More polishing of text, fixed typo's, etc.

git-svn-id: svn+ssh://svn.code.sf.net/p/wsjt/wsjt/branches/wsjtx@6353 ab8295b8-cf94-4d9e-aec4-7959e3be5d79

lib/ftrsd/ftrsd_paper/ftrsd.lyx

@@ -84,15 +84,6 @@ Steven J.
  Taylor, K1JT
 \end_layout
 
-\begin_layout Standard
-\begin_inset CommandInset toc
-LatexCommand tableofcontents
-
-\end_inset
-
-
-\end_layout
-
 \begin_layout Section
 \begin_inset CommandInset label
 LatexCommand label
@@ -117,8 +108,8 @@ moonbounce
 \end_inset
 
 ) communication, where the scattered return signals are always weak.
- It was soon found that JT65 also facilitates worldwide communication on
+ It was soon found that JT65 also enables worldwide communication on the
- the HF bands with low power, modest antennas, and efficient spectral usage.
+ HF bands with low power, modest antennas, and efficient spectral usage.
 \end_layout
 
 \begin_layout Standard
@@ -133,7 +124,7 @@ key "kv2001"
 
 \end_inset
 
-, licensed to and implemented by K1JT in a closed-source executable for
+, licensed to and implemented by K1JT as a closed-source executable for
  use only in amateur radio applications.
  Since 2001 the KV decoder has been considered the best available soft-decision
  decoder for Reed Solomon codes.
@@ -1121,7 +1112,7 @@ reference "sec:Theory,-Simulation,-and"
 \end_inset
 
 , we use simulations to set an empirical acceptance threshold 
-\begin_inset Formula $r_{0}$
+\begin_inset Formula $r_{1}$
 \end_inset
 
  that maximizes the probability of correct decodes while ensuring a low
@@ -1145,7 +1136,7 @@ Technically the FT algorithm is a list decoder.
 \begin_inset Formula $d_{s}$
 \end_inset
 
- are less than conservatively specified limits 
+ are less than specified limits 
 \begin_inset Formula $X_{0}$
 \end_inset
 
@@ -1162,7 +1153,7 @@ Technically the FT algorithm is a list decoder.
 \begin_inset Formula $r<r_{1}$
 \end_inset
 
- are used to validate additional decodes that did not pass the first test.
+ are used to validate additional codewords that did not pass the first test.
  A timeout is used to limit the algorithm's execution time if no acceptable
  codeword is found in a reasonable number of trials, 
 \begin_inset Formula $T$
@@ -1390,17 +1381,17 @@ The FT algorithm is completely general: with equal sensitivity it recovers
 \emph on
 much
 \emph default
- smaller list of messages (say, a few thousand messages or less) that may
+ smaller list of messages (say, a few thousand messages or less) that we
- be among the most likely ones to be received.
+ can guess may be among the most likely ones to be received.
  One such situation exists when making short ham-radio contacts that exchange
  minimal information including callsigns, signal reports, perhaps Maidenhead
  locators, and acknowledgments.
  On the EME path or on a VHF or UHF band with limited geographical coverage,
  the most likely received messages often originate from callsigns that have
  been decoded before.
- Saving a list of previously decoded callsigns makes it easy to generate
+ Saving a list of previously decoded callsigns and associated locators makes
- lists of hypothetical messages and their corresponding codewords, at very
+ it easy to generate lists of hypothetical messages and their corresponding
- little computational expense.
+ codewords at very little computational expense.
  The resulting candidate codewords can be tested in the same way as those
  generated by the probabilistic method described in Setcion 
 \begin_inset CommandInset ref
@@ -1454,16 +1445,8 @@ For hinted decoding we again invoke a ratio threshold test, but in this
 \begin_inset Formula $r_{2},$
 \end_inset
 
