|Introduction to MATLAB and discussion of most important commands, simulation of a simple transmission chain, channel coding (convolutional codes), coding gain, channels with multipath propagation, models of fading channels and performance for binary transmission, Orthogonal Frequency-Division Multiplexing (OFDM), interleaving, implementation of an OFDM modem.|
- Dozent/in: Marc Robert Selig
Praktikum Signalübertragung: Analog modulation techniques, Amplitude Modulation (AM), Double Side Band Suppressed Carrier (DSBSC), Single Side Band (SSB), Frequency Modulation (FM), sampling theorem (sampling and reconstruction), Digital modulation techniques, Amplitude Shift Keying (ASK), Binary Phase Shift Keying (BPSK), Frequency Shift Keying (FSK), Signal constellation for M-QAM and M-PSK, Noisy channel model, signal detection and Bit Error Rate (BER) measurement and eye pattern for noisy channel.
Mobile Radio : Deterministic and stochastic representation of mobile radio channels; Time-variant linear systems; Probability density functions of fading channels; Noise and interference; Diversity; Multichannel transmission and linear combining techniques; Spread spectrum and code-division multiple access (CDMA) systems; Hypothesis testing and minimal error probability; Sufficient statistics; Conventional detection; Near-far problem; Joint detection; Detection in asynchronous CDMA systems; Demodulation in UMTS with wideband CDMA (uplink and downlink); UMTS and LTE systems; Device-2-Device (D2D) communication using LTE; Cellular Internet of Things (IoT); LTE in V2X communication; 5G; An Introduction to Modulations and Waveforms for 5G Networks; Massive-MIMO and Basic Channel Measurement Techniques; Non Orthogonal Multiple Access (NOMA); Cognitive Radio for 5G Networks.
Signal Processing in Wireless Communications: Short sequence of lectures giving an overview over existing wireless communication systems as well as different topics on:
· Deterministic/stochastic description of space-time wireless channels
· Channel estimation and equalization
· Adaptive equalization (channel shortening)
· Multiple-input multiple-output (MIMO) and massive MIMO systems
· Orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA)
· Interference alignment
· Space-time coding
· Sphere decoding
· Adaptive beamforming
· Cooperative communication
· Cognitive radio and filter banks
· Compressive sensing and its applications in wireless communication systems
· 4G and 5G signal processing (e.g. waveform design)
We will also focus on signal processing for specific examples of wireless systems as:
· Satellite systems
· Fourth generation (4G) cellular mobile radio
· Five generation (5G) wireless networks
· Wireless backhauling of 5G
· Outdoor and indoor wireless positioning systems
· Signal Processing for Vehicular Communications
model, introduction to tasks in the DLC and MAC layer; treatment of the PHY
layer; description of communication systems for different transmission mediums:
wired, wireless, mobile, and fiber-optical transmission; impact of different
system components and other factors to the possible transmission quality (e.g.,
capacity, bit-error rate).
Digital Communication Over Fading Channels: Overview of spread spectrum based transmission (direct sequence, frequency hopping), PN sequences, transmission over fading multipath channels, channel coding for multipath channels, multiple-input multiple-output (MIMO) transmission, multiuser detection, code-division multiple access (CDMA), random access, non-orthogonal multiple access (NOMA), channel estimation for NOMA and signal processing in 5G.
Introduction to Information Theory and Coding : Fundamentals in information theory, entropy, mutual information; Shannon capacity for the discrete memoryless channel; channel coding: block codes, cyclic block codes, systematic form; soft and hard decision and performance; interleaving and code con-catenation; convolutional codes: tree and state diagrams, transfer function, distance properties; Viterbi algorithm; source coding, Huffman coding; the Lempel-Ziv algorithm; coding for analog sources, rate-distortion function; pulse-code modulation; delta-modulation, model-based source coding, linear predictive coding (LPC).
Introduction to Digital Communications: Fundamentals in probability Theory, Fourier transform, stochastic processes, sampling theorem (sampling and reconstruction), digital modulation techniques, communication signals and systems, characterization of thermal noise, signal space, signal detection and optimum receivers for the AWGN channel.
Communications (Lab): Introduction to Digital Communications (Lab),
Introduction to Information Theory and Coding (Lab), Digital Communication Over
Fading Channels (Lab) Digital Communication Through Band-Limited Channels
(Lab), Digital Communication Through Band-Limited Channels (Lab) 1- Lab of Introduction to Digital Communications 2- Lab of Introduction to Information Theory and
Coding 3- Lab of Digital Communication Over Fading
Channels 4- Lab of Digital Communication Through Band-Limited Channels
Digital Communication Through Band-Limited Channels (Lab), Digital Communication Through Band-Limited Channels (Lab)
1- Lab of Introduction to Digital Communications
2- Lab of Introduction to Information Theory and Coding
3- Lab of Digital Communication Over Fading Channels
4- Lab of Digital Communication Through Band-Limited Channels