Last Update: March 4, 2010, October 16, 2011.
The
Figure 2 plot (shown below) displays the Simulated Bit Error Rate (BER) results for Convolutional Coded, Block Coded, and UnCoded cases where simulated
Discrete MultiTone (DMT) Modulation Signaling occurs over a
Non-Distorting, UnRestricted Bandwidth MultiCarrier/MultiChannel (MC).
If one compares
Figure 1 (shown below or on the 'Nolta Simulated Systems Introduction' webpage) to
Figure 2, one can readily see the effects of a
bandwidth-limited MC on BER Performance as follows:
1) For UnCoded DMT, increasing the E
b/N
0 has little effect in decreasing BER;
2) At low E
b/N
0 and for UnCoded and Coded DMT, there is a order of magnitude difference in BER, i.e., loss in BER Performance; and
3) At high E
b/N
0 and for UnCoded and Coded DMT, the BER spread increases dramatically.
Figure 2. Bit Error Probability for Coded and UnCoded DMT Signaling over
Non-Distorting, UnRestricted Bandwidth MultiCarrier/MultiChannel (MC)
with Additive White Gaussian Noise (AWGN):
r = 1/6, K = 4, [63,51,60,63] Best Non-Recursive Convolutional Code
and Viterbi Algorithm Decoder;
L = 3, N = 6, [3,5,6] Systematic Block Code and Likelihood Block
Decoder;
3-MC, {l} = [2,2,2]: Gray Coded QPSK, 4-PAM and 4-QAM,
SNRb: Eb/N0, QPSK = Eb/N0, 4-PAM = Eb/N0, 4-QAM;
Non-Distorting, UnRestricted Bandwidth MC.
Figure 1. Bit Error Probability for Coded and UnCoded DMT Signaling over
Distorting Bandwidth-Constrained MultiCarrier/MultiChannel (MC)
with Additive White Gaussian Noise (AWGN):
r = 1/6, K = 4, [63,51,60,63] Best Non-Recursive Convolutional Code
and Viterbi Algorithm Decoder;
L = 3, N = 6, [3,5,6] Systematic Block Code and Likelihood Block
Decoder;
3-MC, {l} = [2,2,2]: Gray Coded QPSK, 4-PAM and 4-QAM,
SNRb: Eb/N0, QPSK = Eb/N0, 4-PAM = Eb/N0, 4-QAM;
First Order Polynomial-based Low Pass Linear Filter MC.
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