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Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), The NOMAD (“Nadir and Occultation for MArs Discovery”) spectrometer suite on board the ExoMars Trace Gas Orbiter (TGO) has been designed to investigate the composition of Mars’ atmosphere, with a particular focus on trace gases, clouds and dust. The detection sensitivity for trace gases is considerably improved compared to previous Mars missions, compliant with the science objectives of the TGO mission. This will allow for a major leap in our knowledge and understanding of the Martian atmospheric composition and the related physical and chemical processes. The instrument is a combination of three spectrometers, covering a spectral range from the UV to the mid-IR, and can perform solar occultation, nadir and limb observations. In this paper, we present the science objectives of the instrument and explain the technical principles of the three spectrometers. We also discuss the expected performance of the instrument in terms of spatial and temporal coverage and detection sensitivity.© 2018, The Author(s)., The NOMAD experiment is led by the Royal Belgian Institute for Space Aeronomy (IASB-BIRA), assisted by Co-PI teams from Spain (IAA-CSIC), Italy (INAF-IAPS), and the United Kingdom (Open University). This project acknowledges funding by the Belgian Science Policy Office (BELSPO), with the financial and contractual coordination by the ESA Prodex Office (PEA 4000103401, 4000121493), by Spanish MICINN through its Plan Nacional and by European funds under grant ESP2015-65064-C2-1-P (MINECO/FEDER), as well as by UK Space Agency through grants ST/R005761/1, ST/P001262/1, ST/R001405/1 and ST/R001405/1 and Italian Space Agency through grant 2018-2-HH.0. The research was performed as part of the >Excellence of Science> project >Evolution and Tracers of Habitability on Mars and the Earth> (30442502). SA acknowledge support from the FNRS, Be.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/) The NOMAD (“Nadir and Occultation for MArs Discovery”) spectrometer suite on board the ExoMars Trace Gas Orbiter (TGO) has been designed to investigate the composition of Mars’ atmosphere, with a particular focus on trace gases, clouds and dust. The detection sensitivity for trace gases is considerably improved compared to previous Mars missions, compliant with the science objectives of the TGO mission. This will allow for a major leap in our knowledge and understanding of the Martian atmospheric composition and the related physical and chemical processes. The instrument is a combination of three spectrometers, covering a spectral range from the UV to the mid-IR, and can perform solar occultation, nadir and limb observations. In this paper, we present the science objectives of the instrument and explain the technical principles of the three spectrometers. We also discuss the expected performance of the instrument in terms of spatial and temporal coverage and detection sensitivity.© 2018, The Author(s). The NOMAD experiment is led by the Royal Belgian Institute for Space Aeronomy (IASB-BIRA), assisted by Co-PI teams from Spain (IAA-CSIC), Italy (INAF-IAPS), and the United Kingdom (Open University). This project acknowledges funding by the Belgian Science Policy Office (BELSPO), with the financial and contractual coordination by the ESA Prodex Office (PEA 4000103401, 4000121493), by Spanish MICINN through its Plan Nacional and by European funds under grant ESP2015-65064-C2-1-P (MINECO/FEDER), as well as by UK Space Agency through grants ST/R005761/1, ST/P001262/1, ST/R001405/1 and ST/R001405/1 and Italian Space Agency through grant 2018-2-HH.0. The research was performed as part of the >Excellence of Science> project >Evolution and Tracers of Habitability on Mars and the Earth> (30442502). SA acknowledge support from the FNRS, Be.

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We introduce a novel physical layer scheme for single user Multiple-Input Multiple-Output (MIMO) communications based on unsupervised deep learning using an autoencoder. This method extends prior work on the joint optimization of physical layer representation and encoding and decoding processes as a single end-to-end task by expanding transmitter and receivers to the multi-antenna case. We introduce a widely used domain appropriate wireless channel impairment model (Rayleigh fading channel), into the autoencoder optimization problem in order to directly learn a system which optimizes for it. We considered both spatial diversity and spatial multiplexing techniques in our implementation. Our deep learning-based approach demonstrates significant potential for learning schemes which approach and exceed the performance of the methods which are widely used in existing wireless MIMO systems. We discuss how the proposed scheme can be easily adapted for open-loop and closed-loop operation in spatial diversity and multiplexing modes and extended use with only compact binary channel state information (CSI) as feedback., Comment: under journal submission

We introduce a powerful recurrent neural network based method for novelty detection to the application of detecting radio anomalies. This approach holds promise in significantly increasing the ability of naive anomaly detection to detect small anomalies in highly complex complexity multi-user radio bands. We demonstrate the efficacy of this approach on a number of common real over the air radio communications bands of interest and quantify detection performance in terms of probability of detection an false alarm rates across a range of interference to band power ratios and compare to baseline methods.

