the number of channels is close to a power of 2, which is demonstrated by the '60-channel frequency-division-multiplexing (FDM)-2 X 30-channel time- division-multiplexing (TDM) transmultiplexer; a rough estimate of the computation rate is carried out in a practical case and appears to be quite within reach of the present technological capabilities. Significant cost advantage over equivalent analog equipment is expected. A digital version of the 12-channel FDM system using the same technique is also considered.

TDM-FDM Transmultiplexer: Digital Polyphase and FFT

Computer Vision, and hence Artificial Intelligence-based extraction of information from images, has increasingly received attention over the last years, for instance in medical diagnostics. While the algorithms’ complexity is a reason for their increased performance, it also leads to the ‘black box’ problem, consequently decreasing trust towards AI. In this regard, “Explainable Artificial Intelligence” (XAI) allows to open that black box and to improve the degree of AI transparency. In this paper, we first discuss the theoretical impact of explainability on trust towards AI, followed by showcasing how the usage of XAI in a health-related setting can look like. More specifically, we show how XAI can be applied to understand why Computer Vision, based on deep learning, did or did not detect a disease (malaria) on image data (thin blood smear slide images). Furthermore, we investigate, how XAI can be used to compare the detection strategy of two different deep learning models often used for Computer Vision: Convolutional Neural Network and Multi-Layer Perceptron. Our empirical results show that i) the AI sometimes used questionable or irrelevant data features of an image to detect malaria (even if correctly predicted), and ii) that there may be significant discrepancies in how different deep learning models explain the same prediction. Our theoretical discussion highlights that XAI can support trust in Computer Vision systems, and AI systems in general, especially through an increased understandability and predictability.

Transparency and Trust in Human-AI-Interaction: The Role of Model-Agnostic Explanations in Computer Vision-Based Decision Support.

Studies of microbiome variation in wildlife often emphasize host physiology and diet as proximate selective pressures acting on host-associated microbiota. In contrast, microbial dispersal and ecological drift are more rarely considered. Using amplicon sequencing, we characterized the bacterial microbiome of adult female (n = 86) Sable Island horses (Nova Scotia, Canada) as part of a detailed individual-based study of this feral population. Using data on sampling date, horse location, age, parental status, and local habitat variables, we contrasted the ability of spatiotemporal, life history, and environmental factors to explain microbiome diversity among Sable Island horses. We extended inferences made from these analyses with both phylogeny-informed and phylogeny-independent null modelling approaches to identify deviations from stochastic expectations. Phylogeny-informed diversity measures were correlated with spatial and local habitat variables, but null modelling results suggested that heterogeneity in ecological drift, rather than differential selective pressures acting on the microbiome, was responsible for these correlations. Conversely, phylogeny-independent diversity measures were best explained by host spatial and social structure, suggesting that taxonomic composition of the microbiome was shaped most strongly by bacterial dispersal. Parental status was important but correlated with measures of β-dispersion rather than β-diversity (mares without foals had lower alpha diversity and more variable microbiomes than mares with foals). Our results suggest that between host microbiome variation within the Sable Island horse population is driven more strongly by bacterial dispersal and ecological drift than by differential selective pressures. These results emphasize the need to consider alternative ecological processes in the study of microbiomes.

Bacterial dispersal and drift drive microbiome diversity patterns within a population of feral hindgut fermenters

This paper gives the design and implementation of Xilinx FPGA based Forward Error Correction (FEC) encoder for DVB S2 system which includes BCH code followed by LDPC code and finally bit mapped to constellation for QPSK modulation. DVB-S2 FEC: ( $\mathbf{n}=64800,\ \mathbf{k}=32400$ ) rate 1/2 code, with QPSK modulation scheme is considered as target for FPGA implementation. The architecture in this design efficiently uses pipeline technique along with parallel processing to optimize the hardware resources and overall latency, to accomplish FEC encoding for DVB S2 system. Coding is completed in Verilog HDL with Xilinx Virtex6 XC6VLX240T FPGA as target for hardware realization and QuestaSim simulator is used to complete the functional simulation.

FPGA Implementation of FEC Encoder with BCH & LDPC Codes for DVB S2 System

Demand for transmission using short block length messages has been increased recently in applications including satellite communication, mobile communication, wireless sensor networks, and machine ...

Performance Analysis of Reliability-Based Decoding Algorithm for Short Block Length Turbo Codes

Errors in a transmitted message is unavoidable since noise is inevitable in any communication channel. For reliable transmission of messages, the bit error rate has to be kept at an acceptable rate by the use of proper error control coding schemes. To ensure that the transmission is also secure, data encryption is used as an integral part of the system. This paper deals with the design and analysis of a secure and reliable communication system accomplished using logistic map-based chaotic encryption and turbo product codes. The system is simulated using MATLAB and it is shown that the use of encryption for secure communication does not degrade the system performance. The hardware design of the decoder is also done and verified in Verilog using the same set of vectors as obtained from the system simulation. BER performance was analyzed in all the different scenarios and the correctness of the design was established.

Design and Analysis of a Secure Coded Communication System Using Chaotic Encryption and Turbo Product Code Decoder

Integrated circuits may be vulnerable to hardware Trojan attacks during its design or fabrication phases. This article is a case study of the design of a Viterbi decoder and the effect of hardware Trojans on a coded communication system employing the Viterbi decoder. Design of a Viterbi decoder and possible hardware Trojan models for the same are proposed. An FPGA-based implementation of the decoder and the associated Trojan circuits have been discussed. The noise-added encoded input data stream is stored in the block RAM of the FPGA and the decoded data stream is monitored on the PC through an universal asynchronous receiver transmitter interface. The implementation results show that there is barely any change in the LUTs used (0.5%) and power dissipation (3%) due to the insertion of the proposed Trojan circuits, thus establishing the surreptitious nature of the Trojan. In spite of the fact that the Trojans cause negligible changes in the circuit parameters, there are significant changes in the bit error rate (BER) due to the presence of Trojans. In the absence of Trojans, BER drops down to zero for signal to noise rations (SNRs) higher than 6 dB, but with the presence of Trojans, BER doesn’t reduce to zero even at a very high SNRs. This is true even with the Trojan being activated only once during the entire duration of the transmission.

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A Viterbi decoder and its hardware Trojan models: an FPGA-based implementation study.

There is a growing demand for low power error control decoders that are widely used in communication systems. One of the key component in a turbo error control decoder used to decode turbo codes-the Shannon limit approaching code- is a Max-Log-MAP decoder. To scale down the power and area used by the conventional Add-Compare-Select (ACS) module of the Max-Log-MAP decoder, a modified version of the ACS, known as Compare-Add-Select (CSA) has been used in this paper. The scale down is accomplished by reducing the number of operations used in calculating the path metrics of the Max-Log-MAP decoder. The observations assert that for the proposed architecture, there is a 50% reduction in both area and power without compromising the performance when compared to the conventional architecture.

Deepak Mishra

Papers

FPGA Implementation of FEC Encoder with BCH & LDPC Codes for DVB S2 System

Performance Analysis of Reliability-Based Decoding Algorithm for Short Block Length Turbo Codes

Design and Analysis of a Secure Coded Communication System Using Chaotic Encryption and Turbo Product Code Decoder

A Viterbi decoder and its hardware Trojan models: an FPGA-based implementation study.

Low Power and Area Efficient Max-log -MAP Decoder