Positioning and Sensing in 6G: Gaps, Challenges, and Opportunities

I. INTRODUCTION AND MOTIVATION

• Radio positioning and sensing can use existing wireless infrastructure and spectrum to provide services beyond data transmission.Positioning accuracy needs are increasing from tens of meters to decimeter levels for some future use cases.Source: §I · p. 1
• Sensing-derived environmental digital twins can aid radio resource management, beamforming, mobility management, and minimizing driving tests.Source: §I · p. 1

II. MOBILE RADIO POSITIONING AND SENSING

• The positioning illustration contrasts TDoA hyperbola intersections with angle-based lines, and depicts monostatic and bistatic sensing configurations.Source: Figure 1 · p. 1

I. INTRODUCTION AND MOTIVATION

• The paper draws on a Hexa-X study to analyze 6G use cases, requirements, gaps, radio enablers, and challenges.Source: §I · p. 1

A. Positioning and Sensing Fundamentals

• Radio positioning estimates device location, and sometimes orientation or velocity, from measurements such as signal power, time of flight, and direction.Performance depends on measurement resolution and accuracy, the number of base stations, and their geometry relative to the UE.Source: A. Positioning and Sensing Fundamentals · p. 1
• Radio sensing detects and tracks targets while estimating properties such as range, velocity, size, shape, orientation, or material.The paper distinguishes mono- from bi-/multistatic sensing by transmitter and receiver placement.Source: A. Positioning and Sensing Fundamentals · p. 2

III. USE CASES AND REQUIREMENTS

• The five use-case families span sustainable development, immersive telepresence, local trust zones, massive twinning, and robots to cobots.Their use cases are not fully orthogonal, and Fig. 2 associates the families with positioning and sensing KPIs.Source: §III · p. 2, Figure 2 · p. 2
• Sustainable-development examples include remote healthcare requiring fine location accuracy, while biodiversity monitoring and asset tracking tolerate meter-level accuracy and seconds-level latency.Source: §III · p. 2
• Immersive telepresence ranges from gesture recognition needing fine range and angular accuracy to AR object placement needing centimeter location and tight orientation accuracy.Source: §III · p. 2
• Local trust-zone applications range from stringent telesurgery and microrobot localization to more relaxed patient tracking and cooperative positioning.Source: §III · p. 2
• Massive twinning includes centimeter-scale manufacturing and smart-building positioning, while smart-city traffic monitoring tolerates meter-to-submeter accuracy and relaxed latency.Smart-building twins tolerate longer delays and lower availability; scalability is its most stringent requirement.Source: §III · pp. 2–3
• Robot and cobot applications include centimeter-level robot positioning with low latency and environmental mapping with tight location, velocity, and angular resolution requirements.Source: §III · p. 3

• The analysis establishes achievable state-of-the-art performance as a baseline for comparing existing technologies with 6G use-case requirements.Source: A. Positioning Gap Analysis · p. 3
• 3GPP Rel-16 is the localization baseline, while sensing is assessed using commercially available radar and lidar sensors.Source: A. Positioning Gap Analysis · p. 3
• Table I summarizes sensing-use-case requirements.Source: Table I · p. 3

1) Position Accuracy:

• For 90% of users, the best method achieves around 1 m in IOO at FR1 and 10 cm at FR2, versus 3–4 m in UMi and UMa at FR1.Source: 1) Position Accuracy · p. 3
• Table II reports achievable 5G positioning accuracy in meters across methods and deployment environments, marking coverage-limited cases as N/A.Source: Table II · p. 3
• Most 6G use cases' required positioning accuracy cannot be met by 5G in the corresponding scenarios, and stringent requirements below 0.1 m are unmet in all considered scenarios.Moderate 0.1–1 m accuracy can mainly be supported in IOO-like scenarios.Source: 1) Position Accuracy · p. 3

2) Latency:

• 5G positioning latency is 150−300 ms, leaving at least an order-of-magnitude gap against the roughly 10 ms requirement of the most stringent 6G use cases.Latency varies with signaling delays and the positioning method.Source: 2) Latency · p. 3

3) Scalability:

• Broadcast-signal positioning can serve multiple UEs or TRPs in coverage, but accurate positioning consumes PRS resources and bandwidth otherwise available for communication.6G must enable simultaneous communication and positioning to address this resource conflict.Source: 3) Scalability · p. 4

4) Availability:

• 5G availability is reported as 90%, while many 6G use cases require improvement, with robots and vehicles and especially medical uses demanding stricter availability.The passage groups use cases into less stringent tracking and context-aware services, strict robot and vehicle requirements, and extreme medical requirements.Source: 4) Availability · p. 4

5) Orientation Accuracy:

• AR, collaborative robots, and temporary local coverage benefit from UE orientation estimates, which should become a primary positioning objective beyond legacy regulatory and IIoT use cases.Legacy objectives often omitted heading because it was not critical for emergency-call positioning and small arrays provided limited angular resolution.Source: 5) Orientation Accuracy · p. 4

