Chair of Information and Coding Theory

Software-Defined and Cognitive Radio Concept


A software-defined radio is a modem, in which some or all functionality at least of the physical (PHY) layer of the open systems interconnection (OSI) model is realized by software. The software-defined radio concept has been established in the 1980's in order to be able to reconfigure radio modems. Initially, only receiver-side baseband signal processing has been implemented in software. At DLR in Oberpfaffenhofen, we were perhaps the first group worldwide also realizing transmitter-side baseband signal processing in software [1], several years before the notion "SDR" has been coined by J. Mitola III. This step paved the road to fully digital transmission systems with much higher flexibility and adaptability. The success of cellular radio systems is partly based on the software-defined radio concept -- flexibility, multi-standard compatibility, and cost efficiency are just some arguments in favor of SDR.

About one decade later, J. Mitola III also coined the cognitive radio (CR) concept. A cognitive radio is an adaptive radio, which does not just monitor its own performance, but additionally also environmental parameters. A cognitive radio is able to detect variations and can react to these. Among the tasks of cognitive radio are power control, spectrum sensing, spectrum sharing, and spectrum management. An inherent challenge of CR is interference between active users. So-called primary users, who have a license and thus pay for a certain service, interfere with secondary users, e.g. Wi-Fi users. In [2,3], a sophisticated approach has been published that mitigates the interference challenge.

Nowadays, several software-defined radio projects are conducted by our students.


Selected References:

[1] P.A. Hoeher and H. Lang, "Coded-8PSK modem for fixed and mobile satellite services based on DSP," in Proc. First Int. Workshop on Digital Signal Processing Techniques Applied to Space Communications, ESA/ESTEC, Noordwijk, Holland, Nov. 1988; ESA WPP-006, pp. 117-123, Jan. 1990.

[2] A. Yaqot and P.A. Hoeher, "Efficient resource allocation in cognitive networks," IEEE Trans. Vehicular Technology, vol. 66, no. 7, pp. 6349-6361, July 2017.

[3] A. Yaqot, Adaptive Precoding and Resource Allocation in Cognitive Radio Networks. Dissertation, Faculty of Engineering, University of Kiel, 2017.


The projects have been sponsored by: