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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.


English