Spectrum-Aware Cross-Layer Network Resource Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current network modeling techniques use uniform models that are imprecise due to broad approximations at lower levels of abstraction, leading to inefficiencies in resource allocation and potential service interruptions.
Innovation Solution
A cross-layer optimization technique that models networks at a higher layer of abstraction, such as the packet layer, without using broad approximations for elements below, allowing for more precise resource allocation by calculating transport capacity based on spectral efficiency and allocating sublinks accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If uniform models with broad approximations are used for network modeling, then the model complexity is reduced and ease of operation is improved, but the measurement precision and manufacturing precision deteriorate significantly
Solution Approach 1:
The patent segments the network model into multiple layers of abstraction (packet layer, transport layer, physical layer) and applies different modeling approaches to each layer. The packet layer uses simplified uniform models for ease of operation, while the transport and physical layers use detailed spectrum-aware models for precision. This segmentation allows the system to benefit from both simplicity and accuracy in appropriate contexts.
Solution Approach 2:
The patent applies local quality by using different levels of modeling detail in different parts of the network model. Specifically, spectrum-aware detailed modeling is applied where precision is critical (transport capacity calculations, spectral efficiency assessments), while uniform approximations are used in higher-level packet layer modeling where computational simplicity is more important. This localized application of modeling detail resolves the contