Proc. IEEE Global Communications Conference,
Dec. 4-8, 2017, Singapore, submitted.
ADC Bit Optimization for Spectrum- and Energy-Efficient Millimeter Wave Communications
Jinseok Choi (1),
Junmo Sung (1),
Brian L. Evans (1) and
Alan Gatherer (2)
(1) Department of Electrical and Computer Engineering,
Wireless Networking and Communications Group,
The University of Texas at Austin,
Austin, TX 78712 USA
(2) Huawei Technologies, Plano, Texas USA
Paper Draft -
Archive Page -
"ADC Bit Allocation for mmWave Massive MIMO Communication Receivers" (2017)
"ADC Bit Allocation under a Power Constraint
for MmWave Massive MIMO Communication Receivers"
Multiantenna Communications Project
A spectrum- and energy-efficient system is essential for millimeter
wave communication systems that require large antenna arrays with
We propose an ADC bit allocation (BA) algorithm that solves a minimum
mean square quantization error problem under a power constraint.
Unlike existing BA methods that only consider an ADC power constraint,
the proposed algorithm regards total receiver power constraint for a
hybrid analog-digital beamforming architecture.
The major challenge is the non-linearities in the minimization problem.
To address this issue, we first convert the problem into a convex
optimization problem through real number relaxation and substitution of
ADC resolution switching power with constant average switching power.
Then, we derive a closed-form solution by fixing the number of
activated radio frequency (RF) chains M.
Leveraging the solution, the binary search finds the optimal M and
its corresponding optimal solution.
We also provide an off-line training and modeling approach to estimate
the average switching power.
Simulation results validate the spectral and energy efficiency of the
In particular, existing state-of-the-art digital beamformers can be
used in the system in conjunction with the BA algorithm as it makes
the quantization error negligible in the low-resolution regime.
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Last Updated 04/15/17.