05 Fakultät Informatik, Elektrotechnik und Informationstechnik

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6

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Institute: search.filters.UBSInstitut.Institut für NachrichtenübertragungStart date: 2020

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Now showing 1 - 5 of 5
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    Low-complexity adaptive digital equalizers for electronic dispersion compensation in optical fiber links
    (2022) Efinger, Daniel; Speidel, Joachim (Prof. Dr.-Ing.)
    This thesis addresses electronic equalization of intersymbol interference caused by chromatic and polarization mode dispersion in intensity-modulated optical communication links with direct detection. The simple and cost-efficient system setup is, even at high bit rates of 40 Gbit/s and beyond, of interest for short-haul optical links in metropolitan, aggregation or local area networks. Therefore, this thesis investigates preferably simple and low-complexity equalizer structures, which are able to compensate well for the nonlinear characteristics and influences of the intensity-modulated optical communication link with direct detection. Starting with system modeling and the introduction to different equalization methods, we identify low-complexity feed-forward and decision-feedback equalizers in the first part of this thesis. We further put their chromatic and polarization mode dispersion compensation performance to the broader context by comparison to maximum likelihood sequence estimation. Finally, we come to the investigation of adaptation algorithms for equalizer coefficient adjustment, which accounts for the time-variant nature of polarization mode dispersion, while still targeting preferably simple and efficient realization.
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    Spectrally efficient transmitter diversity scheme for optical satellite feeder links
    (2024) Mustafa, Ahmad; Ten Brink, Stephan (Prof. Dr.-Ing.)
    There is an ever-growing demand for increasing the data traffic in the order of Tb/s to the geostationary (GEO) satellites. It will help connect numerous users on the ground who do not have access to internet service. This high throughput can be achieved using multiple laser beams in the uplink and combining them with the dense wavelength division multiplexing technique. However, optical signals propagating through the turbulent atmosphere to GEO satellites suffer from the intensity and phase fluctuations. Additionally, atmospherically induced beam wander leads to pointing errors at the satellite resulting in deep fades, hence loss of signal power which can fall below the receiver sensitivity making the communication impossible. The problem of photon scarcity can be tackled by using advanced power-efficient coherent modulation formats which are highly sensitive, but they come at the expense of increased system complexity. Therefore, in this thesis, only an intensity modulation and direct detection scheme called non-return-to-zero on-off keying is considered, which is relatively easier to implement in free-space optical communications. To mitigate the atmospheric fades, a transmitter diversity technique called MISO is considered for GEO feeder links for reliable signal reception at the satellite. It requires multiple laser beams to propagate through uncorrelated channels, which can be achieved by having a physical separation between the transmitting telescopes greater than the atmospheric coherence length. This thesis is divided into two main parts: The first part includes the quantitative analysis of the MISO scheme with no spectral overlapping between the neighboring signals. Here, the fading consists of log-normal scintillation and residual beam pointing jitter. The bit error rate (BER) for the single-input single-output and MISO systems is obtained using the fading statistics of the atmosphere and considering the receiver model of a commercially available 10Gb/s photoreceiver with an avalanche photodiode. For the given atmospheric conditions and residual beam pointing jitter, the transmit power of each beam is optimized to minimize the overall power scintillation index and maximize the BER gain. The second part of the thesis aims at increasing the spectral efficiency of the transmission system where SSB signals are generated using optical filters to achieve the desired BER performance. A laboratory experiment with a 32Gb/s system is performed in a back-to-backup setup to optimize the SSB signals using a passive filtering technique. Here, the filter bandwidth and the center frequency from the carrier are optimized to get the error-free performance. Finally, simulations are performed where the optimized upper sideband and lower sideband from the respective double-sideband signals are obtained, and then they are propagated through the atmospheric channel, which consists of log-normal scintillation effects and phase piston. The carrier separation between the two signals is selected such to emulate constructive and destructive interference due to the slowly varying phase piston. A diversity gain of 2.3dB is achieved, which shows the efficacy of using transmitter diversity in a GEO uplink channel.
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    Augmenting cellular networks with sensing and positioning : algorithm development and validation with proof of concepts
    (2024) Henninger, Marcus; Ten Brink, Stephan (Prof. Dr.-Ing.)
    Since at least Long Term Evolution (LTE), cellular networks have been evolving towards adding functionalities that go beyond communication services in the traditional sense. This thesis focuses on two of the main concepts of this trend: positioning of user equipments by leveraging the transmission of radio signals and the cellular infrastructure, and Integrated Sensing and Communication (ISAC), which is a comparatively new design paradigm that aims at equipping mobile networks with radar-like capabilities. In contrast to positioning, sensing allows to also obtain information about non-transmitting objects, i.e., those that are not part of the network. Many approaches used in the context of ISAC and positioning resort to spectral estimation techniques that exploit the properties of the wireless channel to extract information from incoming radio signals. With this in mind, one of the contributions of this work is an algorithm based on Multiple Signal Classification (MUSIC), which is