Dynamic UE Grouping for NOMA Network Diversity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Non-orthogonal multiple access (NOMA) systems in dense networks face challenges with channel state information acquisition overhead and implementation complexity, leading to poor network/frequency diversity and increased error probability, especially in stationary systems lacking frequency hopping and CSI updates.
Innovation Solution
A dynamic UE grouping method that adapts transmission parameters like beamforming and power allocation based on message decoding status, allowing for virtual diversity without frequent CSI updates, improving HARQ protocols and error probability in dense NOMA systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If NOMA is used in dense networks with stationary UEs working at fixed frequencies, then sum rate and capacity region are improved, but network/frequency diversity is poor leading to increased error probability
Solution Approach 1:
The patent applies dynamics by making the UE grouping configuration changeable over time. The network node determines different grouping configurations for different time instances, allowing the system to adapt to varying channel conditions and improve reliability without sacrificing the high sum rate benefits of NOMA in dense networks.
Solution Approach 2:
The patent changes the grouping configuration parameter dynamically. By adjusting which UEs are grouped together in different time instances, the system can exploit time-varying channel characteristics to improve diversity and reduce error probability while maintaining high spectral efficiency.
2Reliability
If frequent CSI updates are performed to improve reliability, then error probability decreases, but system complexity and overhead increase
Solution Approach 1:
The patent applies self-service by using the existing channel conditions and decoding outcomes to automatically determine grouping configurations without requiring explicit CSI feedback. The system leverages available information (decoding success/failure) to adaptively adjust groupings, reducing overhead while maintaining reliability.
Solution Approach 2:
The patent uses feedback from decoding outcomes (ACK/NACK) to adjust grouping configurations. Instead of requiring frequent CSI updates, the system uses decoding performance feedback to dynamically reconfigure groups, achieving reliability improvement with minimal additional overhead.
3Reliability
If dynamic UE grouping is implemented, then network diversity is improved, but implementation complexity increases
Solution Approach 1:
The patent segments the network into different UE groups that can be independently configured and managed. By dividing UEs into manageable groups with different configurations, the system achieves diversity benefits while keeping the complexity of managing each group tractable.
Solution Approach 2:
The patent changes the grouping configuration parameter to achieve diversity. By dynamically adjusting which UEs are grouped together, the system exploits temporal variations in channel conditions to improve reliability without requiring complex real-time optimization algorithms.
Data Source
AI summary
A dynamic UE grouping method for dense NOMA systems. One objective is to improve the performance gain by adding virtual diversity into the network. An embodiment allows a network node to consider different groups of UEs for data transmission using NOMA based on the UEs' message decoding status without CSI updates.