1,035 research outputs found
Achievable Outage Rates with Improved Decoding of Bicm Multiband Ofdm Under Channel Estimation Errors
We consider the decoding of bit interleaved coded modulation (BICM) applied
to multiband OFDM for practical scenarios where only a noisy (possibly very
bad) estimate of the channel is available at the receiver. First, a decoding
metric based on the channel it a posteriori probability density, conditioned on
the channel estimate is derived and used for decoding BICM multiband OFDM.
Then, we characterize the limits of reliable information rates in terms of the
maximal achievable outage rates associated to the proposed metric. We also
compare our results with the outage rates of a system using a theoretical
decoder. Our results are useful for designing a communication system where a
prescribed quality of service (QoS), in terms of achievable target rates with
small error probability, must be satisfied even in the presence of imperfect
channel estimation. Numerical results over both realistic UWB and theoretical
Rayleigh fading channels show that the proposed method provides significant
gain in terms of BER and outage rates compared to the classical mismatched
detector, without introducing any additional complexity
Information-Theoretic Foundations of Mismatched Decoding
Shannon's channel coding theorem characterizes the maximal rate of
information that can be reliably transmitted over a communication channel when
optimal encoding and decoding strategies are used. In many scenarios, however,
practical considerations such as channel uncertainty and implementation
constraints rule out the use of an optimal decoder. The mismatched decoding
problem addresses such scenarios by considering the case that the decoder
cannot be optimized, but is instead fixed as part of the problem statement.
This problem is not only of direct interest in its own right, but also has
close connections with other long-standing theoretical problems in information
theory. In this monograph, we survey both classical literature and recent
developments on the mismatched decoding problem, with an emphasis on achievable
random-coding rates for memoryless channels. We present two widely-considered
achievable rates known as the generalized mutual information (GMI) and the LM
rate, and overview their derivations and properties. In addition, we survey
several improved rates via multi-user coding techniques, as well as recent
developments and challenges in establishing upper bounds on the mismatch
capacity, and an analogous mismatched encoding problem in rate-distortion
theory. Throughout the monograph, we highlight a variety of applications and
connections with other prominent information theory problems.Comment: Published in Foundations and Trends in Communications and Information
Theory (Volume 17, Issue 2-3
MIMO-OFDM Optimal Decoding and Achievable Information Rates Under Imperfect Channel Estimation
Optimal decoding of bit interleaved coded modulation (BICM) MIMO-OFDM where
an imperfect channel estimate is available at the receiver is investigated.
First, by using a Bayesian approach involving the channel a posteriori density,
we derive a practical decoding metric for general memoryless channels that is
robust to the presence of channel estimation errors. Then, we evaluate the
outage rates achieved by a decoder that uses our proposed metric. The
performance of the proposed decoder is compared to the classical mismatched
decoder and a theoretical decoder defined as the best decoder in the presence
of imperfect channel estimation. Numerical results over Rayleigh block fading
MIMO-OFDM channels show that the proposed decoder outperforms mismatched
decoding in terms of bit error rate and outage capacity without introducing any
additional complexity
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