Parallel-Trellis Turbo Equalizers for Sparse-Coded Transmission over SISO and MIMO Sparse Multipath Channels

This paper describes a low-complexity turbo equalizer for coded sparse multipath channels whose length can span hundreds of symbol intervals. First, for single-input-single-output (SISO) systems, an existing parallel-trellis framework, which consists of a bank of identical regular trellises, is expl...

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Vydané v:IEEE transactions on wireless communications Ročník 5; číslo 12; s. 3568 - 3578
Hlavní autori: Lee, F.K.H., McLane, P.J.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway, NJ IEEE 01.12.2006
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Applied sciences
Banks
Channels
Computation
Computer simulation
Convolutional codes
Decoders
Decoding
Delay
Equalizers
Exact sciences and technology
Fading
Interleaved codes
MIMO
Monte Carlo methods
Multipath channels
Parallel processing
Studies
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Transmission and modulation (techniques and equipments)
Transmitting antennas
Turbo codes
Performance evaluation
decision feedback
convolutional interleaver
Equalizer
Multipath channels
Implementation
Parallel system
multiple-input-multiple-output
A posteriori estimation
Parallel processing
sparse multipath channels
turbo equalization
Fading channels
MIMO system
Monte Carlo method
Convolutional code
Interlacing
prefiltering
Turbo code
Decoding
Equalization
Channel coding
Computation time
Parallel-trellis
Numerical simulation
SISO system
Rayleigh fading
ISSN:1536-1276, 1558-2248
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Popis
Shrnutí:This paper describes a low-complexity turbo equalizer for coded sparse multipath channels whose length can span hundreds of symbol intervals. First, for single-input-single-output (SISO) systems, an existing parallel-trellis framework, which consists of a bank of identical regular trellises, is exploited to construct the maximum a posteriori (MAP) equalizer in the turbo equalizer. This MAP equalizer, when combined with prefiltering, can equalize a broad selection of sparse multipath channels, including those with nonminimum phase, by using only M-state trellises, where M is the constellation size. For multiple-input-multiple-output (MIMO) systems, a MIMO prefilter and a bank of M-state parallel-trellis MAP equalizers are deployed according to a layering structure. The total number of states needed is only N T M, where N T is the number of transmit antennae. For both SISO and MIMO systems, a class of binary convolutional and turbo codes having sparse generator polynomials are chosen as the coding schemes. These codes partially integrate channel interleaving with encoding, which allows a simple channel interleaver with low latency and memory storage requirement to be employed. The MAP decoders for these codes can also be implemented with the same parallel-trellis framework as the MAP equalizers. Overall, parallel processing is supported throughout the turbo equalizers. The amount of computational time reduction when compared to a turbo equalizer using a single-trellis MAP equalizer and decoder is proportional to the number of trellises in the parallel-trellis MAP equalizer and decoder. The performance of the parallel-trellis turbo equalizers is evaluated on static and Rayleigh fading sparse multipath channels via Monte Carlo simulations
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ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2006.256979