Commit 324be9752af9eb82244b9e77b7149a7593c1a73e

Authored by Arthur HUGEAT
1 parent 549741b81b
Exists in master

Correction des petites typos.

Showing 1 changed file with 11 additions and 11 deletions Inline Diff

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31 31
\begin{document} 32 32 \begin{document}
33 33
% Title 34 34 % Title
\begin{center} 35 35 \begin{center}
\textbf{{\scshape 36 36 \textbf{{\scshape
\LARGE\color{OliveGreen} 37 37 \LARGE\color{OliveGreen}
Filter optimization for real time digital processing of radiofrequency signals: application 38 38 Filter optimization for real time digital processing of radiofrequency signals: application
to oscillator metrology 39 39 to oscillator metrology
\\}} 40 40 \\}}
\end{center} 41 41 \end{center}
42 42
\vspace{-0.35cm} 43 43 \vspace{-0.35cm}
% Authors 44 44 % Authors
\begin{center} 45 45 \begin{center}
\addalignedblock{0.18\textwidth}{flushleft}{% 46 46 \addalignedblock{0.18\textwidth}{flushleft}{%
\includegraphics[height=1.6cm]{images/logo_ubfc} 47 47 \includegraphics[height=1.6cm]{images/logo_ubfc}
} 48 48 }
\addalignedblock{0.28\textwidth}{center}{% 49 49 \addalignedblock{0.28\textwidth}{center}{%
A. \textsc{Hugeat}$^{*}$, J. \textsc{Bernard}\\ 50 50 A. \textsc{Hugeat}$^{*}$, J. \textsc{Bernard}\\
~\\ 51 51 ~\\
FEMTO-ST, DISC dept., Besan\c con, France 52 52 FEMTO-ST, DISC dept., Besan\c con, France
} 53 53 }
\addalignedblock{0.28\textwidth}{center}{% 54 54 \addalignedblock{0.28\textwidth}{center}{%
G. \textsc{Goavec-Merou},\\ 55 55 G. \textsc{Goavec-Merou},\\
P.-Y. \textsc{Bourgeois}, J.-M \textsc{Friedt}\\ 56 56 P.-Y. \textsc{Bourgeois}, J.-M \textsc{Friedt}\\
$^{*}$FEMTO-ST, Time \& Frequency dept., Besan\c con, France 57 57 $^{*}$FEMTO-ST, Time \& Frequency dept., Besan\c con, France
} 58 58 }
\addalignedblock{0.18\textwidth}{flushright}{% 59 59 \addalignedblock{0.18\textwidth}{flushright}{%
\includegraphics[height=1.4cm]{images/logo_femto} 60 60 \includegraphics[height=1.4cm]{images/logo_femto}
} 61 61 }
\end{center} 62 62 \end{center}
63 63
% First part 64 64 % First part
\vspace{-.61cm} 65 65 \vspace{-.61cm}
\newsection{Digital signal processing of ultrastable clock signals} 66 66 \newsection{Digital signal processing of ultrastable clock signals}
67 67
\vspace{-.21cm} 68 68 \vspace{-.21cm}
%\begin{minipage}[t]{\linewidth} 69 69 %\begin{minipage}[t]{\linewidth}
%\begin{minipage}{.7\linewidth} 70 70 %\begin{minipage}{.7\linewidth}
\begin{itemize}[leftmargin=*] 71 71 \begin{itemize}[leftmargin=*]
\setlength{\itemsep}{0pt}% 72 72 \setlength{\itemsep}{0pt}%
\setlength{\parskip}{0pt}% 73 73 \setlength{\parskip}{0pt}%
\item 74 74 \item
{\bf Digital phase noise characterization}: flexibility (software defined local 75 75 {\bf Digital phase noise characterization}: flexibility (software defined local
oscillator),\\ stability (no long term drift), reconfigurabilty 76 76 oscillator),\\ stability (no long term drift), reconfigurabilty
$\Rightarrow$ {\bf software defined radio} oscillator \\ 77 77 $\Rightarrow$ {\bf software defined radio} oscillator \\
phase noise characterization 78 78 phase noise characterization
\item analog to digital conversion of radiofrequency signal, software 79 79 \item analog to digital conversion of radiofrequency signal, software
defined local oscillator, 80 80 defined local oscillator,
mixer and {\bf low pass filter} 81 81 mixer and {\bf low pass filter}
