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- Results of (n,m)-ary FSK Phase Optimization Experiment 4/23/88 11am
- Franklin Antonio, N6NKF
- (this is a working paper -- do not republish)
-
- The idea was to find relative phases of three sinusoids, such that when they
- are added, the peak-to-average envelope ratio of the result is held as low
- as possible.
-
- This problem arises out of the desire to use a modulation where during each
- modulation symbol time, n out of a possible m tones are transmitted
- (ie (n,m)-ary FSK). Power amplifiers in SSB rigs are peak-power-limited,
- so the peak-to-average envelope ratio, (PAR), if greater than 1, will force us
- to reduce the average power level at the transmitter. If some parameter, say
- for example, the relative phases of the n tones, could be chosen to minimize
- PAR, and thus allow us a higher average power, then it should be. In the
- previous writeup, i argued that peak-to-average envelope is the right measure
- to use, and developed equations from which PAR can be calculated given the
- frequencies and phases of the tones.
-
- In the previous writeup (CREST.TXT) i showed that for the (2,m)-ary FSK case,
- PAR always = sqrt(2), no matter what phases are used. This means you can't
- choose optimum phases in the two-tone case, 'cause there aren't any.
-
- In the three tone case, i derived eqn-16, for the envelope of a unit power
- three-tone signal as a function of the frequencies and phases of the three
- tones. Because the signal is unit power, this is the PAR directly, ie we don't
- have to divide by the RMS power. I sure hope this equation is correct.
-
- a(t) = sqrt[ 1 + (2/3)*cos((W1-W2)*t+(P1-P2)) (16)
- + (2/3)*cos((W2-W3)*t+(P2-P3))
- + (2/3)*cos((W3-W1)*t+(P3-P1)) ]
-
- For any values of W1,W2,W3,P1,P2,P3, PAR is simply this equation, maximized
- over all values of t in [0,2pi]. Assuming we want to transmit (3,10)-ary FSK,
- we want to try all combinations of three out of 10 tones. That is, we want
- to try every combination of W1,W2,W3 chosen from [1,2,3,4,5,6,7,8,9,10],
- and for each such case, find optimum phases and the resulting PAR.
-
- I wrote a Fortran program to do this. The program uses a brute force search
- procedure. The program assumed P1=0, and did it's two-dimensional search over
- P2 & P3 in [0,2pi]. (There are really only two free variables, because it's
- the relative phases that matter.) To verify that this program was running
- correctly, i made an Excel spreadsheet into which i could pop the resulting
- frequencies and phases, and get on-screen plots of the resulting waveforms.
- (I ran the optimizing program on the IBM-AT, and did the spreadsheet on the
- MAC+.) Hopefully, this verifies correctness of eqn-16, and the optimization
- program. (but feel free to verify this yourself)
-
- Here are some of the results. The first three columns are the frequencies,
- the next three are the optimum phases, and finally, the PAR. Remember, PAR = 1
- = 0 db is as good as a single sinusoid, while PAR = sqrt(3) = 1.73 = 4.77 db
- is as bad as it is possible to do with three sinusoids, at the worst possible
- phases. You will note that the P1 column is always 0.
-
- [For those of you who think in terms of 'crest factor'... Crest factor is
- defined including another sqrt(2), so you can add 3 db to all the PAR's ]
-
- The first case that cranked out was encouraging...
-
- W1 W2 W3 P1 P2 P3 PAR
-
- 1 2 3 .0000 2.356 1.570 1.291
-
- That's not bad. 20*log10(1.29) = 2.2 db. An encouraging result. Ok, one
- down, 119 cases left to try. Another interesting point, is that all the
- other cases with equally-spaced tones, ie the triplets [2,3,4], [3,4,5],
- [4,5,6],...[1,3,5],[2,4,6],...[1,4,7],[2,5,8],...[1,5,9],[2,6,10], all have
- optimum phases which produce a PAR = 1.29 .
-
- Here are some more of the results...
-
- 1 2 4 .0000 2.356 3.926 1.533
- 1 2 5 .0000 .0000 3.141 1.622
- 1 2 6 .0000 1.571 4.712 1.664
- 1 2 7 .0000 .7854 1.571 1.683
- 1 2 8 .0000 .0000 3.141 1.693
- 1 2 9 .0000 1.571 3.141 1.699
- 1 2 10 .0000 .0000 3.141 1.710
- ...
- 1 3 4 .0000 1.571 .7854 1.534
- 1 3 5 .0000 .0000 3.141 1.289
- 1 3 6 .0000 .0000 1.571 1.657
- 1 3 7 .0000 1.571 1.571 1.531
- 1 3 8 .0000 1.571 .7854 1.692
- ...
- 3 4 5 .0000 1.963 .7854 1.291
- 3 4 6 .0000 1.571 1.571 1.535
- 3 4 7 .0000 .3927 4.712 1.624
- 3 4 8 .0000 .0000 3.141 1.665
- 3 4 9 .0000 .0000 3.141 1.686
- 3 4 10 .0000 .3927 5.890 1.699
-
- Some patterns emerge. First, all those phases look familiar, don't they?
- They're simple rational numbers * pi. 0.3927 = pi/8, for example. Makes me
- wish i had solved the thing algebraically. As a practical matter, of course,
- brute force computer generated numbers are as good as any.
-
- There are multiple solutions, ie multiple values of P2,P3 that achieve the
- same PAR. For example, whenever W1=1 & W2=2, the phases (0,0,pi) are also
- solutions. The computer simply picks one of the possibilities. It also
- appears that whenever W1=1 & W2=3, one of the following sets of phases (but not
- both): (0,0,pi) or (0,0,pi/2) always works. I haven't tried to prove this.
- I just discovered it while playing around.
-
- Notice that as the spacing between the tones becomes more disparate, the
- best achievable PAR gets worse and worse. For most choices of frequencies, in
- fact, the best possible PAR is very very close to the worst possible PAR.
-
- 1.710 --> 4.66 db best possible for tones @ 1,2,10
- sqrt(3) --> 4.77 db worst possible any 3 tone freq & phase
-
-
- Conclusion:
-
- A few combinations of tones have optimized phases that can reduce the peak-to-
- average by as much as 2.6 db (ie reduce from 4.7 db for naive adding, to 2.2 db
- as in the case of the optimized 1-2-3 signal). Unfortunately, there are many
- other combinations of tones for which the optimum is within a few percent of
- the worst possible choice of phases.
-
- My conclusion, at this point, is that optimization of phases in a 3-tone signal
- is NOT worthwhile.
-
-