We introduce a model for a market based economic system of cyber-risk valuation to correct fundamental problems of incentives within the information technology and information processing industries. We assess the makeup of the current day marketplace, identify incentives, identify economic reasons for current failings, and explain how a market based risk valuation system could improve these incentives to form a secure and robust information marketplace for all consumers by providing visibility into open, consensus based risk pricing and allowing all parties to make well informed decisions.

We study the adaptation of convolutional neural networks to the complex temporal radio signal domain. We compare the efficacy of radio modulation classification using naively learned features against using expert features which are widely used in the field today and we show significant performance improvements. We show that blind temporal learning on large and densely encoded time series using deep convolutional neural networks is viable and a strong candidate approach for this task especially at low signal to noise ratio.

NOMAD (Nadir and Occultation for MArs Discovery) is one of the four instruments on board the ExoMars Trace Gas Orbiter, scheduled for launch in March 2016. It consists of a suite of three high-resolution spectrometers - SO (Solar Occultation), LNO (Limb, Nadir and Occultation) and UVIS (Ultraviolet and Visible Spectrometer). Based upon the characteristics of the channels and the values of Signal-to-Noise Ratio obtained from radiometric models discussed in (Vandaele et al., 2015a, 2015b; Thomas et al., 2016), the expected performances of the instrument in terms of sensitivity to detection have been investigated. The analysis led to the determination of detection limits for 18 molecules, namely CO, HO, HDO, CH, CH, CH, HCO, CH, SO, HS, HCl, HCN, HO, NH, NO, NO, OCS, O. NOMAD should have the ability to measure methane concentrations, NOMAD has been made possible thanks to funding by the Belgian Science Policy Office (BELSPO) and financial and contractual coordination by the ESA Prodex Office (PlanetADAM no 4000107727). The research was performed as part of the >Inter-university Attraction Poles> programme financed by the Belgian Government (Planet TOPERS no P7-15) and a BRAIN Research Grant BR/143/A2/SCOOP. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement no. 607177 CrossDrive. UK funding is acknowledged under the UK Space Agency Grant ST/I003061/1.

This paper presents research in progress investigating the viability and adaptation of reinforcement learning using deep neural network based function approximation for the task of radio control and signal detection in the wireless domain. We demonstrate a successful initial method for radio control which allows naive learning of search without the need for expert features, heuristics, or search strategies. We also introduce Kerlym, an open Keras based reinforcement learning agent collection for OpenAI's Gym., Comment: 7 pages, 4 figures

The NOMAD instrument has been designed to best fulfil the science objectives of the ExoMars Trace Gas Orbiter mission that will be launched in 2016. The instrument is a combination of three channels that cover the UV, visible and IR spectral ranges and can perform solar occultation, nadir and limb observations. In this series of two papers, we present the optical models representing the three channels of the instrument and use them to determine signal to noise levels for different observation modes and Martian conditions. In this first part, we focus on the UVIS channel, which will sound the Martian atmosphere using nadir and solar occultation viewing modes, covering the 200-650nm spectral range. High SNR levels (, NOMAD has been made possible thanks to funding by the Belgian Science Policy Office (BELSPO) and financial and contractual coordination by the ESA Prodex Office (contracts no 4000107727 and 4000103401). The research was performed as part of the >Interuniversity Attraction Poles> programme financed by the Belgian government (Planet TOPERS, contract PAI no P7/15). UK funding is acknowledged under the UK Space Agency grant ST/I003061/1.