tailored to the requirements imposed by 5G numerologies and makes joint estimation of range and angle computationally feasible. As positioning in cellular networks can look back on multiple years of research, various concepts and fairly mature solutions are already in place. For this reason, the investigations in this thesis focus on extending existing algorithms that are based on probabilistic time of arrival and angle of arrival localization. In particular, a robust initialization routine is presented that limits outliers and allows finding the global maximum in an efficient manner. The advantages of the solution are demonstrated with measurements from a 5G positioning proof of concept (PoC) in a factory-like environment. ISAC research, on the other hand, is still in a rather early phase. This work deals with monostatic sensing systems utilizing the principles of orthogonal frequency division multiplexing (OFDM) radar, as they presumably represent the first realizations of ISAC deployments in upcoming cellular standards. In that context, an analytical model is adopted to estimate the performance and limiting factors of envisioned ISAC use cases based on to be expected hardware features in the coming years and under consideration of available signal parametrization options. One important ISAC research branch is the suppression of clutter, i.e., of reflections from objects that are not of interest for the sensing task and can thus be regarded as interference. Methods for handling clutter in ISAC applications are extensively discussed in this thesis, which overcome several shortcomings of prior art approaches. The introduced algorithms enable both the acquisition and tracking of information about clutter components, as well as their efficient removal in real-time. The benefits of the techniques are illustrated not only by means of different simulation campaigns, but also using an ISAC PoC for pedestrian tracking experiments in a lab environment.
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    Efficient FPGA implementation of an ANN-based demapper using cross-layer analysis
    (2022) Ney, Jonas; Hammoud, Bilal; Dörner, Sebastian; Herrmann, Matthias; Clausius, Jannis; Ten Brink, Stephan; Wehn, Norbert
    In the field of communication, autoencoder (AE) refers to a system that replaces parts of the traditional transmitter and receiver with artificial neural networks (ANNs). To meet the system performance requirements, it is necessary for the AE to adapt to the changing wireless-channel conditions at runtime. Thus, online fine-tuning in the form of ANN-retraining is of great importance. Many algorithms on the ANN layer are developed to improve the AE’s performance at the communication layer. Yet, the link of the system performance and the ANN topology to the hardware layer is not fully explored. In this paper, we analyze the relations between the design layers and present a hardware implementation of an AE-based demapper that enables fine-tuning to adapt to varying channel conditions. As a platform, we selected field-programmable gate arrays (FPGAs) which provide high flexibility and allow to satisfy the low-power and low-latency requirements of embedded communication systems. Furthermore, our cross-layer approach leverages the flexibility of FPGAs to dynamically adapt the degree of parallelism (DOP) to satisfy the system-level requirements and to ensure environmental adaptation. Our solution achieves 2000× higher throughput than a high-performance graphics processor unit (GPU), draws 5× less power than an embedded central processing unit (CPU) and is 5800× more energy efficient compared to an embedded GPU for small batch size. To the best of our knowledge, such a cross-layer design approach combined with FPGA implementation is unprecedented.
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    Deep learning for coherent nonlinear optical communications
    (2025) Uhlemann, Tim; Ten Brink, Stephan (Prof. Dr.-Ing.)
    Communication, in general, is the transport or exchange of information between two geographically distant points. The higher this distance the more sophisticated methods and materials have to be applied to overcome the same. Current state of the art for long-haul communication are optical fibers, that form the crucial backbone of our global, interlinked and digital society, connecting data-centers, factories and homes. Nevertheless, like all other physical media also the optical fiber induces the ever-present attenuation to the information carrying electromagnetic wave what, finally, limits the achievable throughput. This results in the need for higher input powers provided by (laser) diodes. Over the past decades physical and computational limitations led to an operation of the optical fiber in the linear regime, where attenuation as well as dispersion, and, thus, their compensation, constituted the major challenges. As this has changed recently, the investigation of nonlinearity gained more attraction. This work focuses on the pre-distortion and post-equalization of such nonlinear effects that limit the overall efficiency. Thereby, methods from deep-learning are applied and compared to conventional methods. As those, in general, lack of interpretability, here, the concept of so-called architectural templates is proposed that combines well-known, and, from theory derived, concepts with the ones provided by native deep-learning. This way, the results can be analyzed with proven methods from the field of signal processing. While learning of the receiver is a straight-forward, but still complex, task, even more challenging is learning the transmitter as the optimization, i.e., gradient flow, has to be conducted (backwards) through the optical fiber channel. Here, all learnings and evaluations are performed on an accurate simulation of the optical fiber, what enables an isolation of the investigated nonlinear effects. It results that learning over such accurate nonlinear models is possible as the gradient is preserved and the error can be back-propagated. Further, conventional linear filters for dispersion compensation can be outperformed, when being trained in the nonlinear regime. The extension to a nonlinear architectural template revealed the need for a more sophisticated training procedure proposed in this work. When considering a multi-carrier system the trainable nonlinear template for the transmitter was able to exploit additional information from the neighboring channels.