One of the most important application areas of signal processing (SP) is, without a doubt, the software-defined radio (SDR) field [1]-[3]. Although their introduction dates back to the 1980s, SDRs are now becoming the dominant technology in radio communications, thanks to the dramatic development of SP-optimized programmable hardware, such as field-programmable gate arrays (FPGAs) and digital signal processors (DSPs). Today, the computational throughput of these devices is such that sophisticated SP tasks can be efficiently handled, so that both the baseband and intermediate frequency (IF) sections of current communication systems are usually implemented, according to the SDR paradigm, by the FPGA's reconfigurable circuitry (e.g., [4]-[6]), or by the software running on DSPs.

Pasolini, G., Bazzi, A., Zabini, F. (2017). A Raspberry Pi-Based Platform for Signal Processing Education [SP Education]. IEEE SIGNAL PROCESSING MAGAZINE, 34(4), 151-158 [10.1109/MSP.2017.2693500].

A Raspberry Pi-Based Platform for Signal Processing Education [SP Education]

Pasolini, Gianni;Bazzi, Alessandro;Zabini, Flavio
2017

Abstract

One of the most important application areas of signal processing (SP) is, without a doubt, the software-defined radio (SDR) field [1]-[3]. Although their introduction dates back to the 1980s, SDRs are now becoming the dominant technology in radio communications, thanks to the dramatic development of SP-optimized programmable hardware, such as field-programmable gate arrays (FPGAs) and digital signal processors (DSPs). Today, the computational throughput of these devices is such that sophisticated SP tasks can be efficiently handled, so that both the baseband and intermediate frequency (IF) sections of current communication systems are usually implemented, according to the SDR paradigm, by the FPGA's reconfigurable circuitry (e.g., [4]-[6]), or by the software running on DSPs.
2017
Pasolini, G., Bazzi, A., Zabini, F. (2017). A Raspberry Pi-Based Platform for Signal Processing Education [SP Education]. IEEE SIGNAL PROCESSING MAGAZINE, 34(4), 151-158 [10.1109/MSP.2017.2693500].
Pasolini, Gianni; Bazzi, Alessandro; Zabini, Flavio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/623180
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