- for what is 
+ that is small enough to establish adequate confidence, while still ensuring
-\begin_inset Quotes eld
+ that false decodes are rare.
-\end_inset
-
-small enough
-\begin_inset Quotes erd
-\end_inset
-
- to establish adequate confidence, while still ensuring that false decodes
- are rare.
  Because tested candidate codewords are drawn from a list typically no longer
  than a few thousand, rather than 
 \begin_inset Formula $2^{72},$
@@ -1473,22 +1456,14 @@ small enough
 \begin_inset Formula $r_{2}$
 \end_inset
 
- can set a more relaxed limit than 
+ can be a more relaxed limit than the 
-\begin_inset Formula $r_{1},$
+\begin_inset Formula $r_{1}$
 \end_inset
 
- as used in the FT algorithm.
+ used in the FT algorithm.
- For the limited subset of messages established by operator experience as
+ For the limited subset of messages that operator experience suggests to
- 
+ be likely, hinted decodes can be obtained at lower signal levels than required
-\begin_inset Quotes eld
+ for those obtained from the full universe of 
-\end_inset
-
-likely,
-\begin_inset Quotes erd
-\end_inset
-
- hinted decodes can be obtained at lower signal levels than required for
- decodes obtained from the full universe of 
 \begin_inset Formula $2^{72}$
 \end_inset
 
@@ -1512,11 +1487,7 @@ Comparisons of decoding performance are usually presented in the professional
 \end_inset
 
 , the ratio of the energy collected per information bit to the one-sided
- noise power spectral density, 
+ noise power spectral density.
-\begin_inset Formula $N_{0}$
-\end_inset
-
-.
  For weak-signal amateur radio work, performance is more conveniently presented
  as the probability of successfully decoding a received word plotted against
  signal-to-noise ratio in a 2500 Hz reference bandwidth, 
@@ -1540,12 +1511,12 @@ reference "sec:Appendix:SNR"
 \end_inset
 
 .
- Examples of both types of plot are included in the following discussion,
+ Examples of both presentations are included in the following discussion,
- where we describe a number of simulations carried out to compare performance
+ where we describe simulations carried out to compare performance of FT
- of the FT algorithm with others, and with theoretical expectations.
+ with other algorithms, and with theoretical expectations.
  We have also used simulations to establish suitable default values for
  the acceptance parameters 
-\begin_inset Formula $h_{0},$
+\begin_inset Formula $X_{0},$
 \end_inset
 
  
@@ -1556,8 +1527,12 @@ reference "sec:Appendix:SNR"
 \begin_inset Formula $d_{1},$
 \end_inset
 
+ 
+\begin_inset Formula $r_{1},$
+\end_inset
+
  and 
-\begin_inset Formula $r_{1}.$
+\begin_inset Formula $r_{2}.$
 \end_inset
 
 
@@ -1582,8 +1557,8 @@ reference "fig:bodide"
 
 .
  For these tests we generated at least 1000 signals at each signal-to-noise
- ratio, assuming the additive white gaussian noise (AWGN) channel, and processed
+ ratio, assuming the additive white gaussian noise (AWGN) channel, and we
- the data using each algorithm.
+ processed the data using each algorithm.
  For word error rates less than 0.1 it was necessary to process 10,000 or
  even 100,000 simulated signals in order to capture enough errors to make
  the measurements statistically meaningful.
@@ -1594,11 +1569,11 @@ reference "fig:bodide"
 
 \end_inset
 
- also shows theoretical results for comparison with the BM results.
+ also shows results calculated from theory for comparison with the BM results.
  The simulated BM results agree with theory to within about 0.1 dB.
  This difference between simulated BM results and theory is caused by small
  errors in the estimates of time- and frequency-offset of the received signal
- in the simulated results.
+ in the simulated data.
  Such 
 \begin_inset Quotes eld
 \end_inset
@@ -1615,7 +1590,7 @@ sync losses
 As expected, the soft-decision algorithms, FT and KV, are about 2 dB better
  than the hard-decision BM algorithm.
  In addition, FT has a slight edge (about 0.2 dB) over KV.
- On the other hand, the execution time for FT with 
+ On the other hand, the execution time for FT with timeout parameter 
 \begin_inset Formula $T=10^{5}$
 \end_inset
 
@@ -1624,7 +1599,7 @@ As expected, the soft-decision algorithms, FT and KV, are about 2 dB better
 \begin_inset Formula $T=10^{5}$
 \end_inset
 
- is small enough to be practical on most computers.
+ is small enough to be practical on most of today's home computers.
  
