Dynamic RF Chain Selection for Energy Efficient and Low Complexity Hybrid Beamforming in Millimeter Wave MIMO Systems

This paper proposes a novel architecture with a
framework that dynamically activates the optimal number of
radio frequency (RF) chains used to implement hybrid beamforming
in a millimeter wave (mmWave) multiple-input and
multiple-output (MIMO) system. We use fractional programming
to solve an energy efficiency maximization problem and exploit
the Dinkelbach method (DM) based framework to optimize the
number of active RF chains and data streams. This solution is
updated dynamically based on the current channel conditions,
where the analog/digital (A/D) hybrid precoder and combiner
matrices at the transmitter and the receiver, respectively, are
designed using a codebook-based fast approximation solution
called gradient pursuit (GP). The GP algorithm shows less run
time and complexity while compared to the state of the art orthogonal
matching pursuit (OMP) solution. The energy and spectral
efficiency performance of the proposed framework is compared
with the existing state of the art solutions such as the brute force
(BF), the digital beamformer and the analog beamformer. The
codebook-free approaches to design the precoders and combiners
such as alternating direction method of multipliers (ADMM) and
singular value decomposition (SVD) based solution are also shown
to be incorporated into the proposed framework to achieve better
energy efficiency performance.