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A natural question is whether the optimal training design for the initialization phase using PPSAM scheme is still optimal for subsequent iterations of an iterative channel estimator.
Moreover, by multiplexing the training sequence before precoder, training symbols can be exploited in both the initialization and iteration phases of the iterative channel estimation process.
Does the iterative channel decoding and estimation converge, and how many iterations are sufficient? 2.
Does the iterative channel decoding and estimation converge, and how many iterations are sufficient?
a Iterative channel decoding and state estimation, b Iterative channel decoding and state estimation with previous observation, c Iterative channel decoding and state estimation without previous observation.
Figure 1 Iterative channel estimation and decoding for MIMO-OFDM.
(iii) Use also data symbols for channel estimation, by iterative channel estimation.
The system has an iterative channel decoder using bit log-likelihood ratio information.
The detailed operation of the iterative channel estimator is discussed in the following sections.
In the previous section we illustrated how iterative channel estimation can provide a significant performance gain.
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Figure 5 Comparison of FER performance obtained with the optimal PPSAM, sub-optimal PPSAM and PSAM scheme-over a 4 × 2 block-fading channel with n c = 2, when N = 2 and n p = 2 after 1 and 5 iterations of iterative channel-estimation/demodulation/decoding.
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