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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 (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)
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)
Please use this url to cite or link to this publication:
author
organization
publishing date
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
2019-06-29 02:20:16
@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},
  year         = {2019},
}