Nyquist sinc-pulse shaping provides spectral efficiencies close to the theoretical limit. In this paper we discuss the analogy to optical orthogonal frequency division multiplexing and compare both techniques with respect to spectral efficiency and peak to average power ratio. We then show that using appropriate algorithms, Nyquist pulse shaped modulation formats can be encoded on a single wavelength at speeds beyond 100 Gbit/s in real-time. Finally we discuss the proper reception of Nyquist pulses. ©2011 Optical Society of America

Abstract-We demonstrate single laser 32.5 Tbit/s 16QAM Nyquist WDM transmission over a total length of 227 km of SMF-28 without optical dispersion compensation. A number of 325 optical carriers are derived from a single laser and encoded with dualpolarization 16QAM data using sinc-shaped Nyquist pulses. As we use no guard bands, the carriers have a spacing of 12.5 GHz equal to the symbol rate or Nyquist bandwidth of the data. We achieve a net spectral efficiency of 6.4 bit/s/Hz using a softwaredefined transmitter, which generates the electric drive-signals for the electro-optic modulator in realtime.

Understanding of processes and factors influencing slope stability is essential for assessing the stability of potentially hazardous slopes. Passive monitoring of acoustic emissions and microseismology provides subsurface information on fracturing (timing and identification of the mechanism) and therefore complement surface displacement data. This study investigates for the first time acoustic and microseismic signals generated in steep, fractured bedrock permafrost, covering the broad frequency range of 1 − 105 Hz. The analysis of artificial forcing experiments using a rebound hammer in a controlled setting led to two major findings: First, statistically insignificant cross correlation between signals indicates that waveforms change strongly with propagation distance. Second, a significant amplification is found in the frequency band 33–67 Hz. This finding is strongly supported by evidence from artificial rockfall events and more importantly by naturally occurring fracture events identified in fracture displacement data. Thus, filtering this frequency band enables enhanced detection of microseismic events relevant for slope stability assessment. The analysis of 2‐year time series in this frequency band further suggests that the detected energy rate baseline of all automatically triggered events using the STA/LTA algorithm is not sensitive to temperature forcing, an observation of primary importance for long‐term data collection, analysis, and interpretation. The event detection in the established frequency band is not only improved but also not affected by the short‐ and long‐term temperature changes in such a rapidly changing environment.

Abstract. The PermaSense project is an ongoing interdisciplinary effort between geo-science and engineering disciplines and started in 2006 with the goals of realizing observations that previously have not been possible. Specifically, the aims are to obtain measurements in unprecedented quantity and quality based on technological advances. This paper describes a unique >10-year data record obtained from in situ measurements in steep bedrock permafrost in an Alpine environment on the Matterhorn Hörnligrat, Zermatt, Switzerland, at 3500 ma.s.l. Through the utilization of state-of-the-art wireless sensor technology it was possible to obtain more data of higher quality, make these data available in near real time and tightly monitor and control the running experiments. This data set (https://doi.org/10.1594/PANGAEA.897640, Weber et al., 2019a) constitutes the longest, densest and most diverse data record in the history of mountain permafrost research worldwide with 17 different sensor types used at 29 distinct sensor locations consisting of over 114.5 million data points captured over a period of 10 or more years. By documenting and sharing these data in this form we contribute to making our past research reproducible and facilitate future research based on these data, e.g., in the areas of analysis methodology, comparative studies, assessment of change in the environment, natural hazard warning and the development of process models. Finally, the cross-validation of four different data types clearly indicates the dominance of thawing-related kinematics.

In natural hazard warning systems fast decision making is vital to avoid catastrophes. Decision making at the edge of a wireless sensor network promises fast response times but is limited by the availability of energy, data transfer speed, processing and memory constraints. In this work we present a realization of a wireless sensor network for hazard monitoring based on an array of eventtriggered single-channel micro-seismic sensors with advanced signal processing and characterization capabilities based on a novel co-detection technique. On the one hand we leverage an ultra-low power, threshold-triggering circuit paired with on-demand digital signal acquisition capable of extracting relevant information exactly and efficiently at times when it matters most and consequentially not wasting precious resources when nothing can be observed. On the other hand we utilize machine-learning-based classification implemented on low-power, off-the-shelf microcontrollers to avoid false positive warnings and to actively identify humans in hazard zones. The sensors' response time and memory requirement is substantially improved by quantizing and pipelining the inference of a convolutional neural network. In this way, convolutional neural networks that would not run unmodified on a memory constrained device can be executed in real-time and at scale on low-power embedded devices. A field study with our system is running on the rockfall scarp of the Matterhorn Hörnligrat at 3500 m a.s.l. since 08/2018.

To measure the noise performance of highly sensitive SQUID magnetometer systems directly is nearly impossible due to superimposed external noise. In magnetically unshielded environments in particular one needs sophisticated methods in order to get an estimate of the intrinsic noise. We compare different approaches to estimate the noise of our latest SQUID magnetometer systems in the Earth's magnetic field and compare the results with measurements in magnetic (and superconductive) shielding.

We investigate the performance and DSP resource requirements of digitally generated OFDM and sinc-shaped Nyquist pulses. The two multiplexing techniques are of interest as they offer highest spectral efficiency. The comparison aims at determining which technology performs better with limited processing capacities of state-of-the-art FPGAs. It is shown that a novel Nyquist pulse shaping technique, based on look-up tables requires lower resource count than equivalent IFFT-based OFDM signal generation while achieving similar performance with low inter-channel guard-bands in ultra-dense WDM. Our findings are based on a resource assessment of selected DSP implementations in terms of both simulations and experimental validations. The experiments were performed with real-time software-defined transmitters using a single or three optical carriers.

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