ET4147 Signal processing for communications
Topics: Signal separation and parameter estimation using arrays of sensors.
The course discusses techniques for signal separation and parameter estimation, using arrays of sensors, and applied to wireless communications. We start by deriving a signal processing model of the wireless channel. We then recall useful tools from linear algebra: QR, SVD, eigenvalue decompositions, projections. This gives us tools to discuss some more elementary receivers: the matched filter, the Wiener filter. Then we discuss important applications: estimation of angles and delays using ESPRIT, adaptive space-time filters, the constant modulus algorithm. Finally, we look at OFDM and CDMA systems and see how the above techniques can be applied to this.
prof.dr.ir. Geert Leus
Signal processing for communications, with applications to underwater communications, cognitive radio, and multiple-input multiple-output (MIMO) systems. Signal processing for (compressive) sensing with applications to ultrasound imaging and radar. Distributed signal processing. Graph signal processing.
prof.dr.ir. Alle-Jan van der Veen
Array signal processing; Signal processing for communications
Last modified: 2019-02-07