Christian Scheunert

Secrecy Outage in MISO Systems With Partial Channel Information

Secrecy on the physical layer is a promising technique to simplify the overall cross-layer secrecy concept. In many recent works on the multiple antenna wiretap channel, perfect channel state information to the intended receiver as well as the passive eavesdropper are assumed. In this paper, the transmitter has only partial information about the channel to the eavesdropper, but full information on the main channel to the intended receiver. The applied channel model is the flat-fading multiple-input single-output wiretap channel. We minimize the outage probability of secure transmission under single-stream beamforming and the use of artificial noise in the null space of the main channel. Furthermore, we derive a suboptimal beamforming scheme based on a Markov bound, which performs reasonably well. The results generalize the cases with perfect as well as without channel state information of the eavesdropper channel. Numerical simulations illustrate the secrecy outage probability over the degree of channel knowledge and confirm the theoretical results.

Weak Secrecy in the Multiway Untrusted Relay Channel With Compute-and-Forward

We investigate the problem of secure communications in a Gaussian multiway relay channel applying the compute-and-forward scheme under usage of nested lattice codes. All nodes employ half-duplex operation and can exchange confidential messages only via an untrusted relay. The relay is assumed to be honest but curious, i.e., an eavesdropper that conforms to the system rules and applies the intended relaying scheme. We start with the general case of the single-input multiple-output L-user multiway relay channel and provide an achievable secrecy rate region under a weak secrecy criterion. We show that the securely achievable sum rate is equivalent to the difference between the computation rate and the multiple access channel (MAC) capacity. In particular, we show that all nodes must encode their messages such that the common computation rate tuple falls outside the MAC capacity region of the relay. We provide results for the single-input single-output and the multiple-input single-input L-user multiway relay channel as well as the two-way relay channel. We discuss these results and show the dependence between channel realization and achievable secrecy rate. We further compare our result to available results in the literature for different schemes and show that the proposed scheme operates close to the compute-and-forward rate without secrecy.

An efficient branch-and-bound algorithm for compute-and-forward

Compute-and-forward is a framework for reliable physical layer network coding introduced by Nazer and Gastpar. Instead of decoding single messages, it decodes linear combinations of messages with the help of nested lattice codes. Nazer and Gastpar derived an achievable rate for each node depending on the channel coefficients and the desired equation coefficients. However, it is open how to choose the coefficient vector with the equation coefficients. We provide a branch-and-bound algorithm that calculates the coefficient vector, which results in the highest computation rate at a single node. We implemented the algorithm in Matlab and compared the number of iterations to the number of needed iterations if we use a complete search over all possible vectors.

Beamforming for secrecy rate maximization under outage constraints and partial CSI

Secrecy on the physical layer is a promising technique to simplify the overall cross-layer secrecy concept. In many recent works on the multiple antenna wiretap channel, perfect channel state information to the intended receiver as well as the passive eavesdropper are assumed. In this work, the transmitter has only partial information about the channel to the eavesdropper, but full information on the main channel to the intended receiver. The applied channel model is the flat-fading multiple-input single-output wiretap channel. We minimize the outage probability of secure transmission under single-stream beamforming. Additionally, we derive a suboptimal beamforming scheme based on a Markov bound, which performs reasonably well. The results generalize the cases with perfect as well as without channel state information of the eavesdropper channel. Numerical simulations illustrate the secrecy outage probability over the degree of channel knowledge and confirm the theoretical results.

Noise mitigated compressed sensing

Recently, compressed sensing (CS) is of major interest in the area of communication and measurement. CS technique is a subtle mathematical application in practice, which facilitates the signal acquisition and signal processing dramatically. It consists of the two phases: signal projection and signal recovery. Regarding the signal recovery often it is an l1 optimization process in terms of a sparse regularized least squares. In this work, we introduce the noise-mitigated least squares (NMLS) to improve the CS signal recovery performance in case of suboptimal regularization parameter λ. Both theory and empirical results show that NMLS is a promising method over state-of the-art standard regularized CS procedures.

