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Hybrid Processing in Massive MIMO for 5G Mobile Networks
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Prof.Xiaodai Dong
Department of Electricaland Computer Engineering,
University of Victoria, Victoria, Canada
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The 5G mobile cellular network will likely employ a
large number of antennas at the base station (BS). Massive
multiple-input multiple-output (MIMO) is potentially one of
the key technologies to achieve high capacity performance in
the next generation mobile cellular systems. Despite of its
high spectral efficiency in theory, the implementation of
massive MIMO faces significant challenges. Each antenna in
the conventional MIMO system is supported by an expensive radio
frequency (RF) chain that includes analog-to-digital converter (ADC)
or digital-to-analog converter (DAC), mixer for frequency downconversion
or upconversion, bandpass filter, and low noise
amplifier or power amplifier. When the number of antennas
scales up to tens or hundreds of antennas, it is impossible to
maintain an independent RF chain for each antenna, from the cost
and power consumption perspective. Recently, a promising solution
proposed for MIMO systems with limited RF chains is to use hybrid
structures. That is, the full complexity precoding/combining
operation with the number of RF chains equal to the number of
antennas is now replaced by the phase shifters based analog RF
processing with dimension equal to the number of antennas and
digital baseband processing withlow dimension equal to much fewer
RF chains. In this talk, we first review the latest developments
in the hybrid processing design of massive MIMO. Then a low complexity
hybrid zero-forcing based precoding in massive multiuser MIMO with
single antenna users will be introduced, followed by a hybrid block
diagonalization processing for massive multiuser MIMO with
multi-antenna users. Potential future work in this area will also
be discussed.
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