Uplink Interference Mitigation via SINR Prediction in 5G UDN
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Solution Overview
Problem
In ultra-dense wireless communication networks, especially in 5G and beyond, the increasing cell density leads to significant inter-cell interference, which limits network performance and makes existing interference mitigation techniques inadequate.
Innovation Solution
The proposed solution involves a method for uplink interference identification and SINR prediction, where channel quality measurement results are used to determine an interference vector for each user equipment (UE). This interference vector is then utilized to predict SINR values for different resource allocation configurations, allowing for the selection of an optimal resource allocation configuration to mitigate interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cell density is increased to satisfy massive demand for services and throughput, then network capacity is improved, but inter-cell interference becomes more prominent
Solution Approach 1:
The patent applies preliminary action by predicting SINR values for different resource allocation configurations before actual resource allocation occurs. The network device determines interference vectors and predicts SINR for multiple candidate configurations, then selects the optimal configuration in advance, thereby proactively mitigating interference before it degrades performance
Solution Approach 2:
The patent changes parameters by determining interference vectors based on channel quality measurement results and using these to predict SINR values for different resource allocation configurations. The system selects configurations that optimize SINR by changing resource allocation parameters (time, frequency, spatial resources) to avoid high-interference scenarios
2Object-affected harmful factors
If existing interference mitigation techniques are used in ultra-dense networks, then some interference reduction is achieved, but network performance is still limited due to the severity of interference
Solution Approach 1:
The patent applies feedback by using channel quality measurement results (which include interference information) to determine interference vectors, then using these vectors to predict SINR for different configurations and select the optimal one. This closed-loop approach continuously adapts resource allocation based on measured interference conditions, improving both interference mitigation and overall network performance
Data Source
AI summary
Embodiments of the present disclosure relate to a method and apparatus for uplink interference identification and SINR prediction. According to an embodiment of the present disclosure, a method can include: receiving first information including at least one channel quality measurement result associated with a first user equipment (UE) depending on interference caused by one or more second UEs; determining an interference vector for the first UE based on the at least one channel quality measurement result. Embodiments of the present disclosure can mitigate interference in ultra-dense network (UDN) for 5G and beyond.