TY - GEN
T1 - Low-complexity linear precoding for multi-cell massive MIMO systems
AU - Kammoun, Abla
AU - Müller, Axel
AU - Björnson, Emil
AU - Debbah, Mérouane
N1 - Publisher Copyright:
© 2014 EURASIP.
PY - 2014/11/10
Y1 - 2014/11/10
N2 - Massive MIMO (multiple-input multiple-output) has been recognized as an efficient solution to improve the spectral efficiency of future communication systems. However, increasing the number of antennas and users goes hand-in-hand with increasing computational complexity. In particular, the precoding design becomes involved since near-optimal precoding, such as regularized-zero forcing (RZF), requires the inversion of a large matrix. In our previous work [1] we proposed to solve this issue in the single-cell case by approximating the matrix inverse by a truncated polynomial expansion (TPE), where the polynomial coefficients are selected for optimal system performance. In this paper, we generalize this technique to multi-cell scenarios. While the optimization of the RZF precoding has, thus far, not been feasible in multi-cell systems, we show that the proposed TPE precoding can be optimized to maximize the weighted max-min fairness. Using simulations, we compare the proposed TPE precoding with RZF and show that our scheme can achieve higher throughput using a TPE order of only 3.
AB - Massive MIMO (multiple-input multiple-output) has been recognized as an efficient solution to improve the spectral efficiency of future communication systems. However, increasing the number of antennas and users goes hand-in-hand with increasing computational complexity. In particular, the precoding design becomes involved since near-optimal precoding, such as regularized-zero forcing (RZF), requires the inversion of a large matrix. In our previous work [1] we proposed to solve this issue in the single-cell case by approximating the matrix inverse by a truncated polynomial expansion (TPE), where the polynomial coefficients are selected for optimal system performance. In this paper, we generalize this technique to multi-cell scenarios. While the optimization of the RZF precoding has, thus far, not been feasible in multi-cell systems, we show that the proposed TPE precoding can be optimized to maximize the weighted max-min fairness. Using simulations, we compare the proposed TPE precoding with RZF and show that our scheme can achieve higher throughput using a TPE order of only 3.
KW - Massive MIMO
KW - linear precoding
KW - low complexity
KW - multi-cell systems
KW - random matrix theory
UR - http://www.scopus.com/inward/record.url?scp=84911884153&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84911884153
T3 - European Signal Processing Conference
SP - 2150
EP - 2154
BT - 2014 Proceedings of the 22nd European Signal Processing Conference, EUSIPCO 2014
PB - European Signal Processing Conference, EUSIPCO
T2 - 22nd European Signal Processing Conference, EUSIPCO 2014
Y2 - 1 September 2014 through 5 September 2014
ER -