Low-complexity linear precoding for multi-cell massive MIMO systems
2014 (English)Conference paper (Refereed)
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  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.
Place, publisher, year, edition, pages
2014. 2150-2154 p.
, European Signal Processing Conference, ISSN 2219-5491 ; 6952770
linear precoding, low complexity, Massive MIMO, multi-cell systems, random matrix theory, Cells, Computational complexity, Cytology, Inverse problems, MIMO systems, Random variables, Signal processing, Telecommunication links, Linear pre-coding, Multicell system, Optimal system performance, Polynomial coefficients, Polynomial expansion, Spectral efficiencies, Matrix algebra
IdentifiersURN: urn:nbn:se:kth:diva-167595ScopusID: 2-s2.0-84911884153ISBN: 9780992862619OAI: oai:DiVA.org:kth-167595DiVA: diva2:815106
22nd European Signal Processing Conference, EUSIPCO 2014, 1 September 2014 through 5 September 2014
QC 201505292015-05-292015-05-222015-05-29Bibliographically approved