eNode B UE Distribution Mapping via TADV and AOA
Solution Overview
Problem
Existing communication network technologies face challenges in efficiently managing user equipment (UE) distribution and traffic load within cells, leading to degraded service performance due to dynamic user behaviors and environmental conditions, as exact traffic and distribution are unknown during network planning.
Innovation Solution
The enhanced Node B (eNode B) uses two-dimensional bin measurements based on timing advance (TADV) and angle of arrival (AOA) measurements to determine UE distribution, allowing for dynamic adjustment of cell capacity and coverage, and identifying potential locations for small cell deployment to mitigate congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network planning is performed during the planning phase, then cell coverage and bandwidth capabilities can be configured, but the exact traffic amount and UE distribution remain unknown leading to suboptimal resource allocation
Solution Approach 1:
The system performs preliminary network planning with estimated parameters, then later updates the planning data with actual measured UE distribution and traffic load information from the operational network, allowing resource allocation to be optimized based on real conditions rather than just planning phase estimates
Solution Approach 2:
The system implements feedback loops where UE distribution data and traffic load measurements are continuously collected from the network and fed back to the network planning function, enabling dynamic adjustment of resource allocation decisions based on actual network conditions and user behavior patterns
2Device complexity
If cell resources are statically configured during network planning, then network deployment is simplified, but service performance degrades when traffic load increases due to dynamic user behaviors and environmental conditions
Solution Approach 1:
The system transitions from static network planning to dynamic resource allocation by continuously measuring UE distribution and traffic load, then adjusting cell resource configuration in real-time based on actual conditions, allowing the network to adapt to changing user behaviors and environmental factors
Solution Approach 2:
The system changes key network parameters such as cell bandwidth, coverage area, and resource block allocation dynamically based on measured traffic load and UE distribution patterns, enabling resource configuration to match actual demand rather than relying on fixed planning phase decisions
3Reliability
If more cell resources are allocated to handle traffic surges, then service performance is maintained, but network efficiency decreases due to over-provisioning in low-traffic areas
Solution Approach 1:
The system applies different resource allocation strategies to different geographical areas within the network based on local UE distribution and traffic characteristics, allowing high-traffic areas to receive additional resources while low-traffic areas maintain efficient minimal provisioning, optimizing overall network resource efficiency
Data Source
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AI summary
A technology is disclosed that is operable to determine user equipment (UE) distribution information for a communications network. A cell of an enhanced Node B (eNode B) can be mapped into a plurality of UE distribution bins. A UE in the cell of the eNode B can be associated with a UE distribution bin based on a location of the UE in the cell that is determined using a time advance (TADV) value and an angle of arrival (AOA) measurement of an UL transmission from the UE to the eNode B. A UE distribution of one or more UEs in the cell can be calculated based on a number of UEs in each of the plurality of UE distribution bins.