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Due to technological advances in the field of radio technology and its availability, the number of interference signals in the radio spectrum is continuously increasing. Interference signals must be detected in a timely fashion, in order to maintain standards and keep emergency frequencies open. To this end, specialized (multi-channel) receivers are used for spectrum monitoring. In this paper, the performances of two different approaches for controlling the available receiver resources are compared. The methods used for resource management (ReMa) are linear frequency tuning as a heuristic approach and a Q-learning algorithm from the field of reinforcement learning. To test the methods to be investigated, a simplified scenario was designed with two receiver channels monitoring ten non-overlapping frequency bands with non-uniform signal activity. For this setting, it is shown that the Q-learning algorithm used has a significantly higher detection rate than the heuristic approach at the expense of a smaller exploration rate. In particular, the Q-learning approach can be parameterized to allow for a suitable trade-off between detection and exploration rate., Comment: 5 pages, 6 figures

With the upcoming trends in autonomous driving and urban air mobility, the number of self-navigating vehicles will increase, since they are foreseen for deliveries as well as autonomous taxis among other applications. To this end, a multitude of on-board systems for wireless communication, environment sensing, and localization will become mandatory. This is particularly true for unmanned aerial vehicles (UAVs), since participation in the airspace requires compatibility to and safe interaction with established users. A certain number of systems are already in-use and occupy defined spectra as well as installation space, which limits the freedom in the design of new systems. The miniaturization of aerial vehicles like drones for delivery services further reduces the degrees of freedom, especially in terms of size and weight of any additional equipment. Hence, in this paper a joint approach of the design of joint communication, sensing and localization for UAVs is discussed. Towards this goal, multi-mode multi-port antennas and joint waveform design are proposed as a part of the solution, when elevating autonomous driving to the third dimension.

A posteriori probability (APP) and max-log APP detection is widely used in soft-input soft-output detection. In contrast to bijective modulation schemes, there are important differences when applying these algorithms to non-bijective symbol constellations. In this letter the main differences are highlighted., Comment: 3 pages, 2 figures, 1 table

Besides mimicking bio-chemical and multi-scale communication mechanisms, molecular communication forms a theoretical framework for virus infection processes. Towards this goal, aerosol and droplet transmission has recently been modeled as a multiuser scenario. In this letter, the "infection performance" is evaluated by means of a mutual information analysis, and by an even simpler probabilistic performance measure which is closely related to absorbed viruses. The so-called infection rate depends on the distribution of the channel input events as well as on the transition probabilities between channel input and output events. The infection rate is investigated analytically for five basic discrete memoryless channel models. Numerical results for the transition probabilities are obtained by Monte Carlo simulations for pathogen-laden particle transmission in four typical indoor environments: two-person office, corridor, classroom, and bus. Particle transfer contributed significantly to infectious diseases like SARS-CoV-2 and influenza., Comment: 4 pages, 3 figures, submitted to IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Letters

Molecular communication is not only able to mimic biological and chemical communication mechanisms, but also provides a theoretical framework for viral infection processes. In this tutorial, aerosol and droplet transmission is modeled as a multiuser scenario with mobile nodes, related to broadcasting and relaying. In contrast to data communication systems, in the application of pathogen-laden aerosol transmission, mutual information between nodes should be minimized. Towards this goal, several countermeasures are reasoned. The findings are supported by experimental results and by an advanced particle simulation tool. This work is inspired by the recent outbreak of the coronavirus (COVID-19) pandemic, but also applicable to other airborne infectious diseases like influenza., Comment: 7 pages, 4 figures, 1 table, submitted to IEEE Communications Magazine for the Feature Topic on "Nano-Networking for Nano-, Micro-, and Macro-Scale Applications"

This contribution exploits the duality between a viral infection process and macroscopic air-based molecular communication. Airborne aerosol and droplet transmission through human respiratory processes is modeled as an instance of a multiuser molecular communication scenario employing respiratory-event-driven molecular variable-concentration shift keying. Modeling is aided by experiments that are motivated by a macroscopic air-based molecular communication testbed. In artificially induced coughs, a saturated aqueous solution containing a fluorescent dye mixed with saliva is released by an adult test person. The emitted particles are made visible by means of optical detection exploiting the fluorescent dye. The number of particles recorded is significantly higher in test series without mouth and nose protection than in those with a wellfitting medical mask. A simulation tool for macroscopic molecular communication processes is extended and used for estimating the transmission of infectious aerosols in different environments. Towards this goal, parameters obtained through self experiments are taken. The work is inspired by the recent outbreak of the coronavirus pandemic., Comment: 9 pages, 6 figures, submitted to IEEE Transactions on Molecular, Biological, and Multi-Scale Communications for the special issue "Section II: Molecular Communications for Diagnostics and Therapeutic Development of Infectious Diseases"

