Abstract
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.
Original language | English (US) |
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Title of host publication | 2014 Proceedings of the 22nd European Signal Processing Conference, EUSIPCO 2014 |
Publisher | European Signal Processing Conference, EUSIPCO |
Pages | 2150-2154 |
Number of pages | 5 |
ISBN (Electronic) | 9780992862619 |
State | Published - Nov 10 2014 |
Event | 22nd European Signal Processing Conference, EUSIPCO 2014 - Lisbon, Portugal Duration: Sep 1 2014 → Sep 5 2014 |
Publication series
Name | European Signal Processing Conference |
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ISSN (Print) | 2219-5491 |
Other
Other | 22nd European Signal Processing Conference, EUSIPCO 2014 |
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Country/Territory | Portugal |
City | Lisbon |
Period | 09/1/14 → 09/5/14 |
Bibliographical note
Publisher Copyright:© 2014 EURASIP.
Keywords
- Massive MIMO
- linear precoding
- low complexity
- multi-cell systems
- random matrix theory
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering