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Digital Modulations using Python: (Black & White edition)

Digital Modulations using Python: (Black & White edition)

Paperback

Technology & Engineering

ISBN10: 1712342746
ISBN13: 9781712342749
Publisher: Independently Published
Published: Dec 2 2019
Pages: 218
Weight: 0.85
Height: 0.46 Width: 7.01 Depth: 10.00
Language: English
This paperback is a black & white edition. Link to the color edition: https: //www.amazon.com/dp/1712321633 .
A learner-friendly, practical and example driven book, Digital Modulations using Python gives you a solid background in building simulation models for digital modulation systems in Python version 3. This book, an essential guide for understanding the implementation aspects of a digital modulation system, shows how to simulate and model a digital modulation system from scratch. The implemented simulation models shown in this book, provide an opportunity for an engineer to understand the basic implementation aspects of modeling various building blocks of a digital modulation system. It presents the key topics with required theoretical background along with the implementation details in the form of Python scripts.
Key topics:
► Basics of signal processing, essential for implementing digital modulation techniques - generation of test signals, interpreting FFT results, power and energy of a signal, methods to compute convolution, analytic signal and applications.
► Waveform and complex baseband equivalent simulation models.
► Digital modulation techniques covered: BPSK and its variants, QPSK and its variants, M-ary PSK, M-ary QAM, M-ary PAM, CPM, MSK, GMSK, M-ary FSK.
► Simulation for ascertaining performance of digital modulation techniques in AWGN and fading channels - Eb/N0 Vs BER curves.
► Design and implementation of linear equalizers - zero forcing and MMSE equalizers, using them in a communication link, LMS algorithm for adaptive equalization.
► Simulation and performance of modulation systems with receiver impairments.
► Examples using object oriented programming.
► Simulation scripts using SciPy, Numpy and Matplotlib packages.

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