Wireless Mesh Network Layout Using LOS and Fiber Access Data
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Solution Overview
Problem
Planning and deploying a mesh-based communication system involving multiple tiers of wireless communication nodes is time-consuming and labor-intensive, with node locations significantly affecting coverage area and requiring careful stage-by-stage planning.
Innovation Solution
A multi-stage algorithm is employed to plan and deploy mesh-based communication systems, starting with first-tier nodes, followed by spine nodes, additional spine nodes, bridge nodes, and finally ptmp equipment, using fiber access and line-of-sight data to determine optimal node locations and connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual planning and deployment of mesh-based communication systems is performed, then flexibility and adaptability are maintained, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system employs automated algorithms that independently perform network planning, node placement optimization, and deployment coordination without requiring manual intervention. The automated planning system processes coverage area data, fiber access information, and line-of-sight constraints to automatically determine optimal node locations and deployment sequences, eliminating the need for manual planning while maintaining strategic flexibility.
Solution Approach 2:
Manual mechanical planning processes are replaced with computational algorithms and software tools. The system uses computer-based optimization algorithms to calculate node placements, determine deployment stages, and coordinate multiple tiers of communication nodes, substituting human manual planning with automated computational mechanisms that are both faster and more consistent.
2Area of stationary object
If multiple tiers of wireless communication nodes are deployed, then network coverage and capacity are improved, but planning and deployment become more complex and time-consuming
Solution Approach 1:
The deployment process is segmented into distinct stages, with each stage focusing on deploying a specific tier of nodes. The system first deploys first-tier nodes at optimal locations, then progressively deploys second-tier, third-tier, and fourth-tier nodes in subsequent stages. This segmentation allows the complex multi-tier deployment to be managed systematically and automatically, reducing overall deployment time while achieving comprehensive coverage.
Solution Approach 2:
The automated planning system performs preliminary actions by pre-calculating optimal node placements, determining deployment sequences, and preparing configuration parameters before actual deployment occurs. The system analyzes coverage requirements, fiber access points, and line-of-sight constraints in advance to establish a predetermined deployment roadmap, eliminating the need for on-site decision-making during deployment.
3Productivity
If automated algorithms are used for node placement, then deployment efficiency is improved, but measurement and detection of optimal locations become more complex
Solution Approach 1:
The system introduces intermediary data layers including fiber access data, line-of-sight data, and coverage area data that mediate between the automated algorithm and the physical deployment requirements. These intermediary datasets translate complex optimization problems into manageable data processing tasks, allowing algorithms to efficiently determine optimal locations by processing pre-collected spatial and connectivity information rather than performing complex real-time measurements.
Data Source
AI summary
A computing platform is configured to: based on fiber access data associated with a coverage area and a first set of line-of-sight (LOS) data associated with the coverage area, identify a plurality of locations for first-tier nodes; and for each respective first-tier node: (i) determine a plurality of geographic areas relative to the respective first-tier node for deploying spine nodes, wherein each determined geographic area is associated with a respective spine extending from the respective first-tier node; (ii) based on a second set of LOS data associated with the coverage area, identify a set of candidate spine node infrastructure sites for spine nodes extending from the respective first-tier node; and (iii) allocate the identified set of candidate spine node infrastructure sites into one or more subsets of infrastructure sites, wherein each subset of infrastructure sites corresponds to a given one of the determined geographic areas.