Lecture

Wireless Receivers: Gaussian Noise and Error Probability Estimation

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In course

EE-442: Wireless receivers: algorithms and architectures

The students will learn about the basic principles of wireless communication systems, including transmission and modulation schemes as well as the basic components and algorithms of a wireless receiver. They develop an understanding for the wireless channe ...

Description

This lecture covers the analysis of wireless receivers in the presence of Gaussian noise, focusing on error probability estimation and the minimization principle. The instructor explains the assumptions, calculations, and considerations for complex Gaussian noise models, providing insights into maximizing the signal-to-noise ratio and optimizing detection performance.

Instructor

Andreas Peter Burg

Andreas Burg was born in Munich, Germany, in 1975. He received his Dipl.-Ing. degree in 2000 from the Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland. He then joined the Integrated Systems Laboratory of ETH Zurich, from where he graduated with the Dr. sc. techn. degree in 2006. In 1998, he worked at Siemens Semiconductors, San Jose, CA. During his doctoral studies, he was an intern with Bell Labs Wireless Research for a total of one year. From 2006 to 2007, he held positions as postdoctoral researcher at the Integrated Systems Laboratory and at the Communication Theory Group of the ETH Zurich. In 2007 he co-founded Celestrius, an ETH-spinoff in the field of MIMO wireless communication, where he was responsible for the ASIC development as Director for VLSI. In January 2009, he joined ETH Zurich as SNF Assistant Professor and as head of the Signal Processing Circuits and Systems group at the Integrated Systems Laboratory. In January 2011, he became a Tenure Track Assistant Professor at the Ecole Polytechnique Federale de Lausanne (EPFL) where he is leading the Telecommunications Circuits Laboratory in the School of Engineering. In June 2018 he was promoted to the role of a Tenured Associate Professor. In 2000, Mr. Burg received the Willi Studer Award and the ETH Medal for his diploma and his diploma thesis, respectively. Mr. Burg was also awarded an ETH Medal for his Ph.D. dissertation in 2006. In 2008, he received a 4-years grant from the Swiss National Science Foundation (SNF) for an SNF Assistant Professorship. In his professional career, Mr. Burg was involved in the development of more than 25 ASICs. He is a member of the IEEE and of the European Association for Signal Processing (EURASIP). Research interests and expertise

Circuits and systems for telecommunications (wireless and wired)
Prototyping and silicon implementation of new communication technologies
Development of communication algorithms and optimization for hardware implementation
Low-power VLSI signal processing for communications and other applications
Digital integrated circuits
Circuits for image and video processing

Official source

Ontological neighbourhood

Information engineering

Signal processing: Digital image processing

Related concepts (29)

Wireless power transfer

Wireless power transfer (WPT), wireless power transmission, wireless energy transmission (WET), or electromagnetic power transfer is the transmission of electrical energy without wires as a physical link. In a wireless power transmission system, an electrically powered transmitter device generates a time-varying electromagnetic field that transmits power across space to a receiver device; the receiver device extracts power from the field and supplies it to an electrical load.

Wireless access point

In computer networking, a wireless access point, or more generally just access point (AP), is a networking hardware device that allows other Wi-Fi devices to connect to a wired network. As a standalone device, the AP may have a wired connection to a router, but, in a wireless router, it can also be an integral component of the router itself. An AP is differentiated from a hotspot which is a physical location where Wi-Fi access is available.

Probability of error

In statistics, the term "error" arises in two ways. Firstly, it arises in the context of decision making, where the probability of error may be considered as being the probability of making a wrong decision and which would have a different value for each type of error. Secondly, it arises in the context of statistical modelling (for example regression) where the model's predicted value may be in error regarding the observed outcome and where the term probability of error may refer to the probabilities of various amounts of error occurring.

Signal-to-noise ratio

Signal-to-noise ratio (SNR or S/N) is a measure used in science and engineering that compares the level of a desired signal to the level of background noise. SNR is defined as the ratio of signal power to noise power, often expressed in decibels. A ratio higher than 1:1 (greater than 0 dB) indicates more signal than noise. SNR is an important parameter that affects the performance and quality of systems that process or transmit signals, such as communication systems, audio systems, radar systems, imaging systems, and data acquisition systems.

Noise (signal processing)

In signal processing, noise is a general term for unwanted (and, in general, unknown) modifications that a signal may suffer during capture, storage, transmission, processing, or conversion. Sometimes the word is also used to mean signals that are random (unpredictable) and carry no useful information; even if they are not interfering with other signals or may have been introduced intentionally, as in comfort noise. Noise reduction, the recovery of the original signal from the noise-corrupted one, is a very common goal in the design of signal processing systems, especially filters.

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