Software defined radio and modulation recognition, Electrical Engineering


As we all know the next century demand for wireless technology is expected to be the commercial implementation of Software Defined Radio (SDR) paradigm to improve base station efficiency and reduce receiver complexities to provide seamless high quality service to the end user to meet ever increasing customer demands. This will require gradual transition of traditional hardware intensive architectures being replaced by reconfigurable hardware which can run multiple software based radio solutions. Software defined radio has received enormous recognition as the next evolutionary stage of wireless technology, getting support from governmental agencies as well as civil and commercial entities. The numerous benefits provided by SDR have created widespread interest in modulation recognition problem which is one of the major tasks of an intelligent receiver in a radio communication system in SDR.

In this paper we study modulation recognition problem in some detail. A modulation recognition module in a receiver should be able to identify the modulation format present in the received signal with minimum prior knowledge. Based on this information and user requirement an intelligent receiver will take the best decision regarding the software to be run on the reconfigurable hardware to give best quality of service to the user. In an adaptive modulation based system, the receiver can estimate the parameters used by the transmitter from time to time. This results in saving of bandwidth. In the simplest form modulation recognition algorithm helps the receiver to know the modulation format contained in the received signal based on the received samples. This may be done with no or minimum prior information such as carrier frequency, symbol rate or a class of modulation formats etc. All such schemes critically depend on SNR of the received signal. In this paper, we presented two methods for SNR estimation and discuss a few papers on modulation classification.


Posted Date: 3/30/2013 6:52:11 AM | Location : United States

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