5G RACH Parameter Tuning with Automatic Neighbor Relation Creation
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Solution Overview
Problem
Poorly configured Random Access Channels (RACH) in wireless networks increase access time and failure rates, and manually optimizing RACH parameters is a costly and labor-intensive task for operators, while maintaining neighbor relations among base stations is even more complex, especially with the addition of new generations of cellular networks.
Innovation Solution
Implementing RACH optimization and Automatic Neighbor Relation (ANR) management to automatically configure RACH parameters and neighbor relations, reducing access time and failures by adjusting RACH configuration, preamble split, back-off parameters, and transmission power control in 5G networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual optimization of RACH parameters is performed, then RACH performance can be improved, but the cost and labor intensity increase significantly
Solution Approach 1:
The system enables self-service through automatic neighbor relation creation where the network infrastructure autonomously discovers and configures neighbor relations between base stations without human intervention. The SON server automatically collects measurement reports from UEs, processes the data, and creates neighbor relations, eliminating manual configuration requirements while maintaining optimal RACH performance
Solution Approach 2:
The system implements feedback mechanisms where UEs provide measurement reports containing RACH performance data (access delay, preamble transmission attempts) to the SON server. This feedback loop enables continuous monitoring and automatic adjustment of RACH parameters and neighbor relations, allowing the system to self-optimize based on actual network conditions without manual intervention
2Reliability
If neighbor relations among base stations are manually maintained, then network connectivity is ensured, but the complexity increases especially with new network generations
Solution Approach 1:
The automatic neighbor relation creation system performs self-service by autonomously discovering candidate neighbor relations through UE measurement reports and automatically creating and maintaining neighbor relations in the network. This eliminates the need for manual neighbor relation management while ensuring network connectivity, and the system automatically adapts to new network generations without additional complexity
Solution Approach 2:
The system performs preliminary action by proactively discovering and creating neighbor relations before they are needed for handover operations. The SON server continuously monitors measurement reports and pre-configures neighbor relations based on predicted network conditions, ensuring connectivity is established in advance rather than reactively
3Loss of time
If RACH parameters are automatically configured, then access time is reduced, but the system complexity increases
Solution Approach 1:
The system uses feedback from UE measurement reports containing access delay measurements and preamble transmission data to automatically adjust RACH parameters. The SON server processes this feedback and configures optimal parameters dynamically, reducing access time while the complexity is centralized in the server rather than distributed across numerous devices
Solution Approach 2:
The SON server acts as an intermediary that centralizes the complexity of automatic RACH configuration. Rather than requiring complex configuration logic in multiple network elements, the server consolidates the intelligence needed for automatic parameter adjustment, simplifying the overall system architecture while achieving reduced access times
Data Source
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AI summary
Embodiments disclosed herein relate to Random Access Channel (RACH) optimization and Automatic Neighbor Relation (ANR) use cases and requirements for 5G networks. For example, embodiments disclosed herein automatically configure RACH parameters and neighbor relations for 5G networks that can generate biggest saving in resource utilization for mobile operators. The RACH optimization disclosed herein can automatically configure the RACH parameters in a cell to achieve the optimal RACH performance by reducing the network access and handoff time, and minimize the failures. The Automatic Neighbor Relation (ANR) management disclosed herein can automatically create and update the neighbor relations that can generate biggest saving in resource utilization for mobile operators.