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Journal ArticleDOI

Combined equalization and coding using precoding

G.D. Forney, +1 more
- 01 Dec 1991 - 
- Vol. 29, Iss: 12, pp 25-34
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TLDR
The principal classes of classical equalization techniques are described, and Tomlinson-Harashima precoding is introduced, and it is shown that precoding combines nicely with coded modulation and with a technique known as shaping.
Abstract
Recently developed techniques that achieve the joint objectives of increasing the signaling rate so as to use the maximum possible channel bandwidth, and then using powerful equalization techniques to cope with the resulting distortion are reviewed. These techniques generalize the Tomlinson-Harashima precoding techniques, which were proposed more than 20 years ago. The principal classes of classical equalization techniques are described, and Tomlinson-Harashima precoding is introduced. It is shown that precoding combines nicely with coded modulation and with a technique known as shaping. It is also shown that, in principle, optimized combinations of coding, shaping, and precoding can achieve nearly the channel capacity of any strictly band-limited, high-SNR Gaussian channel, and in practice can approach capacity within about 3 dB or less. >

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Citations
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On the achievable throughput of a multiantenna Gaussian broadcast channel

TL;DR: Under certain mild conditions, this scheme is found to be throughput-wise asymptotically optimal for both high and low signal-to-noise ratio (SNR), and some numerical results are provided for the ergodic throughput of the simplified zero-forcing scheme in independent Rayleigh fading.
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A practical discrete multitone transceiver loading algorithm for data transmission over spectrally shaped channels

TL;DR: A finite-granularity, loading algorithm for a discrete multitone (DMT) modulation system that offers significant implementational advantages over the well-known water-pouring method and the earlier Hughes-Hartogs algorithm while typically suffering only negligible performance degradation relative to the optimal solution.
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Optimal designs for space-time linear precoders and decoders

TL;DR: A new paradigm for the design of transmitter space-time coding is introduced that is referred to as linear precoding, which leads to simple closed-form solutions for transmission over frequency-selective multiple-input multiple-output (MIMO) channels, which are scalable with respect to the number of antennas, size of the coding block, and transmit average/peak power.
Journal ArticleDOI

Modulation and coding for linear Gaussian channels

TL;DR: This paper surveys how the capacity of the linear Gaussian channel has been met during the past half century, and new capacity-approaching techniques include turbo coding and decoding, multilevel coding, and combined coding/precoding for intersymbol-interference channels.
References
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Channel coding with multilevel/phase signals

TL;DR: A coding technique is described which improves error performance of synchronous data links without sacrificing data rate or requiring more bandwidth by channel coding with expanded sets of multilevel/phase signals in a manner which increases free Euclidean distance.
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Multicarrier modulation for data transmission: an idea whose time has come

TL;DR: The general technique of parallel transmission on many carriers, called multicarrier modulation (MCM), is explained, and the performance that can be achieved on an undistorted channel and algorithms for achieving that performance are discussed.
Journal ArticleDOI

Maximum-likelihood sequence estimation of digital sequences in the presence of intersymbol interference

TL;DR: In this paper, a maximum likelihood sequence estimator for a digital pulse-amplitude-modulated sequence in the presence of finite intersymbol interference and white Gaussian noise is developed, which comprises a sampled linear filter, called a whitened matched filter, and a recursive nonlinear processor, called the Viterbi algorithm.
Journal ArticleDOI

Adaptive equalization

TL;DR: In this article, the authors give an overview of the current state of the art in adaptive equalization and discuss the convergence and steady-state properties of least mean square (LMS) adaptation algorithms.