2,547 research outputs found
Iterative joint channel and data estimation for rank-deficient MIMO-OFDM
In this paper we propose a turbo-detected multi-antenna-multi-carrier receiver scheme. Following the philosophy of the turbo processing, our turbo MIMO-OFDM receiver comprises a succession of detection modules, namely the channel estimator, the space-time detector and the decoder, which iteratively exchange soft bit-related information and thus facilitate a substantial improvement of the overall system performance. In this paper we analyze the achievable performance of the iterative system proposed with the aim of documenting the various design trade-offs, such as the achievable error-rate performance, the attainable data-rate as well as the associated computational complexity. Specifically, we report a virtually error-free performance for a rate-1/2 turbo-coded 8x8-QPSK-OFDM system, exhibiting an effective throughput of 8*2/2=8 bits/sec/Hz and having a pilot overhead of only 10%, at SNR of 7.5dB and normalized Doppler frequency of 0.003, which corresponds to a mobile terminal speed of about 65 km/h
Receiver Architectures for MIMO-OFDM Based on a Combined VMP-SP Algorithm
Iterative information processing, either based on heuristics or analytical
frameworks, has been shown to be a very powerful tool for the design of
efficient, yet feasible, wireless receiver architectures. Within this context,
algorithms performing message-passing on a probabilistic graph, such as the
sum-product (SP) and variational message passing (VMP) algorithms, have become
increasingly popular.
In this contribution, we apply a combined VMP-SP message-passing technique to
the design of receivers for MIMO-ODFM systems. The message-passing equations of
the combined scheme can be obtained from the equations of the stationary points
of a constrained region-based free energy approximation. When applied to a
MIMO-OFDM probabilistic model, we obtain a generic receiver architecture
performing iterative channel weight and noise precision estimation,
equalization and data decoding. We show that this generic scheme can be
particularized to a variety of different receiver structures, ranging from
high-performance iterative structures to low complexity receivers. This allows
for a flexible design of the signal processing specially tailored for the
requirements of each specific application. The numerical assessment of our
solutions, based on Monte Carlo simulations, corroborates the high performance
of the proposed algorithms and their superiority to heuristic approaches
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
Efficient space-frequency block coded pilot-aided channel estimation method for multiple-input-multiple-output orthogonal frequency division multiplexing systems over mobile frequency-selective fading channels
© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.An iterative pilot-aided channel estimation technique for space-frequency block coded (SFBC) multiple-input multiple-output orthogonal frequency division multiplexing systems is proposed. Traditionally, when channel estimation techniques are utilised, the SFBC information signals are decoded one block at a time. In the proposed algorithm, multiple blocks of SFBC information signals are decoded simultaneously. The proposed channel estimation method can thus significantly reduce the amount of time required to decode information signals compared to similar channel estimation methods proposed in the literature. The proposed method is based on the maximum likelihood approach that offers linearity and simplicity of implementation. An expression for the pairwise error probability (PEP) is derived based on the estimated channel. The derived PEP is then used to determine the optimal power allocation for the pilot sequence. The performance of the proposed algorithm is demonstrated in high frequency selective channels, for different number of pilot symbols, using different modulation schemes. The algorithm is also tested under different levels of Doppler shift and for different number of transmit and receive antennas. The results show that the proposed scheme minimises the error margin between slow and high speed receivers compared to similar channel estimation methods in the literature.Peer reviewe
On Optimal Turbo Decoding of Wideband MIMO-OFDM Systems Under Imperfect Channel State Information
We consider the decoding of bit interleaved coded modulation (BICM) applied
to both multiband and MIMO OFDM systems for typical scenarios where only a
noisy (possibly very bad) estimate of the channel is provided by sending a
limited number of pilot symbols. First, by using a Bayesian framework involving
the channel a posteriori density, we adopt a practical decoding metric that is
robust to the presence of channel estimation errors. Then this metric is used
in the demapping part of BICM multiband and MIMO OFDM receivers. We also
compare our results with the performance of a mismatched decoder that replaces
the channel by its estimate in the decoding metric. Numerical results over both
realistic UWB and theoretical Rayleigh fading channels show that the proposed
method provides significant gain in terms of bit error rate compared to the
classical mismatched detector, without introducing any additional complexity
Soft-Decision-Driven Channel Estimation for Pipelined Turbo Receivers
We consider channel estimation specific to turbo equalization for
multiple-input multiple-output (MIMO) wireless communication. We develop a
soft-decision-driven sequential algorithm geared to the pipelined turbo
equalizer architecture operating on orthogonal frequency division multiplexing
(OFDM) symbols. One interesting feature of the pipelined turbo equalizer is
that multiple soft-decisions become available at various processing stages. A
tricky issue is that these multiple decisions from different pipeline stages
have varying levels of reliability. This paper establishes an effective
strategy for the channel estimator to track the target channel, while dealing
with observation sets with different qualities. The resulting algorithm is
basically a linear sequential estimation algorithm and, as such, is
Kalman-based in nature. The main difference here, however, is that the proposed
algorithm employs puncturing on observation samples to effectively deal with
the inherent correlation among the multiple demapper/decoder module outputs
that cannot easily be removed by the traditional innovations approach. The
proposed algorithm continuously monitors the quality of the feedback decisions
and incorporates it in the channel estimation process. The proposed channel
estimation scheme shows clear performance advantages relative to existing
channel estimation techniques.Comment: 11 pages; IEEE Transactions on Communications 201
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