摘要：Software Defined Radio (SDR) is the technology which has given researchers the opportunity and flexibility of integration and intercommunication of existing and future networks together. The radio spectrum is the most vital resource for a mobile operator in today's world of modern wireless communications. After analyzing the spectrum allocation map one can conclude that the most of the prime spectrums falling under the licensed bands have already been allocated for licensed users for exclusive use. There are very few unlicensed bands for the unlicensed users. SDR offers a perfect solution to this problem of spectrum scarcity being experienced in wireless communication systems. The demand for reliable, high data rate transmission has increased significantly these days, which leads the way to adoption, of different digital modulation techniques. The aim of this paper was to analyze Frequency Shift Keying (FSK) Transceiver built using Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) and to measure the reduction in data errors in the presence of Forward Error Correction (FEC) channel coding algorithms namely the Convolution and the Turbo Codes. Through this design a graphical representation of Bit Error Rate (BER) vs E"b/N"0 where (E"b) is Energy per bit and (N"0) is Spectral noise density has been given in the presence of Additive White Gaussian Noise (AWGN) introduced in the channel. FSK is widely used for data transmission over band pass channels; hence, we have chosen FSK for the implementation of SDR. The SDR transceiver module designed has been fully implemented and has the ability to navigate over a wide range of frequencies with programmable channel bandwidth and modulation characteristics. We are able to build an interactive FSK based SDR transceiver in a shorter time with the use of LabVIEW. The outputs achieved show a low BER for very high data rates in the presence of AWGN noise.
关键词：Software Defined Radio
; Bit Error Rate (BER)
; Wireless communication
; Frequency shift keying
; Signal-to-Noise Ratio (SNR)
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