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Massive MIMO at Night: On the Operation of Massive MIMO in Low Traffic Scenarios
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7599-4367
2015 (English)In: 2015 IEEE International Conference on Communications (ICC), IEEE , 2015, p. 1697-1702Conference paper, Published paper (Refereed)
Resource type
Text
Abstract [en]

For both maximum ratio transmission (MRT) and zero forcing (ZF) precoding schemes and given any specific rate requirement the optimal transmit power, number of antennas to be used, number of users to be served and number of pilots spent on channel training are found with the objective to minimize the total consumed power at the base station. The optimization problem is solved by finding closed form expressions of the optimal transmit power and then search over the remaining discrete variables. The analysis consists of two parts, the first part investigates the situation when only power consumed in the RF amplifiers is considered. The second part includes both the power consumed in the RF amplifiers and in other transceiver circuits. In the former case having all antennas active while reducing the transmit power is optimal. Adaptive scheme to switch off some of the antennas at the base stations is found to be optimal in the latter case.

Place, publisher, year, edition, pages
IEEE , 2015. p. 1697-1702
Series
IEEE International Conference on Communications, ISSN 1550-3607, E-ISSN 1938-1883
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:liu:diva-127290DOI: 10.1109/ICC.2015.7248569ISI: 000371708101150ISBN: 9781467364324 (print)ISBN: 9781467364317 (electronic)ISBN: 9781467364300 (print)OAI: oai:DiVA.org:liu-127290DiVA, id: diva2:921541
Conference
IEEE International Conference on Communications (ICC), 8-12 June, London, UK
Available from: 2016-04-20 Created: 2016-04-19 Last updated: 2018-03-14Bibliographically approved
In thesis
1. Aspects of Power Allocation in Massive MIMO
Open this publication in new window or tab >>Aspects of Power Allocation in Massive MIMO
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The past decades have seen a rapid growth of mobile data trac, both in terms of connected devices and data rate. To satisfy the ever growing data trac demand in wireless communication systems, the current cellular systems have to be redesigned to increase both spectral eciency and energy eciency. Massive MIMO (Multiple-Input-Multiple-Output) is one solution that satisfy both requirements. In massive MIMO systems, hundreds of antennas are employed at the base station to provide service to many users at the same time and frequency. This enables the system to serve the users with uniformly good quality of service simultaneously, with low-cost hardware and without using extra bandwidth and energy. To achieve this, proper resource allocation is needed. Among the available resources, transmit power is one of the most important degree of freedom to control the spectral eciency and energy eciency. Due to the use of excessive number of antennas and low-end hardware at the base station, new aspects of power allocation compared to current systems arises. In the rst part of the thesis, a new uplink power allocation schemes that based on long term channel statistics is proposed. Since quality of the channel estimates is crucial in massive MIMO, in addition to data power allocation, joint power allocation that includes the pilot power as additional variable should be considered. Therefore a new framework for power allocation that matches practical systems is developed, as the methods developed in the literature cannot be applied directly to massive MIMO systems. Simulation results conrm the advantages brought by the the proposed new framework. In the second part of the thesis, we investigate the eects of using low-end ampliers at the base stations. The non-linear behavior of power consumption in these ampliers changes the power consumption model at the base station, thereby changes the power allocation. Two dierent scenarios are investigated and both results show that a certain number of antennas can be turned o in low load scenarios.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2016. p. 32
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1767
National Category
Communication Systems Telecommunications Computer Engineering Signal Processing Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-132784 (URN)9789176856185 (ISBN)
Presentation
2016-12-20, Visionen, hus B, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2016-11-24 Created: 2016-11-24 Last updated: 2018-01-13Bibliographically approved
2. Optimizing Massive MIMO: Precoder Design and Power Allocation
Open this publication in new window or tab >>Optimizing Massive MIMO: Precoder Design and Power Allocation
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The past decades have seen a rapid growth of mobile data traffic,both in terms of connected devices and data rate. To satisfy the evergrowing data traffic demand in wireless communication systems, thecurrent cellular systems have to be redesigned to increase both spectralefficiency and energy efficiency. Massive MIMO(Multiple-Input-Multiple-Output) is one solution that satisfy bothrequirements. In massive MIMO systems, hundreds of antennas areemployed at the base station to provide service to many users at thesame time and frequency. This enables the system to serve the userswith uniformly good quality of service simultaneously, with low-costhardware and without using extra bandwidth and energy. To achievethis, proper resource allocation is needed. Among the availableresources, transmit power beamforming are the most important degrees offreedom to control the spectral efficiency and energy efficiency. Dueto the use of excessive number of antennas and low-end hardware at thebase station, new aspects of power allocation and beamforming compared to currentsystems arises.

In the first part of the thesis, new uplink power allocation schemes that based on long term channel statistics isproposed. Since quality of the channel estimates is crucial in massive MIMO, in addition to data power allocation, joint power allocationthat includes the pilot power as additional variable should be considered. Therefore a new framework for power allocation thatmatches practical systems is developed, as the methods developed in the literature cannot be applied directly to massive MIMO systems. Simulation results confirm the advantages brought by the the proposed new framework.

In the second part, we introduces a new approach to solve the joint precoding and power allocation for different objective in downlink scenarios by a combination of random matrix theory and optimization theory. The new approach results in a simplified problem that, though non-convex, obeys a simple separable structure. Simulation results showed that the proposed scheme provides large gains over heuristic solutions when the number of users in the cell is large, which is suitable for applying in massive MIMO systems.

In the third part we investigate the effects of using low-end amplifiers at the basestations. The non-linear behavior of power consumption in these amplifiers changes the power consumption model at the basestation, thereby changes the power allocation and beamforming design. Different scenarios are investigated and resultsshow that a certain number of antennas can be turned off in some scenarios.

In the last part we consider the use of non-orthogonal-multiple-access (NOMA) inside massive MIMO systems in practical scenarios where channel state information (CSI) is acquired through pilot signaling. Achievable rate analysis is carried out for different pilot signaling schemes including both uplink and downlink pilots. Numerical results show that when downlink CSI is available at the users, our proposed NOMA scheme outperforms orthogonal schemes. However with more groups of users present in the cell, it is preferable to use multi-user beamforming in stead of NOMA.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2018. p. 44
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1929
National Category
Communication Systems Signal Processing Telecommunications
Identifiers
urn:nbn:se:liu:diva-145674 (URN)10.3384/diss.diva-145674 (DOI)9789176853276 (ISBN)
Public defence
2018-04-11, Ada Lovelace, Linköping University, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2018-04-11 Created: 2018-03-14 Last updated: 2018-04-11Bibliographically approved

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Cheng, Hei VictorPersson, DanielBjörnson, EmilLarsson, Erik G

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