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"Simon Grimm examines new multi-microphone signal processing strategies that aim to achieve noise reduction and dereverberation. Therefore, narrow-band signal enhancement approaches are combined with broad-band processing in terms of directivity based beamforming. Previously introduced formulations of the multichannel Wiener filter rely on the second order statistics of the speech and noise signals. The author analyses how additional knowledge about the location of a speaker as well as the microphone arrangement can be used to achieve further noise reduction and dereverberation."

"This book provides a comprehensive introduction to the theory and practice of spherical microphone arrays, and was written for graduate students, researchers and engineers who work with spherical microphone arrays in a wide range of applications. The new edition includes additions and modifications, and references supplementary Matlab code to provide the reader with a straightforward start for own implementations. The book is also accompanied by a Matlab manual, which explains how to implement the examples and simulations presented in the book.The first two chapters provide the reader with the necessary mathematical and physical background, including an introduction to the spherical Fourier transform and the formulation of plane-wave sound fields in the spherical harmonic domain. In turn, the third chapter covers the theory of spatial sampling, employed when selecting the positions of microphones to sample sound pressure functions in space.Subsequent chapters highlight various spherical array configurations, including the popular rigid-sphere-based configuration. Beamforming (spatial filtering) in the spherical harmonics domain, including axis-symmetric beamforming, and the performance measures of directivity index and white noise gain are introduced, and a range of optimal beamformers for spherical arrays, including those that achieve maximum directivity and maximum robustness are developed, along with the Dolph–Chebyshev beamformer. The final chapter discusses more advanced beamformers, such as MVDR (minimum variance distortionless response) and LCMV (linearly constrained minimum variance) types, which are tailored to the measured sound field."

"Antena dengan banyak berkas pancar (multibeam) banyak dibutuhkan untuk berbagai keperluan seperti radar, pencitraan, sensor, komunikasi satelit, dan komunikasi 5G. Dalam rangka mewujudkan multibeam diperlukanlah jaringan pembentuk beam (beamforming network/ BFN). Salah satu BFN yang mempunyai banyak keunggulan adalah Rotman lens. Namun Rotman lens konvensional pada umumnya beukuran agak besar, salah satunya akibat ukuran kaki-kaki transisi antara cavity dan port transmission line yang cukup panjang. Pada penelitian ini dilakukan riset untuk mereduksi ukuran Rotman Lens pada frekuensi 2,4 GHz ISM Band dengan jumlah kaki beam port sebanyak 5 dan kaki array sebanyak 6. Ada dua metode yang diusulkan dalam penelitian ini. Metode tersebut adalah dengan menggunakan teknik Defected ground structure (DGS) dan slot dengan struktur yang sederhana dan ukuran yang sama/ seragam untuk semua port guna memangkas panjang kaki transisi Rotman lens dan meminimalkan jumlah iterasi. Hasil simulasi menunjukkan bahwa baik teknik DGS rectangular ganda maupun slot rectangular ganda berukuran sama di semua port mampu mereduksi ukuran Rotman lens. Ukuran Rotman lens dapat tereduksi menjadi 15.78 persen dibanding yang dibuat dengan metode konvensional tanpa penurunan kinerja yang berarti. Validasi dilakukan dengan memfabrikasi Rotman lens yang direduksi dengan teknik slot rectangular ganda yang terintegrasi dengan antenna array dengan elemen mikrostrip rectangular. Hasil pengukuran menunjukkan hasil yang cukup mirip dengan simulasi. Struktur yang dibuat mampu membentuk lima arah beam, yaitu main beam berada di arah ±33, ±18, dan 0 derajat dengan beda maksimal 3 derajat jika dibandingkan hasil simulasi dan maksimal 6 derajat jika dibandingkan perancangan. Bandwidth bisa mencapai lebih dari 800 MHz untuk sebagian besar port kecuali port yang paling tengah.

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Antennas with multibeam capability are needed for various purposes such as radar, imaging, sensors, satellite communications, and 5G communications. In order to realize multibeam, a beamforming network (BFN) is needed. One of the BFN that has many advantages is the Rotman lens. However, conventional Rotman lenses are generally rather large in size, one of which is due to the length of the transition legs between the cavity and the transmission line port. In this study, research was conducted to reduce the size of the Rotman Lens at the 2,4 GHz ISM Band with 5 beam ports and 6 array ports. There are two methods proposed in this research. They are to use the Defected ground structure (DGS) technique and slots with a simple structure and the same size/uniform for all ports in order to reduce the length of the Rotman lens transition leg and to minimize iteration process. The simulation results show that both the same double rectangular DGS technique and the same double rectangular slots in all ports are able to reduce the size of the Rotman lens. The size of the Rotman lens can be reduced to 15.78 percent compared to those made by conventional methods without significant performance degradation. Validation is done by fabricating a reduced Rotman lens with a double rectangular slot technique which is integrated with array antennas whose elements are rectangular microstrips. The measurement results are quite similar to the simulations. The structure made is able to form five beam directions. The directions of the main beams are ±33, ±18, and 0 degrees with a maximum difference of 3 degrees when compared to the simulation results and a maximum of 6 degrees when compared to the design calculation. Bandwidths are more than 800 MHz for most ports except the middle port."

"Signal conditioning" is a comprehensive introduction to electronic signal processing. The book presents the mathematical basics including the implications of various transformed domain representations in signal synthesis and analysis in an understandable and lucid fashion and illustrates the theory through many applications and examples from communication systems. "

"This Springerbreif introduces a threshold-based channel sparsification approach, and then, the sparsity is exploited for scalable channel training. Last but not least, this brief introduces two scalable cooperative signal detection algorithms in C-RANs. The authors wish to spur new research activities in the following important question: how to leverage the revolutionary architecture of C-RAN to attain unprecedented system capacity at an affordable cost and complexity.Cloud radio access network (C-RAN) is a novel mobile network architecture that has a lot of significance in future wireless networks like 5G. the high density of remote radio heads in C-RANs leads to severe scalability issues in terms of computational and implementation complexities. This Springerbrief undertakes a comprehensive study on scalable signal processing for C-RANs, where scalable means that the computational and implementation complexities do not grow rapidly with the network size."