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.

Teachers Geert Leus

Signal processing for communication and networking, with applications to underwater communication, cognitive radio and sensor networks. Alle-Jan van der Veen

Array signal processing; Signal processing for communications

Last modified: 2016-02-25


Credits: 4 EC
Period: 0/0/0/4


Geert Leus

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