\item low pass filter uses most resources and introduces latency (phase delay 82 82 \item low pass filter uses most resources and introduces latency (phase delay
in feedback loop): needs to be optimized 83 83 in feedback loop): needs to be optimized
\end{itemize} 84 84 \end{itemize}
%\end{minipage} 85 85 %\end{minipage}
%\begin{minipage}{.28\linewidth} 86 86 %\begin{minipage}{.28\linewidth}
87 87
\vspace{-3cm}\hfill\includegraphics[width=.28\linewidth]{schema} 88 88 \vspace{-3cm}\hfill\includegraphics[width=.28\linewidth]{schema}
%\end{minipage} 89 89 %\end{minipage}
%\end{minipage} 90 90 %\end{minipage}
91 91
\vspace{1.21cm} 92 92 \vspace{1.21cm}
\hrule{\hfill} 93 93 \hrule{\hfill}
% Second part 94 94 % Second part
\vspace{-.61cm} 95 95 \vspace{-.61cm}
\newsection{Filter design and implementation strategy:} 96 96 \newsection{Filter design and implementation strategy:}
%\begin{itemize}[leftmargin=*] 97 97 %\begin{itemize}[leftmargin=*]
%\setlength{\itemsep}{0pt}% 98 98 %\setlength{\itemsep}{0pt}%
%\setlength{\parskip}{0pt}% 99 99 %\setlength{\parskip}{0pt}%
\vspace{-.40cm} 100 100 \vspace{-.40cm}
\addblock{0.44\textwidth}{ 101 101 \addblock{0.44\textwidth}{
% \begin{enumerate}[noitemsep,nolistsep] 102 102 % \begin{enumerate}[noitemsep,nolistsep]
% \item 103 103 % \item
\textbf{Classical way:}\\ 104 104 \textbf{Classical way:}\\
Compute the transfer function of a monolithic filter 105 105 Compute the transfer function of a monolithic filter
\begin{itemize}[label=$\Rightarrow$, noitemsep, nolistsep] 106 106 \begin{itemize}[label=$\Rightarrow$, noitemsep, nolistsep]
{\color{Green}\item Simplest way to design filter} 107 107 {\color{Green}\item Simplest way to design filter}
{\color{Green}\item Great rejection} 108 108 {\color{Green}\item Great rejection}
{\color{Red}\item Consume lot of resources on FPGA} 109 109 {\color{Red}\item Consume lot of resources on FPGA}
\end{itemize} 110 110 \end{itemize}
% \end{enumerate} 111 111 % \end{enumerate}
} 112 112 }
\addblock{0.40\textwidth}{ 113 113 \addblock{0.40\textwidth}{
% \begin{enumerate} 114 114 % \begin{enumerate}
% \setcounter{enumi}{1} 115 115 % \setcounter{enumi}{1}
% \item 116 116 % \item
\textbf{Alternative way (our focus):}\\ 117 117 \textbf{Alternative way (our focus):}\\
Chain of small filters 118 118 Chain of small filters
\begin{itemize}[label=$\Rightarrow$, noitemsep, nolistsep] 119 119 \begin{itemize}[label=$\Rightarrow$, noitemsep, nolistsep]
{\color{Green}\item Great rejection} 120
{\color{Green}\item Consume less resources on FPGA} 121 120 {\color{Green}\item Consume less resources on FPGA}
121 {\color{Green}\item Great rejection}
{\color{Red}\item Harder way to design filter} 122 122 {\color{Red}\item Harder way to design filter}
\end{itemize} 123 123 \end{itemize}
% \end{enumerate} 124 124 % \end{enumerate}
} 125 125 }
126 126
\vspace{-2.6cm}\hfill\includegraphics[width=.2\linewidth]{schema2} 127 127 \vspace{-2.6cm}\hfill\includegraphics[width=.2\linewidth]{schema2}
\vspace{-0.3cm} 128 128 \vspace{-0.3cm}
129 129
The 2\textsuperscript{nd} way could be considered as an optimization problem: 130 130 The 2\textsuperscript{nd} way could be considered as an optimization problem:
\begin{itemize}[noitemsep,nolistsep] 131 131 \begin{itemize}[noitemsep,nolistsep]
\item One or many {\bf performance criteria} (rejection, noise, 132 132 \item One or many {\bf performance criteria} (rejection, noise,
throughput...) 133 133 throughput...)
