Cellular Subband Power Allocation Using Effective SINR
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Solution Overview
Problem
Existing 5G NR broadband cellular communication systems face inefficiencies in power allocation across subbands due to the requirement of uniform modulation and coding schemes, leading to suboptimal use of power and spectrum resources, and inaccurate representation of channel conditions using average signal-to-interference-plus-noise ratios.
Innovation Solution
The system allocates power to subbands based on an effective signal-to-interference-plus-noise ratio (eSINR) using a mapping function to determine an optimal modulation coding scheme, maximizing eSINR through techniques like water filling and AI/ML-based neural networks to adjust power distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If uniform modulation and coding schemes are used across all subbands, then system complexity is reduced and ease of operation is improved, but power allocation efficiency deteriorates and spectral efficiency is suboptimal
Solution Approach 1:
The system segments the frequency spectrum into multiple subbands and applies different modulation and coding schemes to each subband based on its specific channel conditions. This segmentation allows optimized power allocation per subband while maintaining overall system coordination, resolving the contradiction between operational simplicity and power allocation efficiency.
Solution Approach 2:
The system dynamically adapts modulation and coding schemes across different subbands based on real-time channel conditions and interference levels. This dynamic approach enables the system to optimize power allocation efficiency while maintaining manageable complexity through standardized adaptation algorithms.
2Device complexity
If average signal-to-interference-plus-noise ratio is used to represent channel conditions, then measurement complexity is reduced, but measurement precision deteriorates leading to inaccurate channel representation
Solution Approach 1:
The system divides the frequency spectrum into multiple subbands and calculates separate signal-to-interference-plus-noise ratios for each subband. This segmentation provides precise channel condition representation for each frequency segment while keeping individual measurements computationally simple, resolving the contradiction between measurement complexity and precision.
Solution Approach 2:
The system applies different measurement and representation methods to different subbands based on their local channel characteristics. Each subband's signal-to-interference-plus-noise ratio is calculated independently to capture local channel quality variations, improving overall measurement precision without significantly increasing total complexity.
3Device complexity
If power is allocated uniformly across subbands, then device complexity is reduced, but power utilization efficiency deteriorates
Solution Approach 1:
The system allocates power to each subband based on its specific channel conditions, signal-to-interference-plus-noise ratio, and interference characteristics. This localized power allocation optimizes power utilization efficiency by directing more power to subbands with better channel conditions while reducing power on subbands with poor conditions, maintaining manageable device complexity through systematic allocation rules.
4Productivity
If higher modulation coding scheme indices are used to improve throughput, then data transmission rate is improved, but transmit power requirements increase
Solution Approach 1:
The system applies different modulation coding schemes to different subbands based on their signal-to-interference-plus-noise ratios. High MCS indices are applied to subbands with favorable channel conditions where they can achieve high throughput with moderate power, while subbands with poor conditions use lower MCS indices, optimizing the overall throughput-power tradeoff.
Solution Approach 2:
The system dynamically changes modulation and coding parameters across subbands based on channel conditions. By adjusting MCS indices per subband rather than using a uniform high MCS across all subbands, the system achieves high overall throughput while reducing total transmit power requirements through parameter optimization.
Data Source
AI summary
A system can allocate respective portions of electrical power to respective subbands of a group of subbands that facilitate broadband cellular communications with a user equipment based on an effective signal-to-interference-plus-noise ratio, wherein the effective signal-to-interference-plus-noise ratio is based on respective signal-to-interference-plus-noise ratios of the respective subbands satisfying a criterion. The system can determine a modulation coding scheme based on the effective signal-to-interference-plus-noise ratio. The system can communicate with the user equipment as part of the broadband cellular communications based on the modulation coding scheme.