Micro Base Station Placement Optimization for Wireless Network Capacity
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Solution Overview
Problem
Current methods for deploying micro base stations in wireless networks are inefficient and time-consuming, often failing to ensure network capacity expansion due to the labor-intensive process of determining optimal grid placement for maximum network gain.
Innovation Solution
A method that performs grid division on a target region to identify N first grids where deploying one micro base station in each grid maximizes network gain, optimizing network capacity and coverage by calculating network capacity and coverage gains using specific formulas and determining optimal grid positions based on interference thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If grid division is performed to determine optimal micro base station deployment positions, then network capacity expansion is achieved, but deployment time and effort increase significantly
Solution Approach 1:
The patent performs preliminary network modeling and simulation to pre-determine optimal micro base station deployment positions before actual deployment. By using path loss models and coverage area calculations in advance, the system identifies the best grid positions for micro base stations without requiring time-consuming drive tests during the actual deployment phase.
Solution Approach 2:
The patent creates a virtual model of the target region divided into grids, and uses this model to simulate and evaluate different deployment scenarios. Instead of directly deploying physical base stations through trial and error, the system copies the real-world scenario into a computational model where optimal positions can be determined efficiently using algorithms.
2Reliability
If micro base stations are deployed to expand network capacity, then spectrum reuse is improved, but interference between base stations increases
Solution Approach 1:
The patent assigns different parameters and characteristics to different grid positions based on local conditions such as path loss, coverage area, and interference levels. Each grid is evaluated individually using the objective function that incorporates local interference considerations, allowing the system to optimize deployment positions with respect to both capacity and interference mitigation on a location-specific basis.
Solution Approach 2:
The patent uses an objective function that dynamically adjusts evaluation parameters based on interference conditions. By incorporating interference thresholds and weighting factors into the optimization criterion, the system can balance capacity expansion goals with interference control, selecting deployment positions that achieve the desired trade-off.
3Reliability
If drive test method is used to add macro base stations, then network coverage is verified, but the method is not applicable to micro base station deployment due to large quantity
Solution Approach 1:
The patent replaces the mechanical drive test method with a computational approach using path loss models and coverage calculations. Instead of physically testing each macro base station location with drive tests, the system uses electromagnetic propagation models to predict coverage and performance, which can then be applied to determine micro base station positions without requiring physical presence or manual testing.
Solution Approach 2:
The patent enables the network planning system to automatically determine optimal micro base station deployment positions using algorithms that evaluate coverage and interference independently. The system performs self-assessment through network modeling and optimization calculations, eliminating the need for manual drive tests and external verification for each deployment position.
Data Source
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AI summary
The present invention provides a wireless network capacity expansion method and device. The method includes: performing grid division on a target region covered by a macro cellular network, to obtain a plurality of grids; and determining N first grids among the plurality of grids, where deploying one micro base station in each of the first grids brings a maximum network gain corresponding to the target region, and deploying one micro base station in each of the N first grids brings a maximum network capacity of the target region. Based on the network gain, the N first grids are determined among the plurality of grids for deploying micro base stations, which brings the maximum network gain corresponding to the target region, and optimizes the network capacity when a coverage requirement is met.