6) Identified Gaps:

• Required position and orientation accuracy depends on service availability, which is constrained by coverage, network geometry including GDOP, and synchronization between network nodes.The passage also calls for efficient time, frequency, and spatial resource use to scale to more devices, and lower latency for quasi-real-time health care, telesurgery, and collaborative robots.Source: 6) Identified Gaps · p. 4

B. Sensing Gap Analysis

• The sensing gap analysis uses radar and lidar to establish a performance baseline because 5G does not support radio-based sensing.Source: B. Sensing Gap Analysis · p. 4

1) Legacy solutions:

• The selected Arbe radar example provides about 0.5 m location accuracy and range resolution at 300 m, and 0.1 m/s velocity resolution with 33 ms latency.The selected Hesai Pandar64 lidar provides 0.02 m position accuracy at 0.5−200 m with 50 ms latency, subject to at least 10% surface reflectivity.Source: 1) Legacy solutions · p. 4
• Lidar approaches location-accuracy and range-resolution demands for most use cases, except robot-to-cobot object sensing, but supplies no velocity measurements and misses velocity-resolution requirements.Short-range gesture and object sensing reduces lidar accuracy, and close-range laser use may pose a safety risk.Source: 1) Legacy solutions · p. 4
• Radar meets velocity-resolution requirements across the use cases and fulfills the traffic-monitoring requirements, but lacks location accuracy and range resolution for most cases.Radar is less sensitive to surrounding-material reflectivity and has lower possible health risks than lidar.Source: 1) Legacy solutions · p. 4

2) Identified Gaps:

• Only road traffic monitoring has all its listed requirements satisfied by one legacy technique; the analysis uses radar as the baseline for the gap to stringent 6G requirements.The comparison uses two examples, and other radars or lidars may trade one performance metric for another.Source: 2) Identified Gaps · p. 5, Figure 4 · p. 5

High-resolution Sensing with Large Bandwidths and Large Arrays

• Higher carrier frequencies support larger bandwidths for better range resolution, while shorter wavelengths enable massive arrays and higher angular resolution.The resulting resolution supports sensing and mapping without the ambient-light and weather effects associated with visible-light and infrared technologies.Source: A. Radio Enablers · p. 5

Reconfigurable Intelligent Surfaces

• RIS can create controllable non-line-of-sight links under blockage and provide additional geometric measurements when their locations are known.Programmable passive reflecting cells and a controller direct incoming waves, with lower deployment and operational costs than a base station or relay.Source: A. Radio Enablers · p. 5

Joint Hardware and Waveform Design

• Joint waveform and hardware design must balance communication data rate, positioning accuracy, ambiguity-function sidelobes and main-lobe width, and high-frequency hardware robustness.OFDM is widely available and efficiently implemented, while single-carrier waveforms offer hardware efficiency through low PAPR but may have higher sidelobes.Source: A. Radio Enablers · p. 5

Algorithmic Developments

• Model-based algorithms use geometric optics, optimization, and statistical signal processing, while data-driven methods can help under severe hardware impairments or intractable measurement-to-position mappings.The paper identifies approaches combining data and domain knowledge as important for extreme positioning and sensing performance.Source: A. Radio Enablers · p. 5

B. Challenges

• Hardware impairments and harsh channel conditions are the two fundamental radio challenges, alongside architecture and service demands from accurate, low-latency positioning and integrated sensing.The figure frames radio enablers as helping close use-case gaps, while identifying these two challenges to address.Source: B. Challenges · pp. 5–6, Figure 5 · p. 6
• Hardware impairments affect positioning and sensing more severely than communication, degrading ranging through timing errors and angle estimates through antenna imperfections.Some impairments can be calibrated, while phase noise requires dynamic compensation; bandwidth and data-processing demands also face hardware and resource limits.Source: B. Challenges · p. 6
• Radio channels vary substantially by frequency: small-scale fading affects sub-6 GHz, while mmW propagation emphasizes obstruction, reflection, and scattering.At 100 GHz and above, faster channel changes require more frequent updates and spatially consistent channel models; characterization under mobility remains a challenge.Source: B. Challenges · p. 6

VI. OUTLOOK FOR POSITIONING AND SENSING IN 6G

• Positioning gaps remain in accuracy, latency, and availability versus 6G requirements, while sensing gaps concern accuracy and resolution versus state-of-the-art sensors.The paper considers large bandwidths and arrays, RIS, and algorithmic developments as enablers, with channel-model mismatch and hardware impairments as challenges.Source: §VI · p. 6
• Some services will need intermediate information with uncertainty and integrity guarantees, while location services raise access-rights, jamming, falsification, privacy, and secrecy concerns.These are implications of new services built on improved positioning and environmental sensing.Source: §VI · p. 6
• Harnessing the enablers while overcoming the challenges for 6G use cases will be a major research endeavor in the coming years.Source: §VI · p. 6