Orthogonal frequency coded filters for use in ultra-wideband communication systems.
The use of ultra-short pulses, producing very wide bandwidths and low spectral power density, are the widely accepted approach for ultra-wideband (UWB) communication systems. This approach is simple and can be implemented with current digital signal processing technologies. However, surface acoustic wave (SAW) devices have the capability of producing complex signals with wide bandwidths and relatively high frequency operation. This approach, using SAW based correlators, eliminates many of the costly components that are needed in the IF block in the transmitter and receiver, and reduces many of the signal processing requirements. This work presents the development of SAW correlators using orthogonal frequency coding (OFC) for use in UWB spread spectrum communication systems. OFC and pseudonoise (PN) coding provide a means for UWB spreading of data. The use of OFC spectrally spreads a PN sequence beyond that of code division multiple access (CDMA) because of the increased bandwidth providing an improvement in processing gain. The transceiver approach is still very similar to that of a CDMA but provides greater code diversity. Experimental results of a SAW filter designed with OFC transducers are presented. The SAW correlation filter was designed using seven contiguous chip frequencies within the transducer. SAW correlators with a 29% fractional bandwidth were fabricated on lithium niobate (LiNbO3) having a center frequency of 250 MHz. A coupling-of-modes (COM) model is used to predict the SAW filter response experimentally and is compared to the measured data. Good correlation between the predicted COM responses and the measured device data is obtained. Discussion of the design, analysis, and measurements are presented. The experimental matched filter results are shown for the OFC device and are compared to the ideal correlation. The results demonstrate the OFC SAW device concept for UWB communication transceivers.
Gallagher
Daniel R
DR
School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816-2450, USA. danielgallagher@ieee.org
Malocha
Donald C
DC
Puccio
Derek
D
Saldanha
Nancy
N