IEEE Transactions on Communications, vol. 68, no. 3, Mar. 2020, pp. 1951-1965, DOI 10.1109/TCOMM.2019.2963023

Base Station Antenna Selection for Low-Resolution ADC Systems

Jinseok Choi (1), Junmo Sung (1), Narayan Prasad (2), Xiao-Feng Qi (2), Brian L. Evans (1), and Alan Gatherer (3)

(1) Department of Electrical and Computer Engineering, Wireless Networking and Communications Group, The University of Texas at Austin, Austin, Texas USA
jinseokchoi89@gmail.com - junmo.sung@utexas.edu - bevans@ece.utexas.edu

(2) Futurewei Technologies, Bridgewater, New Jersey USA.
narayan.prasad@futurewei.com - xiao.feng.qi@futurewei.com

(3) Futurewei Technologies, Plano, Texas USA.
alan.gatherer@futurewei.com

Paper published at IEEE Explore
Paper draft at arXiv

Multiantenna Communications Project

Abstract

For low-resolution analog-to-digital converter (ADC) systems, only high-complexity receive antenna selection has been developed and transmit antenna selection has been limited to a single antenna selection in prior work. In this paper, we propose low-complexity receive antenna selection algorithms and analyze transmit antenna selection by considering antenna selection at a base station with large antenna arrays and low-resolution ADCs. For downlink antenna selection, we show a selection criterion with zero-forcing precoding equivalent to a perfect quantization system; sum rate increases with number of selected antennas; derivation of the sum rate loss function from using a antenna subset; and sum rate loss reaches a maximum at a point of total transmit power and decreases beyond that point to converge to zero. For wideband orthogonal-frequency-division-multiplexing (OFDM) systems, our results hold when entire subcarriers share a common subset of antennas. For uplink antenna selection, we generalize a greedy antenna selection criterion; propose a quantization-aware fast antenna selection algorithm using the criterion; and derive a lower bound on sum rate achieved by the proposed algorithm. For wideband OFDM systems, we extend our algorithm and derive a lower bound on its sum rate. Simulation results validate theoretical analyses and show increases in sum rate over conventional algorithms.


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Last Updated 03/18/20.