| Paper ID | SS-6.3 |
| Paper Title |
INFORMATION DECODING AND SDR IMPLEMENTATION OF DFRC SYSTEMS WITHOUT TRAINING SIGNALS |
| Authors |
Daniel Wong, Batu Chalise, New York Institute of Technology, United States; Justin Metcalf, University of Oklahoma, United States; Moeness G. Amin, Villanova University, United States |
| Session | SS-6: Intelligent Sensing and Communications for Emerging Applications |
| Location | Gather.Town |
| Session Time: | Wednesday, 09 June, 14:00 - 14:45 |
| Presentation Time: | Wednesday, 09 June, 14:00 - 14:45 |
| Presentation |
Poster
|
| Topic |
Special Sessions: Intelligent Sensing and Communications for Emerging Applications |
| IEEE Xplore Open Preview |
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| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
Recent performance analysis of dual-function radar communications (DFRC) systems, which embed information using phase shift keying (PSK) into multiple-input multiple-output (MIMO) frequency hopping (FH) radar pulses, shows promising results for addressing spectrum sharing issues between radar and communications. However, the problem of decoding information at the communication receiver remains challenging, since the DFRC transmitter is typically assumed to transmit only information embedded radar waveforms and not the training sequence. We propose a novel method for decoding information at the communication receiver without using training data, which is implemented using a software-defined radio (SDR). The performance of the SDR implementation is examined in terms of bit error rate (BER) as a function of signal-to-noise ratio (SNR) for differential binary and quadrature phase shift keying modulation schemes and compared with the BER versus SNR obtained with numerical simulations. |
