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Performance Evaluation of Coordinated Multi-Point Transmission
Schemes with Predicted CSI.
Jingya Li
, Chalmers,
Agisilaos Papadogiannis
,
Rikke Apelfröjd
, Uppsala University
Tommy Svensson
, Chalmers, and
Mikael Sternad
Uppsala University.
IEEE Conference on Personal, Indoor and Mobile
Radio Communications, PIMRC
Sept 2012, Sydney, Australia, pp 1055-1060.
© 2012 IEEE
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Abstract:
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Coordinated multi-point (CoMP) transmission is
considered as an efficient technique to improve cell-edge performance
as well as system spectrum efficiency. In CoMP-enabled
systems, a cluster of coordinated base stations (BSs)
are typically assumed to be connected to a control unit (CU) via
backhaul links, and the provided performance gain relies heavily
on the quality of the channel state information (CSI) available
at the CU side.
In this paper, we consider the downlink of a
CoMP cluster and compare three different CoMP transmission
schemes:
- zero-forcing coherent joint transmission,
- non-coherent
joint transmission and
- coordinated scheduling.
Moreover, for
each of the analyzed schemes, the performance in terms of
average sum rate of the CoMP cluster is studied with predicted
CSI, considering the effects of the feedback and backhaul
latency, as well as the user mobility.
Compared to zero-forcing
coherent joint transmission, we show that non-coherent joint
transmission and coordinated scheduling are more robust to
channel uncertainty.
In addition, depending on the latency, user
mobility and user locations, different schemes would achieve the
highest average sum rate performance. Hence, a system could
switch between the transmission schemes to improve the sum
rate.
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Related publications:
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PhD Thesis by Rikke Apelfröjd of Kalman prediction and applications, April 2018.
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- Report by Rikke Apelfröjd
on Kalman prediction for multipoint OFDM downlink channels, May 2014, revised March 2018.
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EURASIP JWCN paper 2014 that evaluates robust linear
precoding and simple user grouping on measured channels.
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Channel Estimation and Prediction for MIMO
OFDM Systems: Key design and performance aspects
of Kalman-based algorithms.
PhD Thesis by Daniel Aronsson, 2012.
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Source:
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