Proc. IEEE International Conference on Acoustics, Speech and Signal Processing,
March 5-9, 2017, New Orleans, LA.
ADC Bit Allocation Under a Power Constraint for mmWave Massive MIMO Communication Receivers
Jinseok Choi (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
jinseokchoi89@gmail.com -
bevans@ece.utexas.edu
(2) Huawei Technologies, Plano, Texas USA
Paper Draft -
Archive Page -
Slides -
Software Release
Related journal paper:
"Resolution-Adaptive Hybrid MIMO Architectures for Millimeter Wave Communications" (2018)
Related conference papers:
"ADC Bit Optimization for Spectrum- and Energy-Efficient Millimeter Wave Communications" (2007)
"Space-Time Fronthaul Compression of Complex Baseband Uplink LTE Signals" (2016)
Related poster:
"ADC Bit Allocation under a Power Constraint
for MmWave Massive MIMO Communication Receivers"
Multiantenna Communications Project
Abstract
Millimeter wave (mmWave) systems operating over a wide bandwidth and
using a large number of antennas impose a heavy burden on power consumption.
In a massive multiple-input multiple-output (MIMO) uplink, analog-to-digital
converters (ADCs) would be the primary consumer of power in the base station
receiver.
This paper proposes a bit allocation (BA) method for mmWave multi-user (MU)
massive MIMO systems under a power constraint.
We apply ADCs to the outputs of an analog phased array for beamspace projection
to exploit mmWave channel sparsity.
We relax a mean square quantization error (MSQE) minimization problem and map
the closed-form solution to non-negative integer bits at each ADC.
In link-level simulations, the proposed method gives better communication
performance than conventional low-resolution ADCs for the same or less power.
Our contribution is a near optimal low-complexity BA method that minimizes
total MSQE under a power constraint.
Questions & Answers
Q1.
In the paper, it is assumed that the channel state information is known at receivers (CSIR),
and the proposed algorithm exploits the channel information to allocate bits.
Then, without the CSIR assumption, how are you going to estimate the channel?
A1.
In many papers, the mmWave channel estimation techniques for low-resolution ADC or even 1-bit systems have been developed and showed good accuracy.
In our low-resolution system, we can employ such techniques by fixing the ADC resolutions.
Q2.
How often should the ADC resolution switching occur?
A2.
The best switching scenario is to switch the resolution at each channel coherence time.
But in mmWave channels that have much shorter coherence time than the sub-3GHz channels,
the coherence-time switching may not be possible.
In this case, the switching can operate at the time scale of slowly changing channel characteristics
such as large-scale fading and angle-of-arrival as they are the dominant factor for the bit allocation.
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Last Updated 11/15/18.