  The ever-increasing demand for broadband Internet access has motivated the
further development of the digital subscriber line to the G.fast standard in
order to expand its operational band from 106 MHz to 212 MHz. Conventional
far-end crosstalk (FEXT) based cancellers falter in the upstream transmission
of this emerging G.fast system. In this paper, we propose a novel differential
evolution algorithm (DEA) aided turbo channel estimation (CE) and multi-user
detection (MUD) scheme for the G.fast upstream including the frequency band up
to 212 MHz, which is capable of approaching the optimal Cramer-Rao lower bound
of the channel estimate, whilst approaching the optimal maximum likelihood (ML)
MUD's performance associated with perfect channel state information, and yet
only imposing about 5% of its computational complexity. Explicitly, the turbo
concept is exploited by iteratively exchanging information between the
continuous value-based DEA assisted channel estimator and the discrete
value-based DEA MUD. Our extensive simulations show that 18 dB normalized mean
square error gain is attained by the channel estimator and 10 dB
signal-to-noise ratio gain can be achieved by the MUD upon exploiting this
iteration gain. We also quantify the influence of the CE error, of the copper
length and of the impulse noise. Our study demonstrates that the proposed DEA
aided turbo CE and MUD scheme is capable of offering near-capacity performance
at an affordable complexity for the emerging G.fast systems.
