Broadcast Beam Weight Subnetting for LTE/5G Coverage and Interference
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Solution Overview
Problem
Existing network optimization methods for 4G LTE/5G NR ultra-dense co-frequency networking are inefficient due to the exponential increase in antenna weight combinations, leading to high computational complexity and time consumption.
Innovation Solution
The method involves dividing cells into subnets based on inter-cell overlapping coverage and inter-cell interference, determining a subnet target broadcast beam weight set for each subnet, and sending these weights to the member cells to optimize broadcast beams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of antenna weight combinations is increased to cover diverse scenarios, then the coverage capability is improved, but the computational complexity and time consumption increase exponentially
Solution Approach 1:
The patent divides the network into multiple subnets based on cell coverage overlap and interference relationships. Each subnet is independently optimized with its own target broadcast beam weight set, reducing the overall computational complexity from exponential to linear or polynomial scale while maintaining comprehensive coverage across all scenarios.
Solution Approach 2:
The patent determines subnet target broadcast beam weight sets based on local characteristics of each subnet, specifically considering cell coverage and inter-cell interference within each subnet. This localized optimization approach allows each subnet to be tuned independently according to its specific conditions, improving adaptability without requiring global optimization of all antenna weight combinations.
2Adaptability or versatility
If the number of antenna weight combinations is increased to cover diverse scenarios, then the coverage capability is improved, but the time consumption increases
Solution Approach 1:
By segmenting the network into subnets and optimizing each independently, the patent reduces the time required for network planning and optimization from exponential to manageable levels, enabling faster deployment and adaptation to diverse scenarios.
Solution Approach 2:
The patent pre-calculates and determines target broadcast beam weight sets for each subnet based on their specific characteristics. These pre-determined weight sets can be directly applied when deploying new scenarios, eliminating the need for time-consuming real-time optimization and enabling rapid adaptation.
3Ease of manufacture
If traditional network planning methods are used, then the network can be deployed, but the optimization efficiency is low and energy-consuming
Solution Approach 1:
The patent improves optimization efficiency by dividing the network into subnets and optimizing each independently based on local coverage and interference characteristics, reducing both computational resources and energy consumption while maintaining deployment feasibility.
Solution Approach 2:
The patent enhances optimization efficiency by determining broadcast beam weight sets tailored to each subnet's specific conditions, allowing for more effective and energy-efficient optimization compared to uniform traditional methods.
Data Source
AI summary
Provided are a weight sending method and apparatus, a storage medium and an electronic device. The weight sending method includes: dividing a plurality of cells to obtain one or more subnets; for any first subnet of the one or more subnets, determining a subnet target broadcast beam weight set of the first subnet from preset weights of a member cell according to at least one of: cell coverage of the member cell included in the first subnet or inter-cell interference of the member cell included in the first subnet; and sending the determined subnet target broadcast beam weight set to the first subnet.