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				| @ -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 | ||||
|  the HF bands with low power, modest antennas, and efficient spectral usage. | ||||
|  It was soon found that JT65 also enables worldwide communication on the | ||||
|  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 | ||||
|  be among the most likely ones to be received. | ||||
|  smaller list of messages (say, a few thousand messages or less) that we | ||||
|  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 | ||||
|  lists of hypothetical messages and their corresponding codewords, at very | ||||
|  little computational expense. | ||||
|  Saving a list of previously decoded callsigns and associated locators makes | ||||
|  it easy to generate lists of hypothetical messages and their corresponding | ||||
|  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  | ||||
| \begin_inset Quotes eld | ||||
| \end_inset | ||||
| 
 | ||||
| small enough | ||||
| \begin_inset Quotes erd | ||||
| \end_inset | ||||
| 
 | ||||
|  to establish adequate confidence, while still ensuring that false decodes | ||||
|  are rare. | ||||
|  that is small enough 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  | ||||
| \begin_inset Formula $r_{1},$ | ||||
|  can be a more relaxed limit than the  | ||||
| \begin_inset Formula $r_{1}$ | ||||
| \end_inset | ||||
| 
 | ||||
|  as used in the FT algorithm. | ||||
|  For the limited subset of messages established by operator experience as | ||||
|   | ||||
| \begin_inset Quotes eld | ||||
| \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  | ||||
|  used in the FT algorithm. | ||||
|  For the limited subset of messages that operator experience suggests to | ||||
|  be likely, hinted decodes can be obtained at lower signal levels than required | ||||
|  for those 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,  | ||||
| \begin_inset Formula $N_{0}$ | ||||
| \end_inset | ||||
| 
 | ||||
| . | ||||
|  noise power spectral density. | ||||
|  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, | ||||
|  where we describe a number of simulations carried out to compare performance | ||||
|  of the FT algorithm with others, and with theoretical expectations. | ||||
|  Examples of both presentations are included in the following discussion, | ||||
|  where we describe simulations carried out to compare performance of FT | ||||
|  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 | ||||
|  the data using each algorithm. | ||||
|  ratio, assuming the additive white gaussian noise (AWGN) channel, and we | ||||
|  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 | ||||
|  allowed for a particular attempt at decoding a received word. | ||||
|  is the maximum number of symbol-erasure trials allowed for a particular | ||||
|  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 | ||||
|  for a run with 1000 simulated transmissions at  | ||||
|  codeword vs. | ||||
|  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 | ||||
|  ionospheric paths and for EME at VHF and lower UHF bands. | ||||
|  These simulated Doppler spreads are comparable to those encountered on | ||||
|  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 | ||||
|  | ||||
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