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Due to the drastic increase of electricity prosumers, i.e., energy consumers that are also producers, smart grids have become a key solution for electricity infrastructure. In smart grids, one of the most crucial requirements is the privacy of the final users. The vast majority of the literature addresses the privacy issue by providing ways of hiding user's electricity consumption. However, open issues in the literature related to the privacy of the electricity producers still remain. In this paper, we propose a framework that preserves the secrecy of prosumers' identities and provides protection against the traffic analysis attack in a competitive market for energy trade in a Neighborhood Area Network (NAN). In addition, the amount of bidders and of successful bids are hidden from malicious attackers by our framework. Due to the need for small data throughput for the bidders, the communication links of our framework are based on a proprietary communication system. Still, in terms of data security, we adopt the Advanced Encryption Standard (AES) 128 bit with Exclusive-OR (XOR) keys due to their reduced computational complexity, allowing fast processing. Our framework outperforms the state-of-the-art solutions in terms of privacy protection and trading flexibility in a prosumer-to-prosumer design.

Performance validation of Satcom on-the-move (SOTM) terminals is becoming more important as the satellite operators continue to recognize the negative influence of suboptimal terminals on their satellite networks. Traditionally, SOTM testing is performed with actual operational satellites in field tests, which lack repeatability. The capability to repeat the conditions in which SOTM terminals are tested is important, especially when the performance of multiple terminals is compared. This contribution describes how the qualification test of SOTM terminals can be conducted in a laboratory environment so that repeatability can be ensured. A major advantage of a laboratory environment is the ability to test the complete terminal as if it was in the field of operation, yet without the involvement of real satellites effectively reducing the costs of testing. The main contributions of this paper are motion and shadowing profiles suitable for standardization of SOTM testing. Standardization of such profiles is necessary to guarantee a fair comparison of the performance of different terminals. Moreover, the paper presents the methodology for testing SOTM terminals at the Fraunhofer Facility for Over-the-air Research and Testing, the procedure used to obtain the proposed profiles and results of testing a Ka-band SOTM terminal, taken as an example.

Radio access at mm-waves has been subject of intensive research in the latest years. However, within the initial deployment of 5G, mm-waves are still relegated and there is a generalized idea that the mm-wave channel for radio access, in comparison to the sub-6 GHz channel, is not only sparse but also troublesome for outdoor applications. In the present paper we introduce simultaneous multi-band measurements comparing the sub-6 GHz with the mm-waves channel at 30 GHz and 60 GHz in street canyon scenarios using the same measurement equipment in Germany and Japan. An analysis on the propagation and radio channel characteristics shows that the mm-waves channel offers similar opportunities as the sub-6 GHz. Consequently, the challenge relies on the design of an adequate radio interface matching the channel characteristics. In that regard, aspects as the location of clusters and spatial consistency gain importance within geometry-based stochastic channel models (GBSCMs). The analysis of the large-scale parameters (LSPs) has shown a large influence of the geometry of the scenario on the channel, encouraging the introduction of deterministic modelling components within GBSCMs targeting these scenarios.

In the air-ground propagation channel, multipath propagation severely affects the performance of communication, navigation, and surveillance systems used in civil aviation. To verify the performance of aeronautical wireless transmission systems independently from expensive flight trials, a channel model for computer simulations is required. Based on an exhaustive propagation measurement campaign, we propose a geometry-based stochastic channel model for the air-ground channel in a regional airport environment in the L-band. The proposed channel model allows us to correctly reproduce the non-stationarity of the channel impulse response. Thus, the channel model is suitable not only to assess the performance of communication systems, but also for ranging, i.e., for navigation systems. We validate the channel model using data from both channel sounding and as well as flight measurements performed in a navigation context.