Confidential Network Coding: Physical Layer vs. Network Layer

In all kind of information exchange, security is essential. One protection goal that has to be enforced is confidentiality. In state-of-the-art protocols, messages are encrypted before they are transmitted to ensure their confidentiality. However, incorporating novel technologies like network coding allows for more efficient solutions. Within this article, we compare different solutions for confidential communication by means of network coding at physical layer and at network layer. We discuss security, efficiency, and computational complexity of these approaches. The results allow to draw conclusions about the choice of a suited communication scheme depending on the system model and the relevant parameters.

Energy Models for Communication of Future Computing Platforms

Energy efficiency is an essential requirement on future computer architectures. Thereby, the efficiency of the communication will play an important role. Within this paper, we present an energy model for a unicast multi-hop communication. The model allows to derive predictions about the energy of a future computing platform. Further, it can be used to identify which components of the system or tasks related to communication have a significant influence on the overall energy and, hence, require special attention in the design phase. We discuss how values for processing delays and power consumption can be determined for a future computing platform and present values for a target platform. The energy model is applied to derive energy predictions for this platform.

Analysis of Parallel Applications on a High Performance-Low Energy Computer

In this paper, we propose a holistic approach for the analysis of parallel applications on a high performance–low energy computer (called the HAEC platform). The HAEC platform is currently under design and refers to an architecture in which multiple 3-D stacked massively parallel processor chips are optically interconnected on a single board and multiple parallel boards are interconnected using short-range high-speed wireless links. Although not exclusively targeting high performance computing (HPC), the HAEC platform aims to deliver high performance at low energy costs, which are essential features for future HPC platforms. At the core of the proposed approach is a trace-driven simulator called haec_sim which we developed to simulate the behavior of parallel applications running on this hardware. We investigate several mapping layouts to assign the parallel applications to the HAEC platform. We concentrate on analyzing the communication performance of the HAEC platform running parallel applications. The simulator can employ two communication models: dimension order routing (DOR) and practical network coding (PNC). As a first example of the usefulness of the proposed holistic analysis approach, we present simulation results using these communication models on a communication-intensive parallel benchmark. These results highlight the potential of the mapping strategies and communication models for analyzing the performance of various types of parallel applications on the HAEC platform. This work constitutes the first step towards more complex simulations and analyses of performance and energy scenarios than those presented herein.

Using LTI Dynamics to Identify the Influential Nodes in a Network

Networks are used for modeling numerous technical, social or biological systems. In order to better understand the system dynamics, it is a matter of great interest to identify the most important nodes within the network. For a large set of problems, whether it is the optimal use of available resources, spreading information efficiently or even protection from malicious attacks, the most important node is the most influential spreader, the one that is capable of propagating information in the shortest time to a large portion of the network. Here we propose the Node Imposed Response (NiR), a measure which accurately evaluates node spreading power. It outperforms betweenness, degree, k-shell and h-index centrality in many cases and shows the similar accuracy to dynamics-sensitive centrality. We utilize the system-theoretic approach considering the network as a Linear Time-Invariant system. By observing the system response we can quantify the importance of each node. In addition, our study provides a robust tool set for various protective strategies.

On modeling epidemics in networks using linear time-invariant dynamics

Can linear time-invariant dynamics be used to model the epidemics on the networks? This paper shows that this is indeed possible. Given the topology of a network in terms of an undirected graph we form a state space representation of a linear system to study the behavior of this network and to compare calculations against simulations of epidemics. In particular, an epidemic modeling approach based on systems theory usable even for lager networks is introduced and its potential is demonstrated. Also, methods to form the state variables of a corresponding LTI system are proposed. Presented results show that this approach is highly effective to evaluate epidemic dynamics analytically in every discrete time step omitting agent-based simulations. Moreover, it is shown that it can be used for network analysis and network optimization against virus spreading. This opens the door for using systems theory tools in network analysis.