Massive MIMO Optimization with Compatible Sets
Fitzgerald, Emma LU
; Pióro, Michał
and Tufvesson, Fredrik
LU
(2019)
In IEEE Transactions on Wireless Communications
p.2794-2812
- Abstract
- Massive multiple-input multiple-output (MIMO) is expected to be a vital component in future 5G systems. As such, there is a need for new modeling in order to investigate the performance of massive MIMO not only at the physical layer but also higher up the networking stack. In this paper, we present general optimization models for massive MIMO, based on mixed-integer programming and compatible sets, with both maximum ratio combining and zero-forcing precoding schemes. We then apply our models to the case of joint device scheduling and power control for heterogeneous devices and traffic demands, in contrast to the existing power control schemes that consider only homogeneous users and saturated scenarios. Our results show that substantial... (More)
- Massive multiple-input multiple-output (MIMO) is expected to be a vital component in future 5G systems. As such, there is a need for new modeling in order to investigate the performance of massive MIMO not only at the physical layer but also higher up the networking stack. In this paper, we present general optimization models for massive MIMO, based on mixed-integer programming and compatible sets, with both maximum ratio combining and zero-forcing precoding schemes. We then apply our models to the case of joint device scheduling and power control for heterogeneous devices and traffic demands, in contrast to the existing power control schemes that consider only homogeneous users and saturated scenarios. Our results show that substantial benefits, in terms of energy usage, can be achieved without sacrificing throughput and that both the signaling overhead and the complexity of end devices can be reduced by abrogating the need for uplink power control through efficient scheduling. (Less)
- Abstract (Swedish)
- Massive multiple-input multiple-output (MIMO) is expected to be a vital component in future 5G systems. As such, there is a need for new modeling in order to investigate the performance of massive MIMO not only at the physical layer, but also higher up the networking stack. In this paper, we present general optimization models for massive MIMO, based on mixed-integer programming and compatible sets, with both maximum ratio combing and zero forcing precoding schemes. We then apply our models to the case of joint device scheduling and power control for heterogeneous devices and traffic demands, in contrast to existing power control schemes that consider only homogeneous users and saturated scenarios. Our results show substantial benefits in... (More)
- Massive multiple-input multiple-output (MIMO) is expected to be a vital component in future 5G systems. As such, there is a need for new modeling in order to investigate the performance of massive MIMO not only at the physical layer, but also higher up the networking stack. In this paper, we present general optimization models for massive MIMO, based on mixed-integer programming and compatible sets, with both maximum ratio combing and zero forcing precoding schemes. We then apply our models to the case of joint device scheduling and power control for heterogeneous devices and traffic demands, in contrast to existing power control schemes that consider only homogeneous users and saturated scenarios. Our results show substantial benefits in terms of energy usage can be achieved without sacrificing throughput, and that both signalling overhead and the complexity of end devices can be reduced by abrogating the need for uplink power control through efficient scheduling. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/bd4054fc-7a77-45a2-9add-86e8c5b1833f
- author
- Fitzgerald, Emma
LU
; Pióro, Michał
and Tufvesson, Fredrik
LU
- organization
- publishing date
- 2019
- type
- Contribution to journal
- publication status
- published
- subject
- in
- IEEE Transactions on Wireless Communications
- pages
- 2794 - 2812
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85065564542
- ISSN
- 1536-1276
- DOI
- 10.1109/TWC.2019.2908362
- language
- English
- LU publication?
- yes
- id
- bd4054fc-7a77-45a2-9add-86e8c5b1833f
- alternative location
- https://arxiv.org/abs/1903.08260
- date added to LUP
- 2019-03-26 17:36:01
- date last changed
- 2022-05-03 19:02:24
@article{bd4054fc-7a77-45a2-9add-86e8c5b1833f,
abstract = {{Massive multiple-input multiple-output (MIMO) is expected to be a vital component in future 5G systems. As such, there is a need for new modeling in order to investigate the performance of massive MIMO not only at the physical layer but also higher up the networking stack. In this paper, we present general optimization models for massive MIMO, based on mixed-integer programming and compatible sets, with both maximum ratio combining and zero-forcing precoding schemes. We then apply our models to the case of joint device scheduling and power control for heterogeneous devices and traffic demands, in contrast to the existing power control schemes that consider only homogeneous users and saturated scenarios. Our results show that substantial benefits, in terms of energy usage, can be achieved without sacrificing throughput and that both the signaling overhead and the complexity of end devices can be reduced by abrogating the need for uplink power control through efficient scheduling.}},
author = {{Fitzgerald, Emma and Pióro, Michał and Tufvesson, Fredrik}},
issn = {{1536-1276}},
language = {{eng}},
pages = {{2794--2812}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Wireless Communications}},
title = {{Massive MIMO Optimization with Compatible Sets}},
url = {{http://dx.doi.org/10.1109/TWC.2019.2908362}},
doi = {{10.1109/TWC.2019.2908362}},
year = {{2019}},
}