In order to fully exploit the scarce spectrum, antenna arrays are incorporated into wireless communication devices in 4G and 5G communication networks to deploy MIMO-OFDM systems. Recently, the least squares Khatri-Rao factorization has been applied to MIMO-OFDM systems for semi-blind joint channel and symbol estimation. Its cubic computational complexity is prohibitive when the number of transmit and receive antennas is very large. Therefore, the average vector and Hadamard ratio rank one approximation has been proposed for MIMO-OFDM systems, showing a linear complexity, but being limited to channels and transmitted symbols with offsets. In this paper, we present four novel MIMO-OFDM algorithms for massive antenna array systems that outperform the state-of-the-art approaches in terms of complexity and/or accuracy. The four proposed schemes are the alternating least squares with vector selection initialization, the vector projection rank one approximation including vector selection rank one initialization, the factorization based on eigenvalue decomposition with eigenvector projection and the factorization based on sectional truncated singular value decomposition and vector projection. Our analytical complexity analysis and numerical results corroborate the trade-offs offered by the different receiver algorithms in terms of complexity, parallelism and performance.

An automotive concept for vehicular communications is proposed that utilizes the potential of the roof area for antennas. Antennas are distributed in cavities and on shelves in the center and on the front and rear roof ends. The arrangement of antennas on the roof allows better radiation to the front and back of automobiles than shark-fins and single cavities. Combining several modules provides space for further antennas, sensors, and integrated front-ends, as well as better spatial separation for multiple-input multiple-output (MIMO) arrays beyond 5G, and cooperative connected and automated driving. A prototype was developed and built into a car chassis. The measured data were analyzed and evaluated in the view of coverage for vulnerable road users and on correlation for the MIMO.

Global Navigation Satellite Systems (GNSS), such as GPS, Galileo, GLONASS, and BeiDou, are vital for safety-critical applications such as civilian aviation and autonomous vehicles. These applications demand very accurate positioning, especially in scenarios in which multipath components are present. In this paper, we propose a semi-algebraic framework for approximate Canonical Polyadic Decomposition via simultaneous matrix diagonalization (SECSI) with Higher Order Singular Value Decomposition (HOSVD) low-rank approximation for time-delay estimation for antenna array based GNSS receivers. The HOSVD-SECSI based approach outperforms all the state-of-the-art tensor-based algorithms for time-delay estimation, mainly, for scenarios with highly correlated or coherent signals and in case of more than two multipath components.

In the air-ground propagation channel, multipath propagation severely affects the performance of the communication, navigation, and surveillance systems used in civil aviation. To gain a deeper understanding of the air-ground channel, we are interested in the locations of objects causing multipath propagation. Therefore, in this paper we propose and experimentally validate an algorithm to localize reflectors causing multipath components based on channel sounding data collected using omnidirectional antennas. The algorithm relies on superresolution parameter estimation and tracking as well as on a localization algorithm. Using both simulations and channel sounding data collected from flight trials, we demonstrate the ability to reliably localize the reflectors causing multipath components.

Antenna characterisation is usually performed by antenna pattern measurements in an anechoic chamber. Subsequently, a conducted test, the radiated two-stage or the wireless-cable method can be used for an overall system evaluation considering the measured patterns. In this study, the authors present a method to perform device tests for antenna arrays/smart antennas with and without the need of radiation pattern measurements, and they validate it experimentally. By using over-the-air tests in a virtual electromagnetic environment and wave-field synthesis, the propagation environment can be realistically recreated in the region around a device-under-test. This allows for reproducible performance comparisons of different antennas or systems under identical propagation environment conditions. As a special application, they consider the controlled reception pattern antenna in a global navigation satellite systems environment in the presence of interferer signals.

Preventing data leakage on the mobile client is a crucial security problem. Therefore, additional control and protection should be taken for the confidential data on the mobile clients that leave the boundaries of the organization. This paper presents a novel approach to the security of the corporate mobile clients, in particular when they operate in the offline mode. The presented approach includes the essential conceptualization and the definition of the core methodology to solve the problem of offline mobile security, i.e. the protection of the confidential data in use when the mobile client is not connected to the corporate cloud. The protection of the sensitive data is provided by the combination of cryptographic means and analytics methods to detect malicious user behavior. The proposed security architecture supports the basic mobile client protection principles: minimized traffic load and reduced communication with the cloud; usage of light-weighted operations and an optimized combination of the security methods.

