Beyond Massive MIMO: The Potential of Positioning With Large Intelligent Surfaces

By Sha Hu, Fredrik Rusek, Ove Edfors. IEEE Transactions on Signal Processing, 2017

318 citations recorded by the source corpus.

We consider the potential for positioning with a system where antenna arrays are deployed as a large intelligent surface (LIS), which is a newly proposed concept beyond massive multi-input multi-output (MIMO). In a first step, we derive Fisher-information matrix (FIM) and Cramér–Rao lower bound (CRLB) in closed form for positioning a terminal located perpendicular to the center of the LIS, whose location we refer to as being on the central perpendicular line (CPL) of the LIS. For a terminal that is not on the CPL, closed-form expressions of the CRLB seem out of reach, and we alternatively find approximations that are shown to be accurate. Under mild conditions, we show that the CRLB for all three Cartesian dimensions (<inline-formula><tex-math notation="LaTeX">$x$</tex-math> </inline-formula>, <inline-formula><tex-math notation="LaTeX">$y$</tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$z$</tex-math></inline-formula>) decreases quadratically in the surface area of the LIS. In a second step, we analyze the CRLB for positioning when there is an unknown phase <inline-formula> <tex-math notation="LaTeX">$\varphi$</tex-math></inline-formula> presented in the analog circuits of the LIS. We then show that the CRLBs are dramatically degraded for all three dimensions and decrease in the third order of the surface area. Moreover, with an infinitely large LIS, the CRLB for the <inline-formula><tex-math notation="LaTeX">$z$ </tex-math></inline-formula>-dimension with an unknown <inline-formula><tex-math notation="LaTeX">$\varphi$</tex-math> </inline-formula> is 6 dB higher than the case without phase uncertainty, and the CRLB for estimating <inline-formula> <tex-math notation="LaTeX">$\varphi$</tex-math></inline-formula> converges to a constant that is independent of the wavelength <inline-formula><tex-math notation="LaTeX">$\lambda$</tex-math></inline-formula>. At last, we extensively discuss the impact of centralized and distributed deployments of LIS, and show that a distributed deployment of LIS can enlarge the coverage and improve the overall positioning performance.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/2dd76649a06d06ae73ec409870a659e426d535bb

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In Electrical and Electronic Engineering

Citations in the corpus

6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities (2020, methodology): “A large number of papers are now appearing on both LISs and IRSs (see [107]–[110], [112]–[114], and references therein).”
A Tutorial on Near-Field XL-MIMO Communications Toward 6G (2023, unknown): “In general, I ≥ 1 is considered to avoid mutual coupling among elements.”
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey (2019, background): “Different from the previous works focusing on capacity performance, reference [108] explores the potential of using an IRS with a large number of scattering elements for terminal positioning.”
The Integrated Sensing and Communication Revolution for 6G: Vision, Techniques, and Applications (2024, unknown): “Depending on the technology adopted and the way it is modeled, an ELAA may be dubbed as holographic MIMO and large intelligent surface (LIS) [232], [233], [234]. these terms are applied when arrays consist of electrically small and densely packed elements.”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead (2020, background): “In [279], the authors envision the use of RISs for positioning purposes.”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead (2020, background): “In [277], the authors envision the use of RISs for positioning purposes.”
Edge Learning for B5G Networks With Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing (2022, unknown): “Researches in this direction are taking place mostly under the name of large intel-ligient surfaces (LIS) [281], holographic MIMO surfaces (HMI-MOS) [282], and holographic RIS [283].”
5G-Advanced Toward 6G: Past, Present, and Future (2023, unknown): “with integrated sensing and communication [63].”
Toward Massive MIMO 2.0: Understanding Spatial Correlation, Interference Suppression, and Pilot Contamination (2019, background): “In addition to providing communication services, the unprecedented spatial resolutions provided by large surfaces can be also used for positioning of objects and sensing [67].”
Reconfigurable Intelligent Surfaces for Localization: Position and Orientation Error Bounds (2020, background): “front of it, both in near-field and far-field [49], [51].”
A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications (2023, methodology): “Some important abbreviations are summarized in Table III.”
Smart radio environments empowered by reconfigurable AI meta-surfaces: an idea whose time has come (2019, result): “The solution analyzed in [13] and [53], in particular, is based, in contrast to other research efforts, on using electromagnetically activematerials, which entail an increase of the power consumption.”
Wireless Communications Through Reconfigurable Intelligent Surfaces (2019, unknown): “As a beyond massive MIMO solution, the large intelligent surface (LIS) concept is proposed in [63]–[65].”
Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication (2018, background): “In [14], [64], it was shown that dividing a given surface area into multiple, smaller, RIS provides more robustness, at the cost of higher feedback and complexity overheads.”
Radio Localization and Mapping With Reconfigurable Intelligent Surfaces: Challenges, Opportunities, and Research Directions (2019, background): “The signals from an RIS can be shaped by the RIS controller to further improve accuracy when the RIS is acting as a transmitter or a reflector [6], [7].”