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 -

(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


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.