A non-iterative receiver is proposed to achieve near capacity performance on intersymbol
interference (ISI) channels. There are two main ingredients in the proposed
design. i) The use of a novel BCJR-DFE equalizer which produces optimal soft
estimates of the inputs to the ISI channel given all the observations from the channel
and L past symbols exactly, where L is the memory of the ISI channel. ii) The
use of an encoder structure that ensures that L past symbols can be used in the
DFE in an error free manner through the use of a capacity achieving code for a
memoryless channel. Computational complexity of the proposed receiver structure
is less than that of one iteration of the turbo receiver. We also provide the proof
showing that the proposed receiver achieves the i.i.d. capacity of any constrained
input ISI channel. This DFE-based receiver has several advantages over an iterative
(turbo) receiver, such as low complexity, the fact that codes that are optimized for
memoryless channels can be used with channels with memory, and finally that the
channel does not need to be known at the transmitter. The proposed coding scheme
is universal in the sense that a single code of rate r; optimized for a memoryless
channel, provides small error probability uniformly across all AWGN-ISI channels of
i.i.d. capacity less than r:
This general principle of a proposed non-iterative receiver also applies to other
signal processing functions, such as timing recovery, pattern-dependent noise whiten ing, joint demodulation and decoding etc. This makes the proposed encoder and
receiver structure a viable alternative to iterative signal processing. The results show
significant complexity reduction and performance gain for the case of timing recovery
and patter-dependent noise whitening for magnetic recording channels.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/3899 |
| Date | 16 August 2006 |
| Creators | Nangare, Nitin Ashok |
| Contributors | Narayanan, Krishna R. |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | 639266 bytes, electronic, application/pdf, born digital |
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