Mohamad Mostafa

Vulnerability analysis of the CNS-infrastructure: An exemplarily approach

In this paper we identify security-related vulnerabilities of a few CNS-systems and describe their possible abuse by malicious agents replicating and broadcasting CNS (similar) signals, particularly for jamming and spoofing purposes. For communications, navigation and surveillance we consider VHF digital link mode 2, ground-based augmentation system and the secondary surveillance radar, respectively. In each case, we introduce a technical overview, identify susceptibilities and describe possible malicious attacks and their corresponding consequences. Finally, we present possibilities for minimizing risks emerging from exploiting the identified vulnerabilities of the considered system.

DME-compliant LDACS1 cell planning: Initial steps

• Compatibility with DME is a limiting factor for LDACS1 cell planning • Reasonable number of DME-compliant LDACS1-GS locations is available • Cell planning within LDACS1 is the decisive factor for achieving full coverage.

Approximation of activation functions for vector equalization based on recurrent neural networks

Activation functions represent an essential element in all neural networks structures. They influence the overall behavior of neural networks decisively because of their nonlinear characteristic. Discrete- and continuous-time recurrent neural networks are a special class of neural networks. They have been shown to be able to perform vector equalization without the need for a training phase because they are Lyapunov stable under specific conditions. The activation function in this case depends on the symbol alphabet and is computationally complex to be evaluated. In addition, numerical instability can occur during the evaluation. Thus, there is a need for a computationally less complex and numerically stable evaluation. Especially for the continuous-time recurrent neural network, the evaluation must be suitable for an analog implementation. In this paper, we introduce an approximation of the activation function for vector equalization with recurrent neural networks. The activation function is approximated as a sum of shifted hyperbolic tangent functions, which can easily be realized in analog by a differential amplifier. Based on our ongoing research in this field, the analog implementation of vector equalization with recurrent neural networks is expected to improve the power/speed ratio by several order of magnitude compared with the digital one.

DME signal power from inlay LDACS1 perspective

L-band digital aeronautical communications system type 1 (LDACS1) is a multicarrier transmission system proposed to cope with the increasingly growing demand in the aeronautical communications. LDACS1 offers the possibility to operate as an inlay system in the frequency gaps between adjacent distance measuring equipment (DME) channels. Therefore, DME signals are interference signals from the perspective of an LDACS1 receiver. The estimation of the DME signal power in the adjacent LDACS1 channels is important for a successful inlay implementation of LDACS1. This includes among others, interference mitigation, cell planning and adaptive coding and modulation. In this paper, we investigate the power of a DME signal in the adjacent LDACS1 channels. Closed-form expressions have been obtained. In the worst case, we found out that the DME signal interference power in the adjacent LDACS1 channel is 32 dB below the DME transmit power.

Iterative interference mitigation and channel estimation for LDACS1

Within the Future Communications Infrastructure (FCI), the L-band Digital Aeronautical Communications System (LDACS) has been specified as the air-to-ground data link technology. Being one of the two LDACS candidates recommended for further study by the International Civil Aviation Organization (ICAO), LDACS1 is a frequency-division duplex (FDD) broadband system exploiting orthogonal frequency division multiplexing (OFDM). Due to signals from coexisting L-band radio systems, LDACS1 has to work under impulsive interference. In this paper, we study the iterative interference mitigation and channel estimation techniques for LDACS1, based on soft-input soft-output (SISO) demodulation and decoding schemes. We use a simple time-domain blanking nonlinearity to mitigate impulsive noise, which introduces inter-carrier interference (ICI) in frequency domain. To improve the performance, iterative decoding (ID) is carried out between a SISO demodulator and a SISO decoder, based on the Turbo principle. By taking into consideration imperfect channel state information (CSI), we design our iterative receiver with two loops, i.e., the inner loop for ID and the outer loop for interference mitigation and CSI estimation. We analyze the performance of the proposed iterative receiver by using bit-error rate (BER) simulations and extrinsic information transfer (EXIT) charts.

Advanced Low Power High Speed Nonlinear Signal Processing: An Analog VLSI Example.

Despite the progress made in digital signal processing during the last decades, the constraints imposed by high data rate communications are becoming ever more stringent. Moreover mobile communications raised the importance of power consumption for sophisticated algorithms, such as channel equalization or decoding. The strong link existing between computational speed and power consumption suggests an investigation of signal processing with energy efficiency as a prominent design choice. In this work we revisit the topic of signal processing with analog circuits and its potential to increase the energy efficiency. Channel equalization is chosen as an application of nonlinear signal processing, and a vector equalizer based on a recurrent neural network structure is taken as an example to demonstrate what can be achieved with state of the art in VLSI design. We provide an analysis of the equalizer, including the analog circuit design, system-level simulations, and comparisons with the theoretical algorithm. First measurements of our analog VLSI circuit confirm the possibility to achieve an energy requirement of a few pJ/bit, which is an improvement factor of three to four orders of magnitude compared with today’s most energy efficient digital circuits.

Datalink security in the L-band digital aeronautical communications system (LDACS) for air traffic management

Todays very high-frequency (VHF) voice-based air–ground communication system for tactical aircraft guidance is suffering from the VHF bands increasing saturation in high-density areas [1]. The air–ground1 communication infrastructure is therefore undergoing modernization to ensure the sustainable growth of the European air transportation system in the coming decades [2], [3]. One major goal of this effort is the introduction of computerized air traffic management applications and new digital communication links between aircraft and ground systems.

Addressing vulnerabilities of the CNS infrastructure to targeted radio interference

Communication, navigation, and surveillance (CNS) technology is the backbone of modern-day air traffic management (ATM), containing a wide variety of radio systems that include ground stations, satellites, and aviation users. With the continuing development of software-defined radio, CNS systems are faced with a fundamentally new challenge that was not known at the time many of the systems were designed: software-defined radio has simplified the generation of radio signals with arbitrarily configurable modulation schemes and waveforms, to the point in which it has become financially accessible for private individuals.

Unmanned aircraft systems: Spectrum related issues for control and non-payload communications

The aim of this paper is to summarize spectrum allocation aspects related to the control and non-payload communications link(s) for unmanned aircraft systems. We take into account the corresponding studies of ITU-R, the position of ICAO and related resolutions of world radiocommunication conferences. In addition, the current situation of the spectrum allocation for unmanned aircraft systems control and non-payload communications links with corresponding limitations are examined.

Improving coding scheme of LDACS in the reverse link

We show in this paper the achievable improvement of the coding gain in the reverse link (air-to-ground) for the L-band Digital Aeronautical Communications System if the current forward error correction scheme based on a concatenated Reed-Solomon convolutional code is replaced by either a turbo code or a nonbinary low-density parity-check code for the smallest assignable data block. Additionally to improving the coding gain, the proposed coding schemes enable a fully iterative detection because of their soft-value decoding algorithms. This improves in general the detection process as a whole.