First Node Path Selection for Power Efficiency in 5G IAB Networks
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Solution Overview
Problem
Current Integrated Access and Backhaul (IAB) architectures in 5G networks face inefficiencies in power usage and resource management, leading to increased latency, waste of radio and processing resources, and energy consumption, particularly in mmWave deployments with small cells and street macro sites.
Innovation Solution
A method is introduced where nodes in a communications network obtain and utilize efficiency measures of power use along multiple paths, enabling the selection of more power-efficient paths for packet routing, using machine-learning models to predict and optimize energy resource utilization, and incorporating PSU and battery efficiency into radio bearer setup decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If traditional IAB architectures are used for backhaul in 5G networks, then network coverage and connectivity are provided, but power usage efficiency is poor and energy consumption is high
Solution Approach 1:
The patent implements dynamic path selection that adapts to changing network conditions and power efficiency metrics. The network node continuously evaluates multiple candidate paths and dynamically switches between them based on real-time power usage indicators, transforming the static routing into a dynamic optimization process that improves energy efficiency while maintaining connectivity
Solution Approach 2:
The patent changes the routing parameter from traditional metrics (latency, bandwidth) to include power usage efficiency as a key selection criterion. By modifying the path selection parameters to incorporate power consumption data from multiple nodes along potential paths, the system identifies and selects routes that minimize overall energy consumption while providing required network services
2Use of energy by moving object
If multiple paths are evaluated for packet routing, then power efficiency can be optimized, but processing resources and latency increase
Solution Approach 1:
The patent performs preliminary evaluation of candidate paths by pre-calculating and storing power efficiency metrics for multiple potential routes before actual packet transmission. This advance preparation allows the network node to quickly select optimal paths without performing complex real-time calculations during packet forwarding, thereby reducing processing overhead and latency while maintaining power optimization capabilities
Solution Approach 2:
The patent uses lightweight indicators and simplified metrics to represent path power efficiency rather than performing exhaustive calculations. By using condensed representations of power consumption data that require minimal processing to evaluate and compare, the system achieves power optimization with reduced computational complexity and lower processing resource requirements
Data Source
AI summary
A computer-implemented method performed by a first node (111). The first node (111) operates in a communications network (100). The first node (111) obtains (501), from another node (112, 113) operating in the communications network (100), a respective indication. The respective indication is of a respective efficiency measure of power use of a plurality of nodes (110) operating in the communications network (100) along at least two paths (151, 152). The first node (111) then selects (502) a path for a first packet in the communications network (100), among the at least two paths (151, 152), based on the obtained respective indication.