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Performances of Convolutionally-Coded QAM Constellations that Map Non-Coded Bits

Performances of Convolutionally-Coded QAM Constellations that Map Non-Coded Bits. Vasile Bota, Zsolt Polgar, Mihaly Varga. Communications Department, Technical University Cluj-Napoca. Overview. Initial Assumptions Convolutional Codes Employed parameters, rates, puncturing, decoding

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Performances of Convolutionally-Coded QAM Constellations that Map Non-Coded Bits

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  1. Performances of Convolutionally-Coded QAM Constellations that Map Non-Coded Bits Vasile Bota, Zsolt Polgar, Mihaly Varga Communications Department, Technical University Cluj-Napoca

  2. Overview • Initial Assumptions • Convolutional Codes Employed • parameters, rates, puncturing, decoding • Soft-decision of the Non-coded Bits • BER Performances of the Studied Configurations • theoretical and simulation evaluations • effects of the non-coded bits • Spectral Efficiencies of the Studied Configurations • OFDM scheme • simulation evaluations • effects of the non-coded bits • practical conclusions - References

  3. Initial Assumptions - the number of bits/symbol of configuration i, ni, is split into nci coded bits and nni non-coded information bits, i.e. ni = nci + nni (1) - Studied configurations: the nc bits are mapped according the Mapping by Set Partitioning (MSP) method [2], which maximizes the Euclidean distance dEfree and the parallel distance dp in the trellis diagram - the configurations with all bits coded are included for reference; their performances are presented in [1] - the nn bits are mapped using a Gray mapping [2]. Table 1.

  4. Convolutional codes employed • are based on the “parent” Rp=1/2, K = 9 (256-state trellis), G = [561,753]8 - the codes with R = 2/3, ¾, 4/5, 5/6 are obtained by puncturing the parent code with the puncturing patterns of [3] - each bin is finished with a number of termination information bits which would bring the trellis to the “all-zero” state - to ensure the non-correlation between successive bins, which might be transmitted with different modulations and codes under different channel conditions, - the number of termination bits nt for the Rp = ½ and codes with R = m/(m+1) is: (2)

  5. Convolutional codes employed - the convolutional codes are decoded with the Viterbi algorithm: • the metric employed is the a posteriori probabilities of each bit, p(1/r,) p(0/r), [4] • the “cumulative distance” is computed by the product of the a posteriori probabilities of the bits corresponding to each path, [4]. • The “missing” bits of the punctured codes are replaced, by a posteriori probabilities equaling 1, according to the puncturing pattern. • The values of the a posteriori probabilities are obtained by the soft demapping procedure [5]

  6. Soft-decision of the non-coded bits - due to the MSP mapping, the coded bits define the 2nc subsets and the non-coded bits define the vectors within the subsets [2]; • once the coded bits are known, the subset is known [2]; • then the vector in the subset placed at the smallest dE from the received vector is chosen and its non-coded bits are the decided bits [2].

  7. Coded Configurations Studied - the coded modulations studied are the 16-QAM, with nci = 4 or 2 and 64-QAM with nci = 6,4 (table 1) coded with the R=1/2, 2/3, ¾, 4/5 and 5/6 mentioned above Rate of the coded configurations • Considering the 81 QAM payload-symbols bin, the n = nc + nn bits/symbol and the nt trellis-termination bits, the coded configuration rate is expressed by: (3)

  8. Rates of the coded configurations Table 2 Coding rates of the studied configurations -mapping non-code bits increase the coding rate of the configuration -a combination of coded bits, coded with a smaller coding rate (more powerful), and non-coded bits offers about the same coding rate as a configuration that maps only coded bits coded with a higher coding rate (less powerful) - e.g. for the 16-QAM, the configuration 4;2;2 R = ½ offers about the same coding rate as the 4;4;0 R = ¾.

  9. Rates of the coded configurations Table 2 shows that the codes with rates higher than 2/3 may be replaced by codes with R = ½ or 2/3 as follows: • - for the 16-QAM: • the 440 R=1/2 or 2/3 could provide coding rates up to 0.63 • the 422 R = ½ or 2/3 could provide coding rates between 0.7 up to 0.8 replacing the 440 coded with R=3/4, 4/5 and 5/6 • - for the 64-QAM: • the 660 R=1/2 could provide Rcfg=0.467 • the 642 R = ½ , 2/3 could provide Rcgf = 0.633 or 0.75 • the 624 R = ½ and 2/3 could provide Rcfg = 0.800 or 0.864 (replacing even the 660 R=1/2) * the configurations coded with the R=6/7 punctured code would be no longer studied since their coding gain is very small.

