TY - GEN
T1 - Angle-Based Multipath Estimation and Beamforming for FDD Cell-free Massive MIMO
AU - Abdallah, Asmaa
AU - Mansour, Mohammad M.
N1 - Funding Information:
This work has been supported by the CNRS-L/AUB Fellowship Award (University Research Board (URB) Award 103604)
Funding Information:
ACKNOWLEDGMENT This work has been supported by the CNRS-L/AUB Fellowship Award (University Research Board (URB) Award 103604)
Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - In this paper, we study frequency-division duplexing (FDD) based cell-free massive multiple-input multiple-output (MIMO) systems wherein distributed multi-antenna access points (APs) serve many single-antenna users simultaneously. Most previous work on cell-free massive MIMO systems consider time-division duplexing mode, although FDD systems dominate current wireless standards. The key challenges in FDD massive MIMO systems are mainly channel-state information (CSI) acquisition and feedback overhead. To address these challenges, we exploit the so-called angle reciprocity of multipath components in the uplink and downlink, so that the required CSI acquisition overhead scales only with the number of served users. We propose a low complexity multipath component estimation technique and present two linear angle-of-arrival (AoA)-based beamforming schemes. We analyze the performance of these schemes by deriving closed-form expressions of the mean-square-error for multipath component estimation, as well as closed form expression for the downlink spectral efficiency. Simulation results demonstrate that the proposed multipath component estimation technique outperforms conventional subspace-based and gradient-descent based techniques. We show also that the proposed beamforming schemes perform close to the ideal beamforming techniques.
AB - In this paper, we study frequency-division duplexing (FDD) based cell-free massive multiple-input multiple-output (MIMO) systems wherein distributed multi-antenna access points (APs) serve many single-antenna users simultaneously. Most previous work on cell-free massive MIMO systems consider time-division duplexing mode, although FDD systems dominate current wireless standards. The key challenges in FDD massive MIMO systems are mainly channel-state information (CSI) acquisition and feedback overhead. To address these challenges, we exploit the so-called angle reciprocity of multipath components in the uplink and downlink, so that the required CSI acquisition overhead scales only with the number of served users. We propose a low complexity multipath component estimation technique and present two linear angle-of-arrival (AoA)-based beamforming schemes. We analyze the performance of these schemes by deriving closed-form expressions of the mean-square-error for multipath component estimation, as well as closed form expression for the downlink spectral efficiency. Simulation results demonstrate that the proposed multipath component estimation technique outperforms conventional subspace-based and gradient-descent based techniques. We show also that the proposed beamforming schemes perform close to the ideal beamforming techniques.
KW - beamforming
KW - Cell-free massive MIMO communications
KW - FDD mode
KW - multipath estimation
UR - http://www.scopus.com/inward/record.url?scp=85072307508&partnerID=8YFLogxK
U2 - 10.1109/SPAWC.2019.8815420
DO - 10.1109/SPAWC.2019.8815420
M3 - Conference contribution
AN - SCOPUS:85072307508
T3 - IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
BT - 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019
Y2 - 2 July 2019 through 5 July 2019
ER -