How Phones and Towers Use AI to Improve Wireless Signal Quality
This patent describes how a mobile phone and a base station work together, using machine learning, to accurately measure and predict the quality of the wireless connection, making communication more reliable.
Original patent title: “Method and apparatus for estimating channel in wireless communication system”
This patent describes how a mobile phone and a base station work together, using machine learning, to accurately measure and predict the quality of the wireless connection, making communication more reliable. Granted to LG Electronics in 2025 with 23 claims and 2 forward citations, and it is expected to expire in 2040.
Coverage
What does this patent actually cover?
This patent outlines a method where a mobile phone, called a User Equipment (UE), helps a base station improve its understanding of the wireless signal path, known as the channel. The UE first receives a 'first message' from the base station with instructions for sending a special 'uplink reference signal' (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1). After transmitting this signal, the UE receives another special signal, a 'downlink reference signal,' from the base station. The UE then measures the quality of the downlink signal and sends this 'channel information' back to the base station. Crucially, the 'first message' also includes information about a machine learning model that the base station uses to learn and improve its channel measurements (Claim 1). For example, a phone might tell the network its capability to support this learning, or request to change its learning behavior based on how busy it is or how fast it's moving (ClaimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more → 3, 6).
The gap
What does this patent NOT cover?
- Does not cover channel estimation methods that do not involve a machine learning model for measuring the channel.
- Does not cover scenarios where the mobile phone itself performs the primary machine learning for channel estimation, as the patent specifies 'the learning is performed by the base station' (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1).
- Does not cover systems where the mobile phone does not transmit an uplink reference signal based on configuration from the base station.
- Does not cover systems where the mobile phone does not transmit channel information measured from a downlink reference signal.
- Does not cover situations where the mobile phone does not communicate its learning support capabilities or desired learning modes to the base station.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The noveltynoveltyThe requirement that an invention be different from anything publicly known before its priority date.Read more → lies in the specific, collaborative interaction between the UE and the base station, where the UE actively provides data and state information to help the base station train and use a machine learning model for better channel estimation. This offloads the heavy computational learning task to the base station while leveraging the UE's local context.
The Patent Drawing
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
5G New Radio (NR) networks
Future 6G wireless communication systems
Advanced cellular base stations
Smartphones and IoT devices operating on modern cellular networks
Why it matters
The bigger picture
Accurate channel estimation is vital for efficient and reliable wireless communication, especially in complex environments like urban areas or with fast-moving users. By using machine learning, base stations can adapt more intelligently to changing conditions, leading to fewer dropped calls, faster data speeds, and better overall network performance. This technology is foundational for advanced wireless systems like 5G and future 6G networks, which demand extremely precise signal management.
Filed
July 9, 2020
Granted
December 23, 2025
Market context
Who's building on this
Companies in this space
LG Electronics Inc., the original assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →, continues to be a significant player in telecommunications research and development, particularly in 5G and future wireless technologies. Other major telecommunications equipment providers like Ericsson, Nokia, Huawei, and Qualcomm are also heavily invested in optimizing wireless channel estimation through AI and machine learning techniques, often building on similar foundational concepts to enhance their network infrastructure and chipsets.
Market impact
This patent contributes to the ongoing evolution of wireless communication standards, enabling more intelligent and adaptive networks. The integration of machine learning into channel estimation helps improve network efficiency and user experience, which is critical for the widespread adoption of bandwidth-intensive applications and services. This technology helps differentiate network performance among service providers and is a key enabler for advanced features in 5G and beyond, influencing hardware and software development across the industry.
Claim 1 — Plain English
What this patent covers
This patent outlines a method where a mobile phone, called a User Equipment (UE), helps a base station improve its understanding of the wireless signal path, known as the channel. The UE first receives a 'first message' from the base station with instructions for sending a special 'uplink reference signal' (Claim 1). After transmitting this signal, the UE receives another special signal, a 'downlink reference signal,' from the base station. The UE then measures the quality of the downlink signal and sends this 'channel information' back to the base station. Crucially, the 'first message' also includes information about a machine learning model that the base station uses to learn and improve its channel measurements (Claim 1). For example, a phone might tell the network its capability to support this learning, or request to change its learning behavior based on how busy it is or how fast it's moving (Claims 3, 6).
The clever bit
The novelty lies in the specific, collaborative interaction between the UE and the base station, where the UE actively provides data and state information to help the base station train and use a machine learning model for better channel estimation. This offloads the heavy computational learning task to the base station while leveraging the UE's local context.
What it does not cover
- Does not cover channel estimation methods that do not involve a machine learning model for measuring the channel.
- Does not cover scenarios where the mobile phone itself performs the primary machine learning for channel estimation, as the patent specifies 'the learning is performed by the base station' (Claim 1).
- Does not cover systems where the mobile phone does not transmit an uplink reference signal based on configuration from the base station.
- Does not cover systems where the mobile phone does not transmit channel information measured from a downlink reference signal.
- Does not cover situations where the mobile phone does not communicate its learning support capabilities or desired learning modes to the base station.
Patent timeline
Application submitted to the patent office
Application published, typically 18 months after filing
Patent officially issued
Patent enters public domain
PatentBrief Score
Impact Score
Strong
Citation count
10/40
Early citations
Claim breadth
15/20
Broad claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
20/20
Granted within 5 years
Assignee scale
20/20
Major company or institution
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$75K – $240K
Midpoint $150K · 13.9 yr remaining · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
The original legal language
Original claims
23 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
JUNG, I., Lee, J. K., Kim, I., & Hong, S. R. (2025). How Phones and Towers Use AI to Improve Wireless Signal Quality (U.S. Patent No. 12,506,552). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/12506552/method-and-apparatus-for-estimating-channel-in-wireless-communication-system
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How Phones and Towers Use AI to Improve Wireless Signal Quality cover?
This patent describes how a mobile phone and a base station work together, using machine learning, to accurately measure and predict the quality of the wireless connection, making communication more reliable.
Who owns patent US 12506552?
LG Electronics owns this patent, granted in 2025.
When does this patent expire?
This patent is expected to expire on July 9, 2040, when the invention enters the public domain.
What is patent US 12506552 cited by?
This patent has been cited by 2 later patents that build on its ideas.
What problem does this patent solve?
Accurate channel estimation is vital for efficient and reliable wireless communication, especially in complex environments like urban areas or with fast-moving users. By using machine learning, base stations can adapt more intelligently to changing conditions, leading to fewer dropped calls, faster data speeds, and better overall network performance. This technology is foundational for advanced wireless systems like 5G and future 6G networks, which demand extremely precise signal management.
What does this patent NOT cover?
Does not cover channel estimation methods that do not involve a machine learning model for measuring the channel.
Same assignee
More from LG Electronics
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