Region-Specific Codebook Learning for Wireless Beam Management
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Solution Overview
Problem
Conventional beam management techniques in wireless communication systems, such as those using DFT codebooks, fail to effectively leverage reflectors and static blockages, leading to reduced power and throughput and increased energy consumption.
Innovation Solution
The proposed solution involves generating region-specific codebooks based on the state of user equipment (UE), which includes line of sight (LoS), reflection, or blockage, using a digital twin that models the environment observed by the network device. This approach allows for dynamic beam management that adapts to the UE's position and environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional beam management techniques (e.g., DFT codebooks) are used, then the system is simple to implement, but communication energy efficiency and reliability are reduced
Solution Approach 1:
The patent implements dynamic beam management by generating codebooks adapted to real-time environmental conditions. The system determines UE state (LoS, reflection, or blockage) using sensor inputs and digital twin modeling, then selects or generates appropriate codebooks dynamically. This allows the system to transition from static conventional codebooks to adaptive, condition-dependent codebook selection, improving communication reliability through environment-aware beam management.
Solution Approach 2:
The patent uses digital twin modeling to create a virtual copy of the physical environment and UE state. By modeling the environment and UE position/orientation in a digital twin, the system can simulate and predict optimal beam configurations without physically testing all possibilities. This digital copying approach enables complex beam management decisions to be made efficiently, resolving the contradiction between reliability improvement and complexity increase.
2Use of energy by moving object
If conventional beam management techniques are used, then device complexity is low, but energy consumption increases
Solution Approach 1:
The system performs self-service by autonomously determining UE state and selecting appropriate codebooks based on environmental conditions. The digital twin model continuously updates UE position and environment information, allowing the system to self-adjust beam management parameters without external intervention. This autonomous adaptation optimizes energy efficiency by avoiding unnecessary beam switching and selecting optimal beams based on real-time conditions.
Solution Approach 2:
The patent applies preliminary action by pre-processing environmental information and digital twin updates before beam selection is needed. The system continuously maintains updated models of UE position and environment in the digital twin, so when beam management is required, the optimal codebook can be selected immediately without performing complex calculations in real-time. This preliminary modeling reduces computational energy consumption during actual beam management operations.
3Use of energy by moving object
If region-specific codebooks are generated based on digital twin modeling, then communication energy efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent segments the environment into distinct regions based on UE state (LoS region, reflection region, blockage region). Instead of treating the entire environment uniformly, the system divides it into manageable segments and generates or selects codebooks specific to each segment. This segmentation approach reduces computational complexity by focusing calculations only on relevant regions rather than processing the entire environment at once.
Solution Approach 2:
The patent applies local quality by generating codebooks tailored to specific local conditions (LoS, reflection, or blockage) rather than using a single global codebook. Each region receives customized codebook parameters based on its specific characteristics, allowing optimized beam management for each local condition. This localized approach improves energy efficiency while managing computational complexity through targeted processing.
Data Source
AI summary
A processor-implemented method for beam management using region information and region-specific codebook generation includes receiving a stream of inputs from one or more sensors. A region of a user equipment (UE) is determined using a digital twin that models an environment observed by the network device based on the stream of inputs. The region is determined based on a position of the UE in the environment. A beam estimate is generated based on a codebook selected based on the region.