Signal Processing - September 2017 - 157

measure the channel matrix. Hence, the calculation of the
precoding matrix must rely on feedback from the receivers.
Two main types of feedback have been considered: channel
estimation feedback and signal error feedback. Channel estimation feedback is based on the transmission of orthogonal
(synchronized) pilot symbols from all transmitters simultaneously and an estimation of a row of the channel matrix by each
receiver. This estimated row is then transmitted (through the
upstream) back to the transmitter, which uses it to construct
the full channel matrix H and calculate the precoding matrix.
Signal error feedback is a more DSL-specific method based
on the feedback of a quantized version of the error signal measured by each receiver [58]. The ONU groups all the error signal feedback from each CPE into a vector to adapt the precoder
coefficient matrix. A simpler version of an adaptive precoder
was proposed independently by Louveaux and van der Veen
[13] and by Bergel and Leshem [14]. The adaptive precoder was
shown to be very robust and converged in all channels with a
strong RWDD property [59], [60]. However, these approaches
lost their attractiveness when the new G.fast standard adopted
a TDD approach. Thus, in G.fast, the ONU can directly measure the channel in the upstream phase and use its estimation
in the downstream phase with no need for feedback.

employs DMT modulation of size K subcarriers of width
51.75 KHz for each user, corresponding to a total K = 2,048
subcarriers for the 106-MHz G.fast system and K = 4,096
subcarriers for the 212-MHz G.fast system. The channel
matrix is diagonally dominant at the lower frequencies but
not at the higher frequency tones. Each user transmits a QAM
symbol (with a rate of 48,000 symbols per second) of unit
energy with a gain scaling factor to control transmission
power. The per-tone PSD mask is based on the frequency of
operation: -65 dBm/Hz for f # 30 MHz, -76  dBm/Hz for
30 MHz 1 f # 106 MHz, and -79 dBm/Hz for f > 106 MHz.
Each transceiver has a total maximum transmit power of
4 dBm. The additive noise is AWGN with a PSD of -140 dBm/
Hz. The target bit error rate is set to 10 - 7, and an SNR gap is
C = 9.75 dB. The specified noise margin of 6 dB and coding
gain of 5 dB lead to a transmission gap of 10.75 dB. The
G.fast limits bit loading to 12 bit per tone, i.e., a QAM constellation size of up to 4,096 points.

Channel coherence time

The G.fast transmission technology is under development and
has features that are different than the current vectored VDSL
technology. The techniques developed for the VDSL system
thus cannot simply be applied to the G.fast system. Still,
efficient design methodologies for the G.fast system are
required to deliver data at the rate of 1 gigabit/s per user over
short telephone lines. Recently, various novel techniques have
been developed for the G.fast system. These techniques are
still not sufficient to reach the desired rates with currently
available hardware. In this section, we discuss various differences between G.fast and VDSL, give an overview of recent
research, and highlight the design considerations for the G.fast
system. We also point out some important topics for G.fast
implementation that have not been studied sufficiently and
require further research.

The DSL channel is slowly time varying because it consists
of twisted-pair copper wires in a static cable binder with
fixed user terminals. The time variability can be attributed
mainly to customer-wiring changes and temperature variations on a time scale of a few minutes or more. Therefore, the
DSL channel has a long coherence time (defined as the time
in which there is no effective variation in the channel impulse
response). This has several advantages with regard to DSL
system design in contrast to wireless communication systems. Furthermore, it allows multiuser operation with as
many as 100 users simultaneously, an order of magnitude
larger than existing MIMO wireless systems. The long coherence time allows for almost perfect CSI acquisition. This
enables the robust design of crosstalk cancelation schemes.
In addition, tracking and updating of the channel matrix is
less frequent, which reduces the overhead required for pilot
symbols inserted between the data symbols. With large channel coherence, iterative algorithms for power allocation as
well as crosstalk cancelation are feasible, even with a very
large number of lines.

