Multi-mode reconfigurable software defined radio (SDR) architecture for avionic radios

Author(s):  
Joe Zambrano ◽  
Abdessamad Amrhar ◽  
Alireza Avakh Kisomi ◽  
Eric Zhang ◽  
Claude Thibeault ◽  
...  
2010 ◽  
Vol 8 ◽  
pp. 67-73 ◽  
Author(s):  
M. D. Blech ◽  
A. T. Ott ◽  
P. Neumeier ◽  
M. Möller ◽  
T. F. Eibert

Abstract. An ultra-wideband (UWB) software defined radio (SDR) implementation is presented. The developed impulse radio (IR) transceiver employs first order bandpass (BP) sampling at a conversion frequency which is four times the channel bandwidth. The subsampling architecture directly provides the RF signal avoiding any non-ideal mixer stages and reduces the requirements of digital signal processing implemented in a field programmable gate array (FPGA). The transmitter consists basically of a multi-Nyquist digital to analog converter (DAC), whereas the implemented matched filter (MF) receiver prototype employs a standard digitizing oscilloscope. This design can be adaptively reconfigured in terms of modulation, data rate, and channel equalization. The reconfigurable design is used for an extensive performance analysis of the quadrature phase shift keying (QPSK) modulation scheme investigating the influence of different antennas, amplifiers, narrowband interferers as well as different equalizer lengths. Even for distances up to 7 m in a multipath environment robust communication was achieved.


2015 ◽  
Vol 22 (6) ◽  
pp. 12-14 ◽  
Author(s):  
Ray Yeuh-Min Huang ◽  
Victor C. M. Leung ◽  
Chin-Feng Lai ◽  
Subhas Mukhopadhyay ◽  
Roy X. Lai

Author(s):  
Ashwin Amanna ◽  
Matthew J. Price ◽  
Soumava Bera ◽  
Manik Gadhiok ◽  
Jeffrey H. Reed

This paper discusses a railway specific cognitive radio that builds upon software defined radio (SDR) platforms to adapt the radio based situational awareness. Cognitive Radio incorporates artificial intelligence based algorithms with reconfigurable software-defined radios that enable automatic adjustments of the radio to improve performance and overcome obstacles the radio may confront in the field (i.e. environmental/man-made interference, occupying the same channel as a user with higher priority, etc.). This paper describes the Railway Cognitive Radio (Rail-CR) architecture and illustrates preliminary results in simulation. The proposed cognitive engine architecture consists of a case-based reasoned (CBR) and a Genetic Algorithm (GA) optimization routine. This paper discusses the overall cognitive architecture, the relationship between the CBR and the GA based on weighted objective functions, and metrics for assessing performance. Methods for case representation, quantifying similarity between cases histories, and techniques for managing case growth rate are presented as well as a proposed test bed SDR platform.


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