  10. Error Probabilities of the Studied Configurations • Due to the fact that the two types of bits mapped on the QAM symbol are decoded in different manners, their BER vs. SNR performances are analyzed separately. • The global BER, pg is expressed, in terms of the BER of the coded bits pec and of the non-coded bits pen, by: (4) • The BER vs. SNR performances of the convolutionally-coded QAM constellations that map non-coded bits are evaluated both theoretically and by computer simulation

  11. Theoretical evaluation of BER -the error probability of these coded constellations could be computed using the approach proposed in [2]. This involves the analysis of the trellis diagram to establish the dEfree which is a complex operation for K =9. - we propose an approximate method to evaluate the BER of these constellation a.Evaluation of pec • the BER of the coded bits requires a previous evaluation of the coding gain provided by the coded modulation, CG. • then, the BER is computed for the equivalent non-coded transmission which operates at a signal to noise ratio equaling SNR + CG, which is approximated by (5), [6]: (5)

  12. Theoretical evaluation of BER b. Evaluation of pen- the non-coded bits may be in error in two situations: • b.1 the coded bits are correctly decoded (1-pec), i.e. the correct subset is chosen and the soft-decision chooses the wrong vector within the subset. This is equivalent to the error-probability p’ of a QAM constellation with a minimum distance , where d0 denotes the minimum distance in the QAM constellation. (6) • b.2 the coded bits are in error, pce, and the non-coded bits are decided from the wrong subset; then the probability of error is p’’: (7) • the error-probability of the non-coded bits is, (6) and (7): (8)

  13. Theoretical evaluation of BER • - the global BER vs. SNR curve of the 16-QAM with nc = 2, nn = 2 coded with R=1/2 is shown in fig.1 for the theoretical evaluation (4-8) and in fig.2 for the computer-simulation evaluation (106 bits for every SNR value) • the similar curves of the 64-QAM with nc = 2, nn = 2 coded with R=1/2 are shown in figures 3 and 4. • results of figures 1-4 and additional comparisons show that the BER values provided by the approximate computation method are reasonably close to the ones delivered by computer simulations. • the method is accurate enough to provide a correct value of the spectral efficiency ensured by these constellations (to be explained later) and is more simple than the rigorous method. • simulations and separate theoretical computations (4-8) show that the error rate of the non-coded bits is smaller than the one of the coded bits. This property requires a more elaborate study.

  14. Theoretical evaluation of BER -1.5 -2 3.16 (-3) -2.5 -3 lg(BER) 3.16 (-4) -3.5 -4 -4.5 10 10.5 11 11.5 12 12.5 13 13.5 14 SNR -2 -2.5 -3 -3.5 lg(BER) -4 -4.5 -5 -5.5 -6 -6.5 15 15.5 16 16.5 17 17.5 18 18.5 19 19.5 20 SNR 3.16 (-4) 3.16 (-5) Figure 3 BER vs. SNR of the 6,4,2 R=1/2 (theoretical evaluation) Figure 1 BER vs. SNR of the 422 R=1/2 (theoretical evaluation) Figure 2 BER vs. SNR of the 422 R=1/2 (computer simulation) red – pen; blue – pec; green - peg Figure 4 BER vs. SNR of the 642 R=1/2 (computer simulation) red – pen; blue – pec; green - peg

  15. BER Performances the Studied Configurations • the BER of the studied configurations were evaluated by computer simulations using the platform described in [7]. • the performances were evaluated by the SNR required to ensure the BER = 1·10-5,because the coded configurations are to be employed in transmissions with packets of 81 QAM-symbols, i.e. 324 or 486 bits, with a packet error-rate smaller than 1∙10-2 - 5∙10-3. • the SNR required by the 16 and 64-QAM to ensure the same BER are 19.5 dB and 25.5 dB, so the coding gains can be computed by referring to these figures.

  16. BER Performances the Studied Configurations • as expected the coding gains decrease with the increase of the coding rate • the same equivalencies that were shown in table 2 occur for the BER performances. i.e. codes with rates higher than 2/3 may be replaced by codes with R = ½ or 2/3 using non-coded bits as follows: Table 3 The SNR requiredby the studied configurations to ensure BER = 1·10-5

  17. BER Performances the Studied Configurations lg BER 1 – 440 R=2/3 4 – 642 R=1/2 2 – 422 R=1/2 0 – 440 R=1/2 SNR 3 – 660 R=2/3 • for rates R = ½ and 2/3 • the 4;4;0 R = ½ ensures a coding gain of about 7.5 dB (curve 0 in figure 5) • the 4;4;0 R=2/3 offers about the same performances as 422 R=1/2, (curves 1,2 in figure 5) • the 6;6;0 R = 2/3 offers better performances as the 6;4;2 R = ½ (curves 3, 4 in figure 5) Fig.5. BER vs.SNR – Replacement of the R = 2/3, nci=0 by the R = 1/2, nci=2 for 16 and 64-QAM