The suitability of compact antenna arrays for Direction of Arrival (DoA) estimation of radio emissions is investigated. Some applications may set constraints with respect to the antenna array physical size. If we increase the number of radiating elements in a given array size to maximize the degrees of freedom (DoF), the spacing between neighboring elements reduces to less than half of the free-space wavelength. Consequently, the electromagnetic coupling between the antenna elements becomes stronger. The result is a distortion of the radiation patterns, and mismatch at the antenna ports. This will have serious effects on the performance of any DoA estimator. Whereas the radiation pattern distortion, which is known from calibration measurements, can be taken into consideration by the DoA estimator, the power mismatch causes a loss of received signal power, and therefore the SNR is reduced. This can only be mitigated by an analog Decoupling and Matching Network (DMN), app lied directly at the antenna array outputs, before digitalization. The DMN together with the antennas will exhibit mutually orthogonal radiation patterns, referred to as eigenpatterns. The output ports are, as a consequence, ideally ""decoupled"", and the power spread of the eigenmodes will reflect the available DoF. We investigate the influence of DMN design to the DoA performance in terms of the Cramér-Rao Lower Bound (CRLB). We show that, both decoupling and matching will have positive impact on the average CRLB. Moreover, for the application case of DoA estimation using small flying UAV platforms (UAV: Unmanned Aerial Vehicles), we describe the performance of a specific circular array with L-Quad antenna elements, and demonstrate the need for dual-polarimetric design and calibration.

Novel schemes for attack detection are crucial to identify adaptive malicious traffic coming from sources that are quickly mobilized by attackers in high throughput communication networks. In this context, signal processing techniques have been applied to attack detection due to their capability to detect anomalies that are previously unknown, i.e. blind detection. This paper proposes a signal processing framework for the detection and identification of network attacks using concepts of model order selection (MOS), eigenvalues and similarity analysis. In order to validate the proposed framework, we consider network traffic datasets that contain malicious activity such as flood and port probing attacks. We propose to model the network traffic as a superposition of components, namely, user's operations (legitimate traffic), network service operation not related to the user (noise) and the malicious activity. The experiments performed in a real network and also using the DARPA 1998 public dataset show that the proposed blind detection approach achieves satisfactory levels of accuracy in terms of timely detection and identification of TCP/UDP ports under attack.

Audio authentication is a critical task in multimedia forensics demanding robust methods to detect and identify tampered audio recordings. In this paper, a new technique to detect adulterations in audio recordings is proposed by exploiting abnormal variations in the electrical network frequency (ENF) signal eventually embedded in a questioned audio recording. These abnormal variations are caused by abrupt phase discontinuities due to insertions and suppressions of audio snippets during the tampering task. First, we propose an ESPRIT-Hilbert ENF estimator in conjunction with an outlier detector based on the sample kurtosis of the estimated ENF. Next, we use the computed kurtosis as an input for a support vector machine classifier to indicate the presence of tampering. The proposed scheme, herein designated as SPHINS, significantly outperforms related previous tampering detection approaches in the conducted tests. We validate our results using the Carioca 1 corpus with 100 unedited authorized audio recordings of phone calls.

The estimation of spatial signatures and spatial frequencies is crucial for several practical applications such as radar, sonar, and wireless communications. In this paper, we propose two generalized iterative estimation algorithms to the case in which a multidimensional (R-D) sensor array is used at the receiver. The first tensor-based algorithm is an R-D blind spatial signature estimator that operates in scenarios where the source's covariance matrix is nondiagonal and unknown. The second tensor-based algorithm is formulated for the case in which the sources are uncorrelated and exploits the dual-symmetry of the covariance tensor. Additionally, a new tensor-based formulation is proposed for an L-shaped array configuration. Simulation results show that our proposed schemes outperform the state-of-the-art matrix-based and tensor-based techniques.