Title : Implementation of quadrature modulation and demodulation
Design Object : By implementing quadrature modulation and demodulation of analog signals in digital signal processing, students will have better understanding of sampling and frequency analysis of discrete-time signals.
Design Content : Make a MATLAB function which performs quadrature modulation and demodulation for a input signal with anti-aliasing filtering.
The Open Radar Data Acquisition (ORDA)
subsystem replaces the current WSR-88D Radar
Data Acquisition subsystem with improved
receiver and signal processing hardware and with
improved user interface, signal processing and
diagnostics software. This paper will discuss the
input data from the digital receiver, the ORDA
signal processing, and the data output from the
ORDA hardware. Specifications of the ORDA
digital receiver will be presented. The paper
outlines the critical radar signal processing flow
and provides analysis of new spectrum width
computations and clutter filtering schemes used in
the ORDA system. Where appropriate, ORDA
performance enhancements, data quality
improvements and reliability and maintenance
improvements will be highlighted.
kalman filter matlab tool help full for understanding the coding for the kalmanfilter, which can either be used for any purposes which could be help for digital signal processing, wirless mobile communication , OFDM .
A simple example of audio signal processing on TMS320VC5416 USB DSK board. Main source is contained in tone.c file, memory configuration - tonecfg.cmd. Folder docs/ contains useful docmentation on board, its components and libraries. The example's configuration is based on example "tone" from Code Composer Studio's 3.1 example for 5416 DSK.
Mobile communication devices like smart phones or tablet PCs enable us to
consume information at every location and at every time. The rapid development
of new applications and new services and the demand to access data in real time
create an increasing throughput demand. The data have to be transmitted reliably
to ensure the desired quality of service. Furthermore, an improved utilization of
the bandwidth is desired to reduce the cost of transmission.
When we started thinking about writing the first edition of this book a few years ago, we had been
working together for more than five years on the borderline between propagation and signal processing.
Therefore, it is not surprising that this book deals with propagation models and design tools for MIMO
wireless communications. Yet, this book should constitute more than a simple combination of these
two domains. It hopefully conveys our integrated understanding of MIMO, which results from endless
controversial discussions on various multi-antenna related issues, as well as various interactions with
numerous colleagues. Obviously, this area of technology is so large that it is beyond our aim to cover all
aspects in details. Rather, our goal is to provide researchers, R&D engineers and graduate students with
a comprehensive coverage of radio propagation models and space–time signal processing techniques
for multi-antenna, multi-user and multi-cell networks.
When we started thinking about writing this book, we had been working together for more
than five years on the borderline between propagation and signal processing.Therefore, it
is not surprising that this book deals with propagation models and design tools for MIMO
wirelesscommunications.Yet, thisbookshouldconstitutemorethanasimplecombination
of these two domains. It hopefully conveys our integrated understanding of MIMO, which
results from endless controversial discussions on various multi-antenna related issues, as
well as various interactions with numerous colleagues. Obviously, this area of technology
is so large that it was beyond our aim to cover all aspects in details. Rather, our goal has
been to provide researchers, R&D engineers and graduate students with a comprehensive
coverage of radio propagation models and space–time coding techniques.