In this paper, the displacement of the phase centers of multi-mode antennas is investigated. A mathematical approach is applied in order to calculate the positions of the phase center for each mode. Using electric far field samples obtained from electromagnetic field simulation data, the coordinates of the shifted positions of the phase center relative to the physical center of the antenna are determined for each mode. Numerical results show the dependency of the phase centers of an antenna prototype as a function of the considered angle of observation.

Recently, multi-mode antennas have been studied for communication as well as localization purposes. In this work, the capabilities provided by a single planar multi-mode radiator as a steerable multi-port antenna are explored. As an original contribution, the radiation characteristics of individual groups of modes of the single radiator are combined to optimize beamforming performance. Three possible codebook realizations are studied and compared. A new optimization criterion, gain by element factor, is introduced., Comment: 4 Pages, 5 Figures. Published in N. L. Johannsen and P. A. Hoeher, "Single-Element Beamforming Using Multi-Mode Antenna Patterns," in IEEE Wireless Communications Letters, vol. 9, no. 7, pp. 1120-1123, July 2020, doi: 10.1109/LWC.2020.2983023

While on the one hand 5G and B5G networks are challenged by ultra-high data rates in wideband applications like 100+ Gbps wireless Internet access, on the other hand they are expected to support reliable low-latency Internet of Things (IoT) applications with ultra-high connectivity. These conflicting challenges are addressed in a system proposal dealing with both extremes. In contrast to most recent publications, focus is on the frequency domain below 10~GHz. Towards this goal, multi-mode antenna technology is used and different realizations, offering up to eight uncorrelated ports per radiator element, are studied. Possible baseband architectures tailored to multi-mode antennas are discussed, enabling different options regarding precoding and beamforming., Comment: 7 pages, 5 figures, 1 table. Published under: N. L. Johannsen, N. Peitzmeier, P. A. Hoeher and D. Manteuffel, "On the Feasibility of Multi-Mode Antennas in UWB and IoT Applications below 10 GHz," in IEEE Communications Magazine, vol. 58, no. 3, pp. 69-75, March 2020, doi: 10.1109/MCOM.001.1900429

Inductively coupled resonant circuits are affected by the so-called frequency splitting phenomenon at short distances. In the area of power electronics, tracking of one of the peak frequencies is state-of-the-art. In the data transmission community, however, the frequency splitting effect is often ignored. Particularly, modulation schemes have not yet been adapted to the bifurcation phenomenon. We argue that binary frequency shift keying (2-ary FSK) is a low-cost modulation scheme which well matches the double-peak voltage transfer function $H(s)$, particularly when the quality factor $Q$ is large, whereas most other modulation schemes suffer from the small bandwidths of the peaks. Additionally we show that a rectified version of 2-ary FSK, coined rectified FSK (RFSK), is even more attractive from output power and implementation points of view. Analytical and numerical contributions include the efficiency factor, the impulse response, and the bit error performance. A low-cost incoherent receiver is proposed. Theoretical examinations are supported by an experimental prototype., Comment: This is the author's version of an article that has been published in IEEE Access, vol. 7, pp. 40183-40194, Mar. 2019. The final version is available in IEEExplore at https://ieeexplore.ieee.org/document/8673753

Multi-mode antennas are an alternative to classical antenna arrays, and hence a promising emerging sensor technology for a vast variety of applications in the areas of array signal processing and digital communications. An unsolved problem is to describe the radiation pattern of multi-mode antennas in closed analytic form based on calibration measurements or on electromagnetic field (EMF) simulation data. As a solution, we investigate two modeling methods: One is based on the array interpolation technique (AIT), the other one on wavefield modeling (WM). Both methods are able to accurately interpolate quantized EMF data of a given multi-mode antenna, in our case a planar four-port antenna developed for the 6-8.5 GHz range. Since the modeling methods inherently depend on parameter sets, we investigate the influence of the parameter choice on the accuracy of both models. Furthermore, we evaluate the impact of modeling errors for coherent maximum-likelihood direction-of-arrival (DoA) estimation given different model parameters. Numerical results are presented for a single polarization component. Simulations reveal that the estimation bias introduced by model errors is subject to the chosen model parameters. Finally, we provide optimized sets of AIT and WM parameters for the multi-mode antenna under investigation. With these parameter sets, EMF data samples can be reproduced in interpolated form with high angular resolution.