  18. BER Performances the Studied Configurations lg BER 3 – 660 R=1/2 1 – 440 R=4/5 0 – 440 R=3/4 2 – 422 R=2/3 SNR • the 4;4;0 R=3/4 configuration may be replaced by the 4;2;2 R=2/3, for BER ≥ 10-5, while the 4;4;0 R =4/5 ensures a small coding gain. • the 660 R=1/2 offers about the same performances as the constellations above Figure 6. BER vs. SNR – Replacement of the R = 3/4, 4/5, nci=0 by the R = 2/3 , nci = 2 for 16-QAM and by R=1/2 nc =0, 64-QAM

  19. BER Performances the Studied Configurations 3 – 660 R=4/5 lg BER 0 – 624 R=2/3 0 – 660 R=3/4 2 – 624 R=1/2 1 – 642 R=2/3 4 – 642 R=3/4 • configurations 6;6;0 R=3/4, 6;4;2 R=2/3 and 6;2;4 R =1/2 have similar performances • configurations 6;6;0 R=4/5, 642 R=3/4 and 6;2;4 R =2/3 have similar performances Figure 7. BER vs. SNR – Equivalencies between 64-QAM configurations

  20. BER Performances the Studied Configurations lg BER 0 – 660 R=5/6 1 – 642 R=4/5 2 – 624 R=3/4 SNR - the 660 R=5/6 may be replaced by 642 R=4/5 or better by 624 R=3/4 Figure 8. BER vs. SNR – BER vs. SNR – replacement of the R = 5/6 and 4/5 for 64-QAM • the results of table 3 and figures 5-8 show that coded configurations that employ only coded bits, nci = 4 or 6 and nni =0, and high coding rates R = 5/6, 4/5 and even ¾ may be replaced, with about the same coding gains, by configurations that employ nni = 2 or even 4. • - this approach requires simpler implementation of the decoding algorithm and fewer puncturing patterns, at the expense of splitting the information bits into two flows and a soft-decision of the nn bits.

  21. Spectral efficiencies of the studied configurations - the spectral efficiencies are studied in an OFDM scheme with the following parameters of the user-bin [8]: • sub carrier spacing: fs = 39062.5 Hz • OFDM symbol length (excluding guard time): Ts = 25.60 μs. • guard time/cyclic prefix: GET = 3.20 μs (G = 0.125 - 1/8 OFDM symbol) • physical bin size: 312.5 KHz x 345.6 μs (BWb = 312.5 KHz; Tb = 345.6μs) • bin size in QAM-symbols: 8 x 12 = 96 = Vs; payload symbols Ps = 81; “service” symbols/bin Ss = 15. • the bin rate BR, including the guard interval, is: (9) - the nominal bit rate of a transmission using a configuration with ni bits/symbol is: Dci = BR·81·ni·Rcfgi (bit/s) (10) - the throughput is: Θci(SNR) = BR·81·ni·Rcfgi(1-BinERi(SNR)) (11)

  22. Spectral efficiencies of the studied configurations - in (11) BinERi denotes the bin-error rate, when configuration i is employed, i.e.: BinERi(SNR) = 1-(1-pgi(SNR))ni(12) pgi isthe bit error rate ensured by the configuration i (QAM const, convolutional code, nci and nni) for that value of SNR. - the spectral efficiency is obtained dividing the throughput by the bin bandwidth: (13) - replacing now the numerical values in (9), (10), (11) and (12) we get for the spectral efficiency: (14)

  23. Spectral efficiencies of the studied configurations - for an 81 QAM symbol bin, the BinEri < 0.5·10-3 - 1·10-2 would not affect significantly the spectral efficiency, both for transmissions governed or not by an H-ARQ protocol. - this would require a bit-error rate smaller than about 5∙10-4 - 1∙10-5. - the nominal spectral efficiencies of the studied configurations are presented in table 4 together with their configuration rates and SNR value required to ensure a pgi = 1∙10-5. • Note that the throughput can be computed by multiplying the ηinom (14) by the bin-bandwidth, i.e. 312.5 kHz.

