Identifying 5G Neighbor Nodes via LTE Signals
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Solution Overview
Problem
In 5G wireless communication networks, establishing neighbor node relations is challenging due to the need for advanced OAM planning tools or additional reference signal transmissions, which can be complex and contradict the ultra-lean design principle.
Innovation Solution
A method that identifies potentially neighboring network nodes by utilizing dual-RAT communication devices to receive and report information from downlink radio signals of existing LTE networks, reducing the need for specific reference signals and complex planning tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If advanced OAM planning tools or additional reference signal transmissions are used to establish neighbor node relations in 5G networks, then the reliability of neighbor node identification is improved, but the device complexity and contradiction with ultra-lean design principle worsen
Solution Approach 1:
The patent uses LTE network downlink signals as an intermediary to indirectly identify 5G neighbor nodes. Instead of requiring direct 5G reference signals or complex OAM tools, the system leverages the existing LTE infrastructure as a mediator to provide neighbor node information, thus reducing complexity while maintaining reliability
Solution Approach 2:
The system enables 5G neighbor node identification to serve itself using existing LTE network resources. Dual-RAT devices automatically report LTE signal information that can be used to infer 5G neighbor relations, allowing the network to self-configure without external OAM intervention
2Measurement precision
If additional reference signal transmissions are implemented for 5G neighbor node identification, then the measurement precision is improved, but the use of energy increases
Solution Approach 1:
The patent makes existing LTE downlink signals serve multiple functions: they continue to provide LTE service while simultaneously enabling 5G neighbor node identification. This multi-functionality eliminates the need for separate 5G reference signals, reducing energy consumption while maintaining measurement precision
Solution Approach 2:
The system changes the parameter of signal usage by repurposing existing LTE signals for 5G network planning purposes. Instead of adding new signals with associated energy costs, the solution modifies how existing signals are utilized, extracting additional value without increasing energy expenditure
3Extent of automation
If dual-RAT communication devices are utilized to report neighbor node information, then the extent of automation is improved, but the quantity of substance (information processing load) increases
Solution Approach 1:
The patent extracts only the necessary neighbor node identification information from dual-RAT device reports, rather than processing all available data. By selectively extracting relevant LTE signal measurements that indicate 5G neighbor relations, the system achieves high automation while minimizing information processing load
Data Source
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AI summary
Identification of network nodes (110a-c) of a first Radio Access Technology, "RAT", and of a wireless communication network (100), which network nodes (110a-c) are at least potentially neighboring each other. Multiple information sets associated with multiple communication devices (120a-c), respectively, are obtained (204a-b; 401). Each communication device (120a-c) supports both the first RAT and another, second RAT. Each information set, thus associated with a communication device (120a), identifies a network node (110a) of the first RAT, and one or more network nodes (111a) of the second RAT that have been identified by the communication device (120a) when the communication device (120a) was associated with a communicative connection to said identified network node (110a) of the first RAT. The network nodes (110a-b) of the first RAT that are at least potentially neighboring each other are then identified (205; 402) based on the obtained multiple information sets.