G.fast characteristics

Channel estimation and calibration

We first present a concise representation of the main G.fast
characteristics, as a complement to the general system model
given in the "Wireline Discrete Multitone Technology" section. The G.fast transmission model consists of N vectored
users (typically up to 100) and operates over loop lengths
shorter than 250 m. The G.fast standard targets an aggregate
data rate (combined upstream and downstream) of 1 gigabit/s
per user. The data rate performance of the G.fast system is
limited by FEXT, since NEXT is eliminated with the TDD
scheme, which provides independent transmissions on
upstream and downstream directions over the whole bandwidth. The transmission bandwidth starts at 2.2 MHz and
ends at 106 MHz for the low-bandwidth version of G.fast,
and ends at 212 MHz for the upcoming version. The system

As previously discussed, the long coherence time enables the
receivers to obtain very good channel estimates, which are
important for crosstalk cancelation. Hence, channel-matrix
estimation in upstream transmission is much easier than in the
downstream. In upstream transmission, users transmit known
training symbols, and a simple least-squares technique can be
used to estimate the channel matrix at the DP. The length of
each user's training symbols should be at least equal to the
number of vectored users. In the downstream, the channel
estimation is carried out at the user terminals, where each row
of the channel matrix is estimated. This increases the complexity of the users' modem and power consumption.
However, the main challenge is to forward the estimated channel from each user to the DP.

Design considerations and challenges for G.fast

IEEE SIGNAL PROCESSING MAGAZINE

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September 2017

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Table of Contents for the Digital Edition of Signal Processing - September 2017

Signal Processing - September 2017 - Cover1
Signal Processing - September 2017 - Cover2
Signal Processing - September 2017 - 1
Signal Processing - September 2017 - 2
Signal Processing - September 2017 - 3
Signal Processing - September 2017 - 4
Signal Processing - September 2017 - 5
Signal Processing - September 2017 - 6
Signal Processing - September 2017 - 7
Signal Processing - September 2017 - 8
Signal Processing - September 2017 - 9
Signal Processing - September 2017 - 10
Signal Processing - September 2017 - 11
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Signal Processing - September 2017 - 13
Signal Processing - September 2017 - 14
Signal Processing - September 2017 - 15
Signal Processing - September 2017 - 16
Signal Processing - September 2017 - 17
Signal Processing - September 2017 - 18
Signal Processing - September 2017 - 19
Signal Processing - September 2017 - 20
Signal Processing - September 2017 - 21
Signal Processing - September 2017 - 22
Signal Processing - September 2017 - 23
Signal Processing - September 2017 - 24
Signal Processing - September 2017 - 25
Signal Processing - September 2017 - 26
Signal Processing - September 2017 - 27
Signal Processing - September 2017 - 28
Signal Processing - September 2017 - 29
Signal Processing - September 2017 - 30
Signal Processing - September 2017 - 31
Signal Processing - September 2017 - 32
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Signal Processing - September 2017 - 34
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Signal Processing - September 2017 - 106
Signal Processing - September 2017 - 107
Signal Processing - September 2017 - 108
Signal Processing - September 2017 - 109
Signal Processing - September 2017 - 110
Signal Processing - September 2017 - 111
Signal Processing - September 2017 - 112
Signal Processing - September 2017 - 113
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Signal Processing - September 2017 - 125
Signal Processing - September 2017 - 126
Signal Processing - September 2017 - 127
Signal Processing - September 2017 - 128
Signal Processing - September 2017 - 129
Signal Processing - September 2017 - 130
Signal Processing - September 2017 - 131
Signal Processing - September 2017 - 132
Signal Processing - September 2017 - 133
Signal Processing - September 2017 - 134
Signal Processing - September 2017 - 135
Signal Processing - September 2017 - 136
Signal Processing - September 2017 - 137
Signal Processing - September 2017 - 138
Signal Processing - September 2017 - 139
Signal Processing - September 2017 - 140
Signal Processing - September 2017 - 141
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Signal Processing - September 2017 - 143
Signal Processing - September 2017 - 144
Signal Processing - September 2017 - 145
Signal Processing - September 2017 - 146
Signal Processing - September 2017 - 147
Signal Processing - September 2017 - 148
Signal Processing - September 2017 - 149
Signal Processing - September 2017 - 150
Signal Processing - September 2017 - 151
Signal Processing - September 2017 - 152
Signal Processing - September 2017 - 153
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Signal Processing - September 2017 - 155
Signal Processing - September 2017 - 156
Signal Processing - September 2017 - 157
Signal Processing - September 2017 - 158
Signal Processing - September 2017 - 159
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Signal Processing - September 2017 - 187
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Signal Processing - September 2017 - 189
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Signal Processing - September 2017 - 191
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Signal Processing - September 2017 - 193
Signal Processing - September 2017 - 194
Signal Processing - September 2017 - 195
Signal Processing - September 2017 - 196
Signal Processing - September 2017 - Cover3
Signal Processing - September 2017 - Cover4
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