  24. Spectral efficiencies of the studied configurations Table 4 Performances of the studied configurations – SNRs for BER=10-5, configuration rates and nominal spectral efficiencies

  25. Spectral efficiencies Practical conclusions 1 - 2.5 Group 3 2 - 2.1 Group 2 3 - 2.4 4 - 1.9 6 – 1.5 Group 1 5 – 1.35 13.4 16.8 10.3 - the 4;4;0 R=2/3 and ¾ may be replaced by 4;2;2 R=1/2 - the 4;4;0 R=4/5 and 5/6 may be replaced by 4;2;2 R=2/3 • figure 9 shows the ηi vs. SNR of the 16-QAM coded configs. • It shows that the 4;2;2 configurations have higher spectral efficiencies than the 4;4;0 with R > ½, in about the same SNR domains, groups 2 and 3 Figure 9 Spectral Efficiencies of the 16-QAM configs 0- 4;0;4; 1 – 4;2;2 ¾; 2 – 4;22; ½ 3- 4;4;0 5/6; 4 - 4;4;0 2/3; 5 – 4;4;0 ½; 6 -2;0;2

  26. Spectral efficiencies Practical conclusions 1 – 4.5 Group 6 2 – 4 Group 5 3 2 – 3.6 6 –3.66 Group 4 4 7 – 3.3 5 – 2.85 8 9 – 2.1 10 23.20 20.30 • - the 6;6;0 R = 2/3 may be replaced by 6;4;2 R=1/2 • - the 6;6;0 R =3/4, 4/5, 5/6 and 6;4;2 R=1/2 and ¾ may be replaced by 6;2;4 R=1/2 • - the 6;4;2 R=4/5 and 5/6 may be replaced 6;2;4 R=2/3 • figure 10 shows the spectral efficiencies of the 64-QAM configs. • in groups 5 and 6, according to the SNR domain, there is a 6;2;4 config that outperforms a 6;4;2 and a 6;6;0 configurations. In group 4, a 6;4;2 config. outperforms a 6;6;0 and the 4;0;4 configs. Figure 10 Spectral Efficiencies of the 64-QAM configs 0 – 6;0;6; 1- 6;2;4 3/4 ; 2 – 6;2;4 ½; 3 – 6;4;2 5/6; 4 – 6;4;2 2/3; 5 – 6;4;2 ½; 6 – 6;6;0 5/6; 7 – 6;6;0 ¾; 8 -6;6;0 2/3; 9 – 6;6;0 ½; 10- 4;0;4

  27. Spectral efficiencies Practical conclusions - comparing figures 9 and 10, note that the 6;6;0 R=1/2 may be replaced by 4;2;2 R=2/3 - coded configurations with only R=1/2 and 2/3 together with an appropriate combination between the numbers of coded and non-coded bits may ensure better or equivalent spectral efficiencies in at lower SNR domains, with about 1 dB. - the spectral efficiency increases are about 0.3-0.35 bps/Hz, which, considering the BWb = 312.5 kHz, lead to about some 100 kbps throughput increases, i.e. about 10% of the nominal throughput ensured by the coded configurations which map only coded bits.

  28. Global set of configurations employing the 16 and 64-QAM that map non-coded bits 1 – 4.0 2 – 3.6 3 – 2.85 4 – 2.5 5 – 2.1 8 – 2.1 6 – 1.35 7 – 1.5 10.3 13.7 17.4 20.3 23.3 • a set of configurations that ensure the highest spectral efficiencies is shown in figure 11. • the 6;6;0 R=1/2 is shown for comparison and below 7 dB a coded 4-QAM should be employed Figure 11 Spectral Efficiencies of a selected set of 16 and 64-QAM coded configs with n-c bits 0 – 6;0;6; 1- 6;2;4 ¾; 2- 6;2;4 ½; 3- 6;4;2 – 1/2 ; 4 – 4;2;2 3/4 ; 5 4;2;2 1/2 ; 6 – 4;4;0 ½; 7 – 2;0;2; 8 – 6;6;0 ½

  29. References (selected) [1] - V.Bota, M.Varga, Zs.Polgar, “Convolutional vs. LDPC Coding for Coded Adaptive-QAM Modulations on Mobile Radio Channels”, 9-th MCM, COST 289, Madrid, 2005 [2] – G.Ungerboeck, “ Trellis-Coded Modulation with Redundant Signal Sets, Part I and Part II”, IEEE Communications Magazine, vol.25, No.2, February 1987 [3] - Qualcomm –“Q1650 k=7 Multi-code rate Viterbi decoder” Technical data sheet, Qualcomm, 1991 [4] – S.Lin, D.Costello, “Error Control Coding. Fundamentals and Applications”, Prentice Hall, 1983 [5] – ITU-T , “LDPC codes for G.dmt.bis and G.lite.bis,” Temporary Document CF-060, 2000 [6] – X. Fuqin, “Digital Modulation Techniques”, ArtechHouse, 2000. [7] - V.Bota, M.Varga, Zs.Polgar, “Simulators of LDPC-Coded Multi-carrier Transmissions –LDPC-MC”, COST 289, 1st Workshop, Budapest, 2004. [8] – S.Falahati, coord., “Assessment of adaptive transmission technologies” Report D2.4 ver. 1.0 IST-Winner February, 2005

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