Systems with Massive Number of Antennas: Distributed Approaches
(2022)- Abstract
- As 5G is entering maturity, the research interest has shifted towards 6G, and specially the new use cases that the future telecommunication infrastructure needs to support. These new use cases encompass much higher requirements, specifically: higher communication data-rates, larger number of users, higher accuracy in localization, possibility to wirelessly charge devices, among others.
The radio access network (RAN) has already gone through an evolution on the path towards 5G. One of the main changes was a large increment of the number of antennas in the base-station. Some of them may even reach 100 elements, in what is commonly referred as Massive MIMO. New proposals for 6G RAN point in the direction of continuing this path of... (More) - As 5G is entering maturity, the research interest has shifted towards 6G, and specially the new use cases that the future telecommunication infrastructure needs to support. These new use cases encompass much higher requirements, specifically: higher communication data-rates, larger number of users, higher accuracy in localization, possibility to wirelessly charge devices, among others.
The radio access network (RAN) has already gone through an evolution on the path towards 5G. One of the main changes was a large increment of the number of antennas in the base-station. Some of them may even reach 100 elements, in what is commonly referred as Massive MIMO. New proposals for 6G RAN point in the direction of continuing this path of increasing the number of antennas, and locate them throughout a certain area of service. Different technologies have been proposed in this direction, such as: cell-free Massive MIMO, distributed MIMO, and large intelligent surface (LIS). In this thesis we focus on LIS, whose conducted theoretical studies promise the fulfillment of the aforementioned requirements.
While the theoretical capabilities of LIS have been conveniently analyzed, little has been done in terms of implementing this type of systems. When the number of antennas grow to hundreds or thousands, there are numerous challenges that need to be solved for a successful implementation. The most critical challenges are the interconnection data-rate and the computational complexity.
In the present thesis we introduce the implementation challenges, and show that centralized processing architectures are no longer adequate for this type of systems. We also present different distributed processing architectures and show the benefits of this type of schemes. This work aims at giving a system-design guideline that helps the system designer to make the right decisions when designing these type of systems. For that, we provide algorithms, performance analysis and comparisons, including first order evaluation of the interconnection data-rate, processing latency, memory and energy consumption. These numbers are based on models and available data in the literature. Exact values depend on the selected technology, and will be accurately determined after building and testing these type of systems.
The thesis concentrates mostly on the topic of communication, with additional exploration of other areas, such as localization. In case of localization, we benefit from the high spatial resolution of a very-large array that provides very rich channel state information (CSI). A CSI-based fingerprinting via neural network technique is selected for this case with promising results. As the communication and localization services are based on the acquisition of CSI, we foresee a common system architecture capable of supporting both cases. Further work in this direction is recommended, with the possibility of including other applications such as sensing.
The obtained results indicate that the implementation of these very-large array systems is feasible, but the challenges are numerous. The proposed solutions provide encouraging results that need to be verified with hardware implementations and real measurements. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3f499912-5707-4b6b-bbec-7eff85f916e0
- author
- Rodríguez Sánchez, Jesús LU
- supervisor
-
- Liang Liu LU
- Ove Edfors LU
- opponent
-
- Prof. Ouitin, Francois, Université libre de Bruxelles, Belgium.
- organization
- publishing date
- 2022
- type
- Thesis
- publication status
- published
- subject
- keywords
- Massive MIMO, Large Intelligent Surface (LIS), distributed processing, algorithm-architecture codesign, equalization, inter-connection data-rate
- pages
- 237 pages
- publisher
- Electrical and Information Technology, Lund University
- defense location
- Lecture Hall E:1406, building E, Ole Römers väg 3, Faculty of Engineering LTH, Lund University, Lund.
- defense date
- 2022-09-02 09:00:00
- ISBN
- 978-91-8039-227-3
- 978-91-8039-228-0
- language
- English
- LU publication?
- yes
- id
- 3f499912-5707-4b6b-bbec-7eff85f916e0
- date added to LUP
- 2022-06-07 15:03:38
- date last changed
- 2023-06-14 08:23:36
@phdthesis{3f499912-5707-4b6b-bbec-7eff85f916e0,
abstract = {{As 5G is entering maturity, the research interest has shifted towards 6G, and specially the new use cases that the future telecommunication infrastructure needs to support. These new use cases encompass much higher requirements, specifically: higher communication data-rates, larger number of users, higher accuracy in localization, possibility to wirelessly charge devices, among others.<br/><br/>The radio access network (RAN) has already gone through an evolution on the path towards 5G. One of the main changes was a large increment of the number of antennas in the base-station. Some of them may even reach 100 elements, in what is commonly referred as Massive MIMO. New proposals for 6G RAN point in the direction of continuing this path of increasing the number of antennas, and locate them throughout a certain area of service. Different technologies have been proposed in this direction, such as: cell-free Massive MIMO, distributed MIMO, and large intelligent surface (LIS). In this thesis we focus on LIS, whose conducted theoretical studies promise the fulfillment of the aforementioned requirements.<br/><br/>While the theoretical capabilities of LIS have been conveniently analyzed, little has been done in terms of implementing this type of systems. When the number of antennas grow to hundreds or thousands, there are numerous challenges that need to be solved for a successful implementation. The most critical challenges are the interconnection data-rate and the computational complexity.<br/><br/>In the present thesis we introduce the implementation challenges, and show that centralized processing architectures are no longer adequate for this type of systems. We also present different distributed processing architectures and show the benefits of this type of schemes. This work aims at giving a system-design guideline that helps the system designer to make the right decisions when designing these type of systems. For that, we provide algorithms, performance analysis and comparisons, including first order evaluation of the interconnection data-rate, processing latency, memory and energy consumption. These numbers are based on models and available data in the literature. Exact values depend on the selected technology, and will be accurately determined after building and testing these type of systems.<br/><br/>The thesis concentrates mostly on the topic of communication, with additional exploration of other areas, such as localization. In case of localization, we benefit from the high spatial resolution of a very-large array that provides very rich channel state information (CSI). A CSI-based fingerprinting via neural network technique is selected for this case with promising results. As the communication and localization services are based on the acquisition of CSI, we foresee a common system architecture capable of supporting both cases. Further work in this direction is recommended, with the possibility of including other applications such as sensing.<br/><br/>The obtained results indicate that the implementation of these very-large array systems is feasible, but the challenges are numerous. The proposed solutions provide encouraging results that need to be verified with hardware implementations and real measurements.}},
author = {{Rodríguez Sánchez, Jesús}},
isbn = {{978-91-8039-227-3}},
keywords = {{Massive MIMO; Large Intelligent Surface (LIS); distributed processing; algorithm-architecture codesign; equalization; inter-connection data-rate}},
language = {{eng}},
publisher = {{Electrical and Information Technology, Lund University}},
school = {{Lund University}},
title = {{Systems with Massive Number of Antennas: Distributed Approaches}},
url = {{https://lup.lub.lu.se/search/files/119623821/thesis_main_document_Jesus.pdf}},
year = {{2022}},
}