**2. Conclusion**

USRP can be effectively combined to create an SDR transceiver. The LabVIEW/USRP combination presents an opportunity to enhance communications education by enabling a low-cost, hands-on approach with live signals for realistic, real-world demonstrations, laboratory exercises, capstone design projects and cutting-edge research.

The universal software radio peripheral family of products is a popular platform for hardwarebased research and test bed validations conducted by universities in the software-defined radio and cognitive radio (CR) fields. The USRP offers a simpler, scalable and easier to use combined platform that will both broaden the accessibility of the technology and platform for hands-on applications and spur further adoption and use within university communication systems classrooms, teaching laboratories and their natural follow-on coursework (e.g., SDR, CR, digital communications, wireless communications and satellite communications).This chapter describes SDR system built using LabVIEW and testing the output using real-time data. Through this chapter, we have tried to cover emerging SDR standards and the technologies being used to specify and support them. We have proposed expanding the SDR definition and discussed the issues pertaining to the design of a multi-band flexible receiver and a linearized transmitter using broadband quadrature techniques. Here, we have described the case study of the SDR by designing an SDR generic transceiver in LabVIEW highlighting the multimodulation approach for the SDR. The design uses forward error correction codes namely convolution codes and turbo codes for enhanced security for the data being transmitted. The proposed design is entirely reconfigurable in nature and supports multiple M-ary modulation schemes which can be changed accordingly by the user any time during the runtime. The biggest advantage of this design is that we have used phase tracking for identification of the constellation points. The analysis of the case study proves that turbo coding gives a much improved and better minimization of the data errors than the convolution coding.
