TY - GEN
T1 - A discrete first-order method for large-scale MIMO detection with provable guarantees
AU - Liu, Huikang
AU - Yue, Man Chung
AU - So, Anthony Man Cho
AU - Ma, Wing Kin
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/19
Y1 - 2017/12/19
N2 - In this paper, we consider a simple and low-complexity discrete first-order method called the Generalized Power Method (GPM) for large-scale MIMO detection. The GPM is essentially a projected gradient method and exploits the fact that the projection onto the discrete MPSK or QAM constellation is efficiently computable. As our main contribution, we first show that under certain conditions on the channel and additive noise, the GPM will converge to the true symbol vector in a finite number of iterations. We then show that the aforementioned conditions will be satisfied with high probability under standard probabilistic models of the channel and noise. Besides enjoying strong theoretical guarantees, the proposed method is shown in our simulations to be competitive with existing methods in terms of both detection performance and numerical efficiency. We believe that our techniques will find further applications in the development of high-performance detection methods for massive MIMO.
AB - In this paper, we consider a simple and low-complexity discrete first-order method called the Generalized Power Method (GPM) for large-scale MIMO detection. The GPM is essentially a projected gradient method and exploits the fact that the projection onto the discrete MPSK or QAM constellation is efficiently computable. As our main contribution, we first show that under certain conditions on the channel and additive noise, the GPM will converge to the true symbol vector in a finite number of iterations. We then show that the aforementioned conditions will be satisfied with high probability under standard probabilistic models of the channel and noise. Besides enjoying strong theoretical guarantees, the proposed method is shown in our simulations to be competitive with existing methods in terms of both detection performance and numerical efficiency. We believe that our techniques will find further applications in the development of high-performance detection methods for massive MIMO.
UR - http://www.scopus.com/inward/record.url?scp=85040710533&partnerID=8YFLogxK
U2 - 10.1109/SPAWC.2017.8227768
DO - 10.1109/SPAWC.2017.8227768
M3 - Conference article published in proceeding or book
AN - SCOPUS:85040710533
VL - 2017-July
T3 - IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
SP - 1
EP - 5
BT - 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017
Y2 - 3 July 2017 through 6 July 2017
ER -