\item Limited {\bf resources} (on FPGA) 134 134 \item Limited {\bf resources} (on FPGA)
\end{itemize} 135 135 \end{itemize}
Translation into a Mixed-Integer Linear Programming (MILP) with GLPK solver 136 136 Translation into a Mixed-Integer Linear Programming (MILP) with GLPK solver. We have
3 degrees of freedom: 137 137 3 degrees of freedom:
138 138
\vspace{.1cm} 139 139 \vspace{.1cm}
%\parbox{.60\linewidth}{ 140 140 %\parbox{.60\linewidth}{
% \begin{enumerate}[noitemsep,nolistsep] 141 141 % \begin{enumerate}[noitemsep,nolistsep]
% \item 142 142 % \item
\noindent 143 143 \noindent
size of chain filters, 144 144 size of chain filters,
% \item 145 145 % \item
number of coefficients for each filter $i$: $N_i$, 146 146 number of coefficients for each filter $i$: $N_i$,
% \item 147 147 % \item
number of bits for each coefficients and for each filter $i$: $c_i$ 148 148 number of bits for each coefficients and for each filter $i$: $c_i$
% \end{enumerate} 149 149 % \end{enumerate}
%} 150 150 %}
%\end{itemize} 151 151 %\end{itemize}
\vspace{-0.5cm} 152 152 \vspace{-0.5cm}
\newsection{Filter selection} 153 153 \newsection{Filter selection}
\vspace{-0.3cm} 154 154 \vspace{-0.3cm}
\begin{itemize}[noitemsep,nolistsep] 155 155 \begin{itemize}[noitemsep,nolistsep]
\item For select the filter design we need to evaluate the rejection like: 156 156 \item For select the filter design we need to evaluate the rejection like:
157 157
% \begin{enumerate}[noitemsep,nolistsep] 158 158 % \begin{enumerate}[noitemsep,nolistsep]
% \item The mean value of rejection 159 159 % \item The mean value of rejection
% \item The median value of rejection 160 160 % \item The median value of rejection
% \item A custom criterion (we penalize the rejection in base band and we keep only the maximum rejection on the filter tail) 161 161 % \item A custom criterion (we penalize the rejection in base band and we keep only the maximum rejection on the filter tail)
% \end{enumerate} 162 162 % \end{enumerate}
\begin{minipage}[t]{0.30\textwidth} 163 163 \begin{minipage}[t]{0.30\textwidth}
\includegraphics[width=0.95\textwidth]{images/noise-rejection-mean} 164 164 \includegraphics[width=0.95\textwidth]{images/noise-rejection-mean}
%\captionof{figure} 165 165 %\captionof{figure}
{Criterion=mean value of rejection} 166 166 {Criterion=mean value of rejection}
\end{minipage} 167 167 \end{minipage}
\begin{minipage}[t]{0.30\textwidth} 168 168 \begin{minipage}[t]{0.30\textwidth}
\includegraphics[width=0.95\textwidth]{images/noise-rejection-median} 169 169 \includegraphics[width=0.95\textwidth]{images/noise-rejection-median}
% \captionof{figure}{ 170 170 % \captionof{figure}{
{Criterion=median value of rejection} 171 171 {Criterion=median value of rejection}
\end{minipage} 172 172 \end{minipage}
\begin{minipage}[t]{0.30\textwidth} 173 173 \begin{minipage}[t]{0.30\textwidth}
\includegraphics[width=0.95\textwidth]{images/noise-rejection-custom} 174 174 \includegraphics[width=0.95\textwidth]{images/noise-rejection-custom}
% \captionof{figure} 175 175 % \captionof{figure}
{Criterion=max value of rejection} 176 176 {Criterion=max value of rejection}
\end{minipage} 177 177 \end{minipage}
\vspace{0.4cm} 178 178 \vspace{0.4cm}
\item All rejection criteria produce the same kind of result: the best filters seem to be in the edge of pyramid 179 179 \item All rejection criteria produce the same kind of result: the best filters seem to be in the edge of pyramid
