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author | Nao Pross <np@0hm.ch> | 2021-12-21 20:27:58 +0100 |
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committer | Nao Pross <np@0hm.ch> | 2021-12-21 20:27:58 +0100 |
commit | e8844143393b23510c3e640954179f74f5632031 (patch) | |
tree | 0d8b37382b904b646f0f02c1cb71104aca9bff8d /doc | |
parent | Doku changes (diff) | |
download | Fading-e8844143393b23510c3e640954179f74f5632031.tar.gz Fading-e8844143393b23510c3e640954179f74f5632031.zip |
PSAM in conclusions
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-rw-r--r-- | doc/thesis/chapters/conclusions.tex | 13 |
1 files changed, 11 insertions, 2 deletions
diff --git a/doc/thesis/chapters/conclusions.tex b/doc/thesis/chapters/conclusions.tex index 8cb3a5d..5d6eb1f 100644 --- a/doc/thesis/chapters/conclusions.tex +++ b/doc/thesis/chapters/conclusions.tex @@ -17,17 +17,26 @@ One other file to implement the hardware with. Unfortunately it was not possible \subsection{Improve BER measurements and simulations} -An interesting continuation of the current work could be to automate the collection of the BER data, and to measure and observe the influence of each parameters in the fading channel model. In addition, new flow graphs for further modulation schemes could be easily added to the current framework. +A missing feature in this work is an automated collection of the BER data, which would allow to more easily to observe and measure the influence of each parameters in the fading channel model. \subsection{Improvements of GUI frontend} The current GUI prototype built with DearPyGUI has some issues, the most critical begin a single-threaded application. The interprocess communication (with GR's flow graphs) should be on a separate thread from the graphics. The problem is not noticeable as long as the flow graphs in the background keep sending data, but as soon as the UDP/IP data stream stops the timeout of the socket interface causes the interface to run at less that 20 frames per second. -In addition to fixing the aforementioned issue, a very important missing feature that is currently missing is the ability to change the fading parameters in real time from within the GUI. Dear PyGUI offers many graphical elements that could be used to control the parameters, however a new GR block would need to be created to propagate the updated values into the flow graph. +In addition to fixing the aforementioned issue, a very important feature that is currently missing is the ability to change the fading parameters in real time from within the GUI. Dear PyGUI offers many graphical elements that could be used to control the parameters, however a new GR block would need to be created to propagate the updated values into the flow graph. \subsection{Channel parameters estimation with Pilot Symbols} +An interesting continuation of this work could be to regularly interpolate some so called pilot symbols in the modulated data stream. Briefly, the pilot symbol assisted modulation (PSAM) technique consists of periodically inserting informationless (known) symbols in the data stream, which are then used to estimate the fading parameters of the communication channel. More details are presented in \cite{Xiaoyi1999} (and its references) from which the illustrations in \figref{fig:psam} were taken. +\begin{figure} + \centering + \includegraphics[width = \linewidth]{figures/xiaoyi-psam-figures} + \caption{ + Illustration of the pilot symbols assisted modulation (PSAM) frame format (left), and PSAM fading interpolation method (right). The PSAM technique allows to compute the fading (denoted in the figure with \(\tilde{z}_n\)) by interpolating measurements of informationless symbols (pilot symbols) over multiple frames. Both figures were taken from \cite{Xiaoyi1999}, which presents an analytical method to compute the BER from the PSAM and multilevel quadrature amplitude modulation (M-QAM) parameters. + \label{fig:psam} + } +\end{figure} \section{Closing words} |