Spectrum sharing between radars and cellular systems is an emerging area of research. In this paper, we model channel between a seaborne MIMO radar and MIMO cellular system. We model a 2D channel to capture the azimuth aspect of the spectrum sharing scenario. Our channel modeling methodology allows MIMO radar to place accurate nulls in the azimuth location of base stations (BS), thus, protecting them from harmful radar interference. We use a projection based approach, where radar waveform is projected onto null space of channel, for mitigating radar interference to BSs. This is also known as an approach based on eigen-nulling which is different from spatial-nulling commonly employed by radars. We show through simulations that the proposed spatial channel model allows eigen-nulling which performs superior to traditional spatial-nulling for interference mitigation. The proposed channel model can be leveraged to use eigen-nulling that enhances target detection and beampattern resolution of MIMO radar while mitigating interference to BSs., submitted to IEEE Letters

In this paper, we present a novel approach for robust optimal resource allocation with joint carrier aggregation to allocate multiple carriers resources optimally among users with elastic and inelastic traffic in cellular networks. We use utility proportional fairness allocation policy, where the fairness among users is in utility percentage of the application running on the user equipment (UE). Each UE is assigned an application utility function based on the type of its application. Our objective is to allocate multiple carriers resources optimally among users subscribing for mobile services. In addition, each user is guaranteed a minimum quality of service (QoS) that varies based on the user's application type. We present a robust algorithm that solves the drawback in the algorithm presented in [1] by preventing the fluctuations in the resource allocation process, in the case of scarce resources, and allocates optimal rates for both high-traffic and low-traffic situations. Our distributed resource allocation algorithm allocates an optimal rate to each user from all carriers in its range while providing the minimum price for the allocated rate. In addition, we analyze the convergence of the algorithm with different network traffic densities and show that our algorithm provides traffic dependent pricing for network providers. Finally, we present simulation results for the performance of our resource allocation algorithm., Submitted to IEEE. Part of this work has been uploaded to arXiv:1405.6448

Sharing radar spectrum with communication systems is an emerging area of research. Deploying commercial wireless communication services in radar bands give wireless operators the much needed additional spectrum to meet the growing bandwidth demands. However, to enable spectrum sharing between these two fundamentally different systems interference concerns must be addressed. In order to assess interference concerns we design a three-dimensional (3D) channel model between radar and cellular base stations (BSs) in which the radar uses a two-dimensional (2D) antenna array and the BS uses a one-dimensional (1D) antenna array. We formulate a line-of-sight (LoS) channel and then propose an algorithm that mitigates radar interference to BSs. We extend the previously proposed null space projection algorithm for 2D channels to 3D channels and show that effective nulls can be placed by utilizing both the azimuth and elevation angle information of BSs. This results in effective interference mitigation. In addition we show that the 3D channel model allows us to accurately classify the size of radar's search space when null space projection algorithm is used for interference mitigation., Comment: submitted to IEEE Letters

This paper details the design of precoders for a MIMO radar spectrally coexistent with a MIMO cellular network. We focus on a coordinated multi-point (CoMP) system where a cluster of base stations (BSs) coordinate their transmissions to the intended user. The radar operates in two modes, interference-mitigation mode when it avoids interference with the CoMP system and cooperation mode when it exchanges information with it. Using either the conventional Switched Null Space Projection (SNSP) or the newly proposed Switched Small Singular Value Space Projection (SSSVSP), the radar beam sweeps across the BS clusters focusing on the optimal ones, optimal in either nullity or difference between the precoded and original radar signal. Taking the channel estimation error into account, the design of precoder is pivoted on the minimal radar interference at the BS clusters during interference-mitigation mode and minimal bit-error-rate at the BSs during cooperation mode while interfering minimally with the radar target detection capability. Our investigation shows that loss in radar performance can be compensated using SSSVSP instead of SNSP to some extent but increasing the number of radar antenna elements goes a long way to serve the purpose. Simulations verify our theoretical predictions about the proposed SSSVSP.