\item For each criteria, we associate the rejection to the related filter and we let GLPK choose the best configuration\\ 180 180 \item For each criteria, we associate the rejection to the related filter and we let GLPK choose the best configuration\\
\begin{minipage}[t]{0.30\textwidth} 181 181 \begin{minipage}[t]{0.30\textwidth}
\includegraphics[width=0.95\textwidth]{images/fir-mono-vs-fir-series-noise-fixe-mean.pdf} 182 182 \includegraphics[width=0.95\textwidth]{images/fir-mono-vs-fir-series-noise-fixe-mean.pdf}
% \captionof{figure}{ 183 183 % \captionof{figure}{
{Criterion=mean value of rejection} 184 184 {Criterion=mean value of rejection}
\end{minipage} 185 185 \end{minipage}
\begin{minipage}[t]{0.30\textwidth} 186 186 \begin{minipage}[t]{0.30\textwidth}
\includegraphics[width=0.95\textwidth]{images/fir-mono-vs-fir-series-noise-fixe-median.pdf} 187 187 \includegraphics[width=0.95\textwidth]{images/fir-mono-vs-fir-series-noise-fixe-median.pdf}
% \captionof{figure} 188 188 % \captionof{figure}
{Criterion=median value of rejection} 189 189 {Criterion=median value of rejection}
\end{minipage} 190 190 \end{minipage}
\begin{minipage}[t]{0.30\textwidth} 191 191 \begin{minipage}[t]{0.30\textwidth}
\includegraphics[width=0.95\textwidth]{images/fir-mono-vs-fir-series-noise-fixe-jmf.pdf} 192 192 \includegraphics[width=0.95\textwidth]{images/fir-mono-vs-fir-series-noise-fixe-jmf.pdf}
% \captionof{figure} 193 193 % \captionof{figure}
{Criterion=max value of rejection} 194 194 {Criterion=max value of rejection}
\end{minipage} 195 195 \end{minipage}
\vspace{0.4cm} 196 196 \vspace{0.4cm}
\item {\bf Rejection}: the last configuration is better than the first but worse 197 197 \item {\bf Rejection}: the last configuration is better than the first one but worse
than the monolithic filter 198 198 than the monolithic filter
\item Resources {\bf consumption}: last filter is better than the single monolithic filter 199 199 \item Resources {\bf consumption}: last filter is better than the single monolithic filter
(monolithic does not fit in available resources) 200 200 (monolithic does not fit in available resources)
\vspace{-.33cm} 201 201 \vspace{-.33cm}
\begin{center} 202 202 \begin{center}
\begin{tabular}{|c|ccccc|}\hline 203 203 \begin{tabular}{|c|ccccc|}\hline
FIR & BlockRAM36 & BlockRAM18 & LookUpTables & DSP & rejection (dB)\\\hline\hline 204 204 FIR & BlockRAM36 & BlockRAM18 & LookUpTables & DSP & rejection (dB)\\\hline\hline
1 (monolithic) & 1 & 0 & {\color{Red}76183} & 220 & -162 \\ 205 205 1 (monolithic) & 1 & 0 & {\color{Red}76183} & 220 & -162 \\
5 & 0 & 5 & {\color{Green}18597} & 220 & -160 \\ 206 206 5 & 0 & 5 & {\color{Green}18597} & 220 & -160 \\
10 & 0 & 8 & {\color{Green}24729} & 220 & -161 \\\hline\hline 207 207 10 & 0 & 8 & {\color{Green}24729} & 220 & -161 \\\hline\hline
\textbf{Zynq 7020} & \textbf{140} & \textbf{280} & \textbf{53200} & \textbf{220} & \\\hline 208 208 \textbf{Zynq 7020} & \textbf{140} & \textbf{280} & \textbf{53200} & \textbf{220} & \\\hline
\end{tabular} 209 209 \end{tabular}
% \captionof{table}{Resources consumption when we use the configuration with the custom criterion} 210 210 % \captionof{table}{Resources consumption when we use the configuration with the custom criterion}
\end{center} 211 211 \end{center}
\item Series of filters: targetd rejection level (-160~dB) reached since less 212 212 \item Series of filters: target rejection level (-160~dB) reached since less
resources are needed than with a monolithic filter 213 213 resources are needed than with a monolithic filter
\end{itemize} 214 214 \end{itemize}
\hrule{\hfill} 215 215 \hrule{\hfill}
216 216
\vspace{-.71cm} 217 217 \vspace{-.71cm}