Zobrazeno 1 - 10
of 331
pro vyhledávání: '"Mathar, Rudolf"'
Autor:
Taghizadeh, Omid, Yang, Tianyu, Iimori, Hiroki, Abreu, Giuseppe, Cirik, Ali Cagatay, Mathar, Rudolf
In this work, we study a full-duplex (FD) cloud radio access network (C-RAN) from the aspects of infrastructure sharing and information secrecy, where the central unit utilizes FD remote radio units (RU)s belonging to the same operator, i.e., the tru
Externí odkaz:
http://arxiv.org/abs/2107.08495
In this paper, we analyze the asymptotic rate for a multi-carrier (MC) full-duplex (FD) massive multiple input multiple output (mMIMO) decode and forward (DF) relay system which serves multiple MC single-antenna half-duplex (HD) nodes. We take into a
Externí odkaz:
http://arxiv.org/abs/2011.08303
Publikováno v:
Sampling Theory, Signal Processing, Data Analysis 19, Article number: 11 (2021)
Many practical sampling patterns for function approximation on the rotation group utilizes regular samples on the parameter axes. In this paper, we relate the mutual coherence analysis for sensing matrices that correspond to a class of regular patter
Externí odkaz:
http://arxiv.org/abs/2010.02344
In this paper, we address the power allocation problem for a decode and forward (DF) relay system, where a massive multiple-input-multiple-output (mMIMO) multi-carrier (MC) base station (BS) node communicates with a MC single antenna node directly an
Externí odkaz:
http://arxiv.org/abs/1907.13381
Neural networks have been shown to be vulnerable against minor adversarial perturbations of their inputs, especially for high dimensional data under $\ell_\infty$ attacks. To combat this problem, techniques like adversarial training have been employe
Externí odkaz:
http://arxiv.org/abs/1906.00698
In this paper, we present a deep learning based wireless transceiver. We describe in detail the corresponding artificial neural network architecture, the training process, and report on excessive over-the-air measurement results. We employ the end-to
Externí odkaz:
http://arxiv.org/abs/1905.10468
In this paper, {the goal is to design deterministic sampling patterns on the sphere and the rotation group} and, thereby, construct sensing matrices for sparse recovery of band-limited functions. It is first shown that random sensing matrices, which
Externí odkaz:
http://arxiv.org/abs/1904.11596
Autor:
Zandi, Ehsan, Mathar, Rudolf
This work estimates the position and the transmit power of multiple co-channel wireless transmitters under model uncertainties. The model uncertainties include the number of the targets and the parameters of the path-loss model which enable the syste
Externí odkaz:
http://arxiv.org/abs/1903.03517
Recently, there has been an abundance of works on designing Deep Neural Networks (DNNs) that are robust to adversarial examples. In particular, a central question is which features of DNNs influence adversarial robustness and, therefore, can be to us
Externí odkaz:
http://arxiv.org/abs/1901.10371
Group-sparsity is a common low-complexity signal model with widespread application across various domains of science and engineering. The recovery of such signal ensembles from compressive measurements has been extensively studied in the literature u
Externí odkaz:
http://arxiv.org/abs/1901.06214