Rick FritschekUniversität Siegen
Rick Fritschek
Dr.-Ing.
About
31
Publications
910
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157
Citations
Introduction
Additional affiliations
October 2019 - present
Position
- PostDoc Position
Description
- Principal Investigator of the DFG-funded project "Machine Learning for Physical Layer Security" (jointly with Rafaell Schaefer from TU Berlin)
May 2019 - present
Position
- PostDoc Position
Description
- Working on applied ML/DL for communication systems and security
October 2015 - April 2019
Position
- Research Associate
Description
- PhD Student until 2018, Postdoc until 2019
Publications
Publications (31)
The Jensen inequality is a widely used tool in a multitude of fields, such as for example information theory and machine learning. It can be also used to derive other standard inequalities such as the inequality of arithmetic and geometric means or the H\"older inequality. In a probabilistic setting, the Jensen inequality describes the relationship...
The use of deep learning-based techniques for approximating secure encoding functions has attracted considerable interest in wireless communications due to impressive results obtained for general coding and decoding tasks for wireless communication systems. Of particular importance is the development of model-free techniques that work without knowl...
Deep learning based physical layer design, i.e., using dense neural networks as encoders and decoders, has received considerable interest recently. However, while such an approach is naturally training data-driven, actions of the wireless channel are mimicked using standard channel models, which only partially reflect the physical ground truth. Ver...
End-to-end deep learning for communication systems , i.e., systems whose encoder and decoder are learned, has attracted significant interest recently, due to its performance which comes close to well-developed classical encoder-decoder designs. However, one of the drawbacks of current learning approaches is that a differentiable channel model is ne...
End-to-end deep learning for communication systems, i.e., systems whose encoder and decoder are learned, has attracted significant interest recently, due to its performance which comes close to well-developed classical encoder-decoder designs. However, one of the drawbacks of current learning approaches is that a differentiable channel model is nee...
End-to-end learning of communication systems with neural networks and particularly autoencoders is an emerging research direction which gained popularity in the last year. In this approach, neural networks learn to simultaneously optimize encoding and decoding functions to establish reliable message transmission. In this paper, this line of thinkin...
Recently, the Hierarchical Hard Thresholding Pursuit (HiHTP) algorithm was introduced to optimally exploit the hierarchical sparsity structure in joint user activity and channel detection problems, occurring e.g. in 5G massive Machine-type Communications (mMTC) scenarios. In this paper, we take a closer look at the performance of HiHTP under noise...
The Internet of Things and specifically the Tactile Internet give rise to significant challenges for notions of security. In this work, we introduce a novel concept for secure massive access. The core of our approach is a fast and low-complexity blind deconvolution algorithm exploring a bi-linear and hierarchical compressed sensing framework. We sh...
The Internet of Things and specifically the Tactile Internet give rise to significant challenges for notions of security. In this work, we introduce a novel concept for secure massive access. The core of our approach is a fast and low-complexity blind deconvolution algorithm exploring a bi-linear and hierarchical compressed sensing framework. We sh...
We study deterministic approximations of the Gaussian two-user multiple access wiretap channel (G-MAC-WT) and the Gaussian wiretap channel with a helper (G-WT-H). These approximations enable results beyond the recently shown 2/3 and 1/2 secure degrees of freedom (s.d.o.f.) for the G-MAC-WT and the G-WT-H, respectively. While the s.d.o.f. were obtai...
Recently, the Hierarchical Hard Thresholding Pur-
suit (HiHTP) algorithm was introduced to optimally exploit
the hierarchical sparsity structure in joint user activity and
channel detection problems, occurring e.g. in 5G massive Massive
Machine-type Communications (mMTC) scenarios. In this paper,
we take a closer look at the performance of HiHTP fo...
Recent investigations have shown sum capacity results within a constant bit-gap for several channel models, e.g. the two-user Gaussian interference channel (G-IC), k-user G-IC or the Gaussian X-channel. This has motivated investigations of interference-limited multi-user channels, for example, the Gaussian interfering multiple access channel (G-IMA...
It is well-known that wireless channel reciprocity together with fading can be exploited to generate a common secret key between two legitimate communication partners. This can be achieved by exchanging known deterministic pilot signals between both partners from which the random fading gains can be estimated and processed. However, the entropy and...
We study a deterministic approximation of the two-user multiple access wiretap channel. This approximation enables results beyond the recently shown $\tfrac{2}{3}$ secure degrees of freedom (s.d.o.f.) for the Gaussian multiple access channel. While the s.d.o.f. were obtained by real interference alignment, our approach uses signal-scale alignment....
Recent investigations have shown that multi-user gain can be enabled in frequency-flat, time-invariant, single-antenna interfering multiple access channels. This chapter will provide an overview of results, which lead to these recent key results. We will present conclusions of two deterministic approximation models and discuss the advantages and di...
Recent investigations have shown that the sum secure degrees of freedom of the Gaussian wiretap channel with a helper is $\tfrac{1}{2}$. The achievable scheme for this result is based on the real interference alignment approach. While providing a good way to show degrees of freedom results, this technique has the disadvantage of relying on the Khin...
Presentation for the publication ”Constant-Gap Sum-Capacity Approximation of the Deterministic Interfering Multiple Access Channel”
The MAC-BC duality of information theory and wireless communications is an
intriguing concept for efficient algorithm design. However, no concept is known
so far for the important cellular channel. To make progress on this front, we
consider in this paper the linear deterministic cellular channel. In
particular, we prove duality of a network with t...
There has been major progress over the last decade in understanding the
classical interference channel (IC). Recent key results show that constant bit
gap capacity results can be obtained from linear deterministic models (LDMs).
However, it is widely unrecognized that the time-invariant, frequency-flat
cellular channel, which contains the IC as a s...
Projects
Projects (2)
The project AutoKEY brings wireless channel based key generation into WiSHFUL testbed with the following major objectives:
- To evaluate and validate the availability of 3x3 MIMO complex-valued measurements on off-the-shelf WiSHFUL testbed hardware for wireless channel based key generation.
- To define and evaluate suitable key extraction metrics for the measurements and improve on the existing 6doku scheme. Specifically, AutoKEY protocol shall reduce the large number of packets and corresponding information leakage in the 6doku protocol which is required to generate a sufficiently long key of at least 128 bits
- To enhance the randomness/entropy of the collected key material to prevent for weak cryptographic keys by utilizing AutoKEY MIMO channel measurements and respective metrics.
