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Articles by Rick Fritschek
MinGRU-Based Encoder for Turbo Autoencoder Frameworks
Abstract Early neural channel coding approaches leveraged dense neural networks with one-hot encodings to design adaptive encoder-decoder pairs, improving block error rate (BLER) and automating the design process. However, these methods struggled with scalability as the size of message sets and block lengths increased.
Robust Generation of Channel Distributions with Diffusion Models
Robust Generation of Channel Distributions with Diffusion Models Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
Deep Learning for Channel Coding via Neural Mutual Information Estimation
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 needed for the training of the underlying neural networks.
On deterministic models for capacity approximations in interference networks and information theoretic security
Contributors Rick Fritschek - , Technical University of Berlin (Author) Details Original language German Qualification level Dr.-Ing.
Performance of Hierarchical Sparse Detectors for Massive MTC
Contributors Gerhard Wunder - , Free University of Berlin (Author) Ingo Roth - , Free University of Berlin (Author) Rick Fritschek - , Free University of Berlin (Author) Jens Eisert - , Free University of Berlin (Author) Abstract Recently, a new class of so-called \emph{hierarchical thresholding algorithms} was introduced to optimally exploit the sparsity structure in joint user activity and channel detection problems.
Constant-gap sum-capacity approximation of the deterministic interfering multiple access channel
Recent investigations have shown that multi-user gain can be enabled in frequency-flat time-invariant single-antenna cellular networks, for example the interfering multiple access channel (IMAC). These investigations have shown gain beyond results through treating interference as noise (TIN) techniques in the weak interference regime, rendering TIN sub-optimal for these networks.
Deterministic IMAC revisited: Constant-gap capacity in the weak interference case
Recent investigations have shown that approximations of certain channels by the linear deterministic model (LDM) are sub-optimal in some cases. Replacing the LDM by a more sophisticated deterministic model possibly results in improvements of previous results. An example is use of the lower triangular deterministic model (LTDM) to replace the LDM. Due to the integrated dependence on the fine channel gains, results can be obtained which were not previously possible.
Shielding calculations of a CASTOR with MCNP5
Shielding calculations of a CASTOR with MCNP5 Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed
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