Exact error-rate analysis of diversity 16-QAM with channel estimation error.

IEEE Transactions on Communications 01/2004; 52:1019-1029.
Source: DBLP
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    ABSTRACT: We investigate the joint effect of channel estimation and frequency flat transmitter and receiver I/Q imbalance on an Orthogonal Frequency Division Multiplex (OFDM) system. We assume independent fading with identically and independently distributed (i.i.d) mirror carrier channel coefficients. Closed form expressions for symbol error rate and bit error rate of M-QAM modulation are derived. We consider join and separate channel estimation, as well as joint and separate equalization of the mirror carriers. Performance is evaluated by treating the I/Q interference as a non-Gaussian random variable. The results show that a Gaussian approximation of I/Q interference is very good, especially for low order modulations.
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    ABSTRACT: The use of generalized logarithmic likelihood ratio (GLLR), as a metric for soft-input decoding, was shown to provide gains over the conventional logarithmic likelihood ratio (LLR). However, computational complexity of the GLLR is greater than in the case of LLR, so the choice of GLLRs must be justified by a notable performance improvement. In this paper, we investigate the judiciousness of the adoption of GLLRs or LLRs for soft decoding analyzing the performance of both metrics in two different scenarios. Metrics expressions are derived and channel estimation errors are considered in analysis and simulation. Numerical results show that GLLRs outperform LLRs but, in general, the achieved improvement is relatively small. Therefore, application of GLLR metrics requires cautious analysis
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    ABSTRACT: Traditionally, the performance of blind SIMO channel estimates has been characterized in a deterministic fashion, by identifying those channel realizations that are not blindly identifiable. In this paper, we focus instead on the performance of Zero-Forcing (ZF) Linear Equalizers (LEs) or Decision-Feedback Equalizers (DFEs) for fading channels when they are based on (semi-)blind channel estimates. Although it has been known that various (semi-)blind channel estimation techniques have a receiver counterpart that is matched in terms of symbol knowledge hypotheses, we show here that these (semi-)blind techniques and corresponding receivers also match in terms of diversity order: the channel becomes (semi-)blindly unidentifiable whenever its corresponding receiver structure goes in outage. In the case of mismatched receiver and (semi-blind) channel estimation technique, the lower diversity order dominates. Various cases of (semi-)blind channel estimation and corresponding receivers are considered in detail. To be complete however, the actual combination of receiver and (semi-)blind channel estimation lowers somewhat the diversity order w.r.t. the ideal picture.
    Communications, Control and Signal Processing (ISCCSP), 2010 4th International Symposium on; 04/2010


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