 \end_layout
 
@@ -1694,7 +1669,7 @@ reference "fig:bodide"
 
 \end_inset
 
- often extend downward to much smaller error rates, say 
+ often extend downward to even smaller error rates, say 
 \begin_inset Formula $10^{-6}$
 \end_inset
 
@@ -1711,18 +1686,18 @@ reference "fig:WER2"
 
 \end_inset
 
- shows the FT results for 
+ shows in this format the FT results for 
 \begin_inset Formula $T=10^{5}$
 \end_inset
 
- and the KV results that were shown in Figure 
+ and the KV results from Figure 
 \begin_inset CommandInset ref
 LatexCommand ref
 reference "fig:bodide"
 
 \end_inset
 
- in this format along with additional FT results for 
+, along with additional FT results for 
 \begin_inset Formula $T=10^{4},\:10^{3},\:10^{2}$
 \end_inset
 
@@ -1731,14 +1706,13 @@ reference "fig:bodide"
 \end_inset
 
 .
- The KV results are plotted with open squares.
  It is apparent that the FT decoder produces more decodes than KV when 
 \begin_inset Formula $T=10^{4}$
 \end_inset
 
  or larger.
  It also provides a very significant gain over the hard-decision BM decoder
- even when limited to at most 10 trials.
+ even when limited to 10 or fewer trials.
 \end_layout
 
 \begin_layout Standard
@@ -1794,12 +1768,12 @@ Percent of JT65 messages copied as a function of SNR in 2500 Hz bandwidth.
 \end_layout
 
 \begin_layout Standard
-The timeout parameter 
+Timeout parameter 
 \begin_inset Formula $T$
 \end_inset
 
- employed in the FT algorithm is the maximum number of symbol-erasure trials
+ is the maximum number of symbol-erasure trials allowed for a particular
- allowed for a particular attempt at decoding a received word.
+ attempt at decoding a received word.
  Most successful decodes take only a small fraction of the maximum allowed
  number of trials.
  Figure 
@@ -1810,8 +1784,9 @@ reference "fig:N_vs_X"
 \end_inset
 
  shows the number of stochastic erasure trials required to find the correct
- codeword versus the number of hard-decision errors in the received word
+ codeword vs.
- for a run with 1000 simulated transmissions at 
+ the number of hard-decision errors in the received word, for a run with
+ 1000 simulated transmissions at 
 \begin_inset Formula $\mathrm{SNR}=-24$
 \end_inset
 
@@ -1843,7 +1818,7 @@ reference "fig:N_vs_X"
  The variability of the decoding time also increases dramatically with the
  number of errors in the received word.
  These results provide insight into the mean and variance of the execution
- time for the FT algorithm, since execution time will be roughly proportional
+ time for the FT algorithm, since execution time is roughly proportional
  to the number of required trials.
 \end_layout
 
@@ -1928,11 +1903,15 @@ reference "fig:Psuccess"
  We include three curves for each decoding algorithm: one for the AWGN channel
  and no fading, and two more for simulated Doppler spreads of 0.2 and 1.0
  Hz.
- The simulated Doppler spreads are comparable to those encountered on HF
+ These simulated Doppler spreads are comparable to those encountered on
- ionospheric paths and for EME at VHF and lower UHF bands.
+ HF ionospheric paths and also for EME at VHF and the lower UHF bands.
  For reference, we note that the JT65 symbol rate is about 2.69 Hz.
- (*** A little more description of hinted decoding is needed here, and new
+ 
- data for the DS curves.***)
+\end_layout
+
+\begin_layout Standard
+(*** A little more description is needed here, along with new data for the
+ DS curves.***)
 \end_layout
 
 \begin_layout Standard