Positioning in 5G Networks

Dwivedi, Satyam; Shreevastav, Ritesh; Munier, Florent; Nygren, Johannes; Siomina, Iana; Lyazidi, Yazid; Shrestha, Deep; Lindmark, Gustav; Ernström, Per; Stare, Erik; Razavi, Sara Modarres; Muruganathan, S.D.; Masini, Gino; Busin, Åke; Gunnarsson, Fredrik

doi:10.1109/mcom.011.2100091

Cited by 138 publications

(62 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Position accuracy is a measure of the difference between the estimated and actual user locations. The 3GPP (the entity that develops 5G specifications) has set different position accuracy targets for different scenarios ranging from several meters for emergency calls to a few decimeters for indoor plant operations and vehicle-to-everything (V2X) [ 17 ].…”

Section: Key Performance Indicators For 5g-healthcarementioning

confidence: 99%

Communication Requirements in 5G-Enabled Healthcare Applications: Review and Considerations

et al. 2022

View full text Add to dashboard Cite

Fifth generation (5G) mobile communication technology can enable novel healthcare applications and augment existing ones. However, 5G-enabled healthcare applications demand diverse technical requirements for radio communication. Knowledge of these requirements is important for developers, network providers, and regulatory authorities in the healthcare sector to facilitate safe and effective healthcare. In this paper, we review, identify, describe, and compare the requirements for communication key performance indicators in relevant healthcare use cases, including remote robotic-assisted surgery, connected ambulance, wearable and implantable devices, and service robotics for assisted living, with a focus on quantitative requirements. We also compare 5G-healthcare requirements with the current state of 5G capabilities. Finally, we identify gaps in the existing literature and highlight considerations for this space.

show abstract

Section: Key Performance Indicators For 5g-healthcarementioning

confidence: 99%

Communication Requirements in 5G-Enabled Healthcare Applications: Review and Considerations

et al. 2022

View full text Add to dashboard Cite

show abstract

“…with the projection and retraction operators as defined in (12), and ε k being the step size obtained using a backtracking linesearch [42]. We also use the trust region algorithm [43,Sec.…”

Section: ) Solving the ML Estimation Problemmentioning

confidence: 99%

“…Prior to 5G, the majority of cellular localization schemes relied on multiple synchronized base stations and timedifference-of-arrival (TDoA) measurements [10]. With the introduction of new dedicated positioning reference signals (PRSs) and measurements in 3GPP release 16 [11], a combination of angle and delay measurements has become possible [12]. Because of the high resolution in both temporal and angular domains, thanks to 400MHz bandwidth at mmWave and large antenna arrays, respectively, multipath components can be better resolved [13], leading to new positioning architectures.…”

Section: Introductionmentioning

confidence: 99%

MmWave 6D Radio Localization with a Snapshot Observation from a Single BS

Nazari¹,

Seco‐Granados²,

Johannisson³

et al. 2022

Preprint

View full text Add to dashboard Cite

Accurate and ubiquitous localization is crucial for a variety of applications such as logistics, navigation, intelligent transport, monitoring, and control. Exploiting mmWave signals in 5G and Beyond 5G systems can provide accurate localization with limited infrastructure. We consider the single base station localization problem and extend it to 3D position and 3D orientation estimation of an unsynchronized multi-antenna user, using downlink MIMO-OFDM signals. Through a Fisher information analysis, we show that the problem is often identifiable, provided that there is at least one additional multipath component, even if the position of corresponding incidence point is a priori unknown. Subsequently, we pose a maximum likelihood (ML) estimation problem, to jointly estimate the 3D position and 3D orientation of the user as well as several nuisance parameters (the user clock offset and the positions of incidence points corresponding to the multipath). The ML problem is a highdimensional non-convex optimization problem over a product of Euclidean and Riemannian manifolds. To avoid complex exhaustive search procedures, we propose a geometric initial estimate of all parameters, which reduces the problem to a 1dimensional search over a finite interval. Numerical results show the efficiency of the proposed ad-hoc estimation, whose gap to the Cramér-Rao bound (CRB) is tightened using ML estimation.

show abstract

“…1, localization and mapping are performed on the agent side. Therefore, active and passive sensing can be realized by beam sweeping and downlink positioning reference signals (DL-PRS), respectively, in the communication process [38], [39]. According to 5G NR beam management [15], the agent can sweep the beams for initial access.…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

“…). (38) The state transition function of agent f (u t |u t−1 ) is defined by a linear, near-constant-velocity motion model [49] given as u T t = Au T t−1 + ω t , where…”

Section: B Hybrid Active and Passive Sensing-based Slam Mechanismmentioning

confidence: 99%

Hybrid Active and Passive Sensing for SLAM in Wireless Communication Systems

Yang,

Wen,

Jin

2022

Preprint

View full text Add to dashboard Cite

Integrating sensing functions into future mobile equipment has become an important trend. Realizing different types of sensing and achieving mutual enhancement under the existing communication hardware architecture is a crucial challenge in realizing the deep integration of sensing and communication.In the 5G New Radio context, active sensing can be performed through uplink beam sweeping on the user equipment (UE) side to observe the surrounding environment. In addition, the UE can perform passive sensing through downlink channel estimation to measure the multipath component (MPC) information. This study is the first to develop a hybrid simultaneous localization and mapping (SLAM) mechanism that combines active and passive sensing, in which mutual enhancement between the two sensing modes is realized in communication systems. Specifically, we first establish a common feature associated with the reflective surface to bridge active and passive sensing, thus enabling information fusion. Based on the common feature, we can attain physical anchor initialization through MPC with the assistance of active sensing. Then, we extend the classic probabilistic data association SLAM mechanism to achieve UE localization and continuously refine the physical anchor and target reflections through the subsequent passive sensing. Numerical results show that the proposed hybrid active and passive sensing-based SLAM mechanism can work successfully in tricky scenarios without any prior information on the floor plan, anchors, or agents. Moreover, the proposed algorithm demonstrates significant performance gains compared with active or passive sensing only mechanisms.

show abstract

Positioning in 5G Networks

Cited by 138 publications

References 9 publications

Communication Requirements in 5G-Enabled Healthcare Applications: Review and Considerations

Communication Requirements in 5G-Enabled Healthcare Applications: Review and Considerations

MmWave 6D Radio Localization with a Snapshot Observation from a Single BS

Hybrid Active and Passive Sensing for SLAM in Wireless Communication Systems

Contact Info

Product

Resources

About