International audience; The NOMAD spectrometer suite on the ExoMars Trace Gas Orbiter will map the composition and distribution of Mars' atmospheric trace species in unprecedented detail, fulfilling many of the scientific objectives of the joint ESA-Roscosmos ExoMars Trace Gas Orbiter mission. The instrument is a combination of three channels, covering a spectral range from the UV to the IR, and can perform solar occultation, nadir and limb observations. In this paper, we present the science objectives of the instrument and how these objectives have influenced the design of the channels. We also discuss the expected performance of the instrument in terms of coverage and detection sensitivity.

The increase in data storage and power consumption at data-centers has made it imperative to design energy efficient Distributed Storage Systems (DSS). The energy efficiency of DSS is strongly influenced not only by the volume of data, frequency of data access and redundancy in data storage, but also by the heterogeneity exhibited by the DSS in these dimensions. To this end, we propose and analyze the energy efficiency of a heterogeneous distributed storage system in which $n$ storage servers (disks) store the data of $R$ distinct classes. Data of class $i$ is encoded using a $(n,k_{i})$ erasure code and the (random) data retrieval requests can also vary across classes. We show that the energy efficiency of such systems is closely related to the average latency and hence motivates us to study the energy efficiency via the lens of average latency. Through this connection, we show that erasure coding serves the dual purpose of reducing latency and increasing energy efficiency. We present a queuing theoretic analysis of the proposed model and establish upper and lower bounds on the average latency for each data class under various scheduling policies. Through extensive simulations, we present qualitative insights which reveal the impact of coding rate, number of servers, service distribution and number of redundant requests on the average latency and energy efficiency of the DSS., Submitted to IEEE Transactions on Cloud Computing. Contains 24 pages, 13 figures

Jamming attacks can significantly impact the performance of wireless communication systems. In addition to reducing the capacity, such attacks may lead to insurmountable overhead in terms of re-transmissions and increased power consumption. In this paper, we consider the multiple-input single-output (MISO) broadcast channel (BC) in the presence of a jamming attack in which a subset of the receivers can be jammed at any given time. Further, countermeasures for mitigating the effects of such jamming attacks are presented. The effectiveness of these anti-jamming countermeasures is quantified in terms of the degrees-of-freedom (DoF) of the MISO BC under various assumptions regarding the availability of the channel state information (CSIT) and the jammer state information at the transmitter (JSIT). The main contribution of this paper is the characterization of the DoF region of the two user MISO BC under various assumptions on the availability of CSIT and JSIT. Partial extensions to the multi-user broadcast channels are also presented., Comment: submitted to IEEE Transactions on Information Theory

A significant limitation of current cyber security research and techniques is its reactive and applied nature. This leads to a continuous 'cyber cycle' of attackers scanning networks, developing exploits and attacking systems, with defenders detecting attacks, analyzing exploits and patching systems. This reactive nature leaves sensitive systems highly vulnerable to attack due to un-patched systems and undetected exploits. Some current research attempts to address this major limitation by introducing systems that implement moving target defense. However, these ideas are typically based on the intuition that a moving target defense will make it much harder for attackers to find and scan vulnerable systems, and not on theoretical mathematical foundations. The continuing lack of fundamental science and principles for developing more secure systems has drawn increased interest into establishing a 'science of cyber security'. This paper introduces the concept of using cybernetics, an interdisciplinary approach of control theory, systems theory, information theory and game theory applied to regulatory systems, as a foundational approach for developing cyber security principles. It explores potential applications of cybernetics to cyber security from a defensive perspective, while suggesting the potential use for offensive applications. Additionally, this paper introduces the fundamental principles for building non-stationary systems, which is a more general solution than moving target defenses. Lastly, the paper discusses related works concerning the limitations of moving target defense and one implementation based on non-stationary principles., Comment: 12 pages, 7 figures

Mobile wireless delay-tolerant networks (DTNs) are wireless networks that suffer from intermittent connectivity, but enjoy the benefit of mobile nodes that can store, carry, and forward packets or messages, bringing them closer to their destinations through a selective forwarding policy. The evaluation of DTN routing protocols has primarily relied on simulation because most theoretical mobility models are unable to represent the mobility patterns that such protocols seek to take advantage of. In this paper we present and analyze a mobility model that we call localized random walk. This model is simple enough that it can be incorporated into mathematical models, but is spatially localized, which unlike other common mobility models, will make it possible to showcase the properties of heuristic-based DTN routing protocols. We derive the stationary spatial distribution of the mobility model, approximate what we call its spatial cross section, approximate the properties of its interaction with nodes following other mobility models, and use it to model some relatively simple DTN scenarios.