In this paper, we show that a multi-mode antenna (MMA) is an interesting alternative to a conventional phased antenna array for direction-of-arrival (DoA) estimation. By MMA we mean a single physical radiator with multiple ports, which excite different characteristic modes. In contrast to phased arrays, a closed-form mathematical model of the antenna response, like a steering vector, is not straightforward to define for MMAs. Instead one has to rely on calibration measurement or electromagnetic field (EMF) simulation data, which is discrete. To perform DoA estimation, array interpolation technique (AIT) and wavefield modeling (WM) are suggested as methods with inherent interpolation capabilities, fully taking antenna nonidealities like mutual coupling into account. We present a non-coherent DoA estimator for low-cost receivers and show how coherent DoA estimation and joint DoA and polarization estimation can be performed with MMAs. Utilizing these methods, we assess the DoA estimation performance of an MMA prototype in simulations for both 2D and 3D cases. The results show that WM outperforms AIT for high SNR. Coherent estimation is superior to non-coherent, especially in 3D, because non-coherent suffers from estimation ambiguities. In conclusion, DoA estimation with a single MMA is feasible and accurate.

In this work, spatial diversity techniques in the area of multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC) are investigated. For transmitter-side spatial coding, Alamouti-type coding and repetition MIMO coding are proposed and analyzed. At the receiver-side, selection diversity, equal-gain combining, and maximum-ratio combining are studied as combining strategies. Throughout the numerical analysis, a symmetrical $2\times 2$ MIMO-DBMC system is assumed. Furthermore, a trained artificial neural network is utilized to acquire the channel impulse responses. The numerical analysis demonstrates that it is possible to achieve a diversity gain in molecular communications. In addition, it is shown that for MIMO-DBMC systems repetition MIMO coding is superior to Alamouti-type coding., Comment: Submitted work

This paper studies spatial diversity techniques applied to multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC). Two types of spatial coding techniques, namely Alamouti-type coding and repetition MIMO coding are suggested and analyzed. In addition, we consider receiver-side equal-gain combining, which is equivalent to maximum-ratio combining in symmetrical scenarios. For numerical analysis, the channel impulse responses of a symmetrical $2 \times 2$ MIMO-DBMC system are acquired by a trained artificial neural network. It is demonstrated that spatial diversity has the potential to improve the system performance and that repetition MIMO coding outperforms Alamouti-type coding.

Sparse intersymbol-interference (ISI) channels are encountered in a variety of high-data-rate communication systems. Such channels have a large channel memory length, but only a small number of significant channel coefficients. In this paper, trellis-based equalization of sparse ISI channels is revisited. Due to the large channel memory length, the complexity of maximum-likelihood detection, e.g., by means of the Viterbi algorithm (VA), is normally prohibitive. In the first part of the paper, a unified framework based on factor graphs is presented for complexity reduction without loss of optimality. In this new context, two known reduced-complexity algorithms for sparse ISI channels are recapitulated: The multi-trellis VA (M-VA) and the parallel-trellis VA (P-VA). It is shown that the M-VA, although claimed, does not lead to a reduced computational complexity. The P-VA, on the other hand, leads to a significant complexity reduction, but can only be applied for a certain class of sparse channels. In the second part of the paper, a unified approach is investigated to tackle general sparse channels: It is shown that the use of a linear filter at the receiver renders the application of standard reduced-state trellis-based equalizer algorithms feasible, without significant loss of optimality. Numerical results verify the efficiency of the proposed receiver structure., Comment: To be presented at the 2005 IEEE Int. Symp. Inform. Theory (ISIT 2005), September 4-9, 2005, Adelaide, Australia