Background The immune contribution to cancer progression is complex and difficult to characterize. For example in tumors, immune gene expression is detected from the combination of normal, tumor and immune cells in the tumor microenvironment. Profiling the immune component of tumors may facilitate the characterization of the poorly understood roles immunity plays in cancer progression. However, the current approaches to analyze the immune component of a tumor rely on incomplete identification of immune factors. Methods To facilitate a more comprehensive approach, we created a ranked immunological relevance score for all human genes, developed using a novel strategy that combines text mining and information theory. We used this score to assign an immunological grade to gene expression profiles, and thereby quantify the immunological component of tumors. This immunological relevance score was benchmarked against existing manually curated immune resources as well as high-throughput studies. To further characterize immunological relevance for genes, the relevance score was charted against both the human interactome and cancer information, forming an expanded interactome landscape of tumor immunity. We applied this approach to expression profiles in melanomas, thus identifying and grading their immunological components, followed by identification of their associated protein interactions. Results The power of this strategy was demonstrated by the observation of early activation of the adaptive immune response and the diversity of the immune component during melanoma progression. Furthermore, the genome-wide immunological relevance score classified melanoma patient groups, whose immunological grade correlated with clinical features, such as immune phenotypes and survival. Conclusions The assignment of a ranked immunological relevance score to all human genes extends the content of existing immune gene resources and enriches our understanding of immune involvement in complex biological networks. The application of this approach to tumor immunity represents an automated systems strategy that quantifies the immunological component in complex disease. In so doing, it stratifies patients according to their immune profiles, which may lead to effective computational prognostic and clinical guides.

Two T helper (Th) cell subsets, namely Th1 and Th2 cells, play an important role in inflammatory diseases. The two subsets are thought to counter-regulate each other, and alterations in their balance result in different diseases. This paradigm has been challenged by recent clinical and experimental data. Because of the large number of genes involved in regulating Th1 and Th2 cells, assessment of this paradigm by modeling or experiments is difficult. Novel algorithms based on formal methods now permit the analysis of large gene regulatory networks. By combining these algorithms with in silico knockouts and gene expression microarray data from human T cells, we examined if the results were compatible with a counter-regulatory role of Th1 and Th2 cells. We constructed a directed network model of genes regulating Th1 and Th2 cells through text mining and manual curation. We identified four attractors in the network, three of which included genes that corresponded to Th0, Th1 and Th2 cells. The fourth attractor contained a mixture of Th1 and Th2 genes. We found that neither in silico knockouts of the Th1 and Th2 attractor genes nor gene expression microarray data from patients with immunological disorders and healthy subjects supported a counter-regulatory role of Th1 and Th2 cells. By combining network modeling with transcriptomic data analysis and in silico knockouts, we have devised a practical way to help unravel complex regulatory network topology and to increase our understanding of how network actions may differ in health and disease., Author Summary Different T helper (Th) cell subsets have an important role in regulating the immune response in inflammatory diseases. Th1 and Th2 cells are thought to counter-regulate each other, and alterations in their balance result in different diseases.This paradigm has been challenged by recent clinical and experimental data. Because of the large number of genes involved in regulating Th1 and Th2 cells, assessment of this paradigm by experiments or modelling is difficult. In this study, we combined novel algorithms for network analysis, in silico knockouts, and gene expression microarrays to examine if Th1 and Th2 cells had counter-regulatory roles. We constructed a directed network model of genes that regulated Th1 and Th2 cells through text mining and manual curation. We identified four cycles in the gene expression dynamics, three of which expressed genes that corresponded to Th0 (Th1/Th2 precursor), Th1 and Th2 cells. The fourth cycle contained the expression of a mixture of Th1 and Th2 genes. We found that neither in silico knockouts of the Th1 and Th2 attractor genes nor gene expression microarray data from patients and healthy subjects supported a counter-regulatory role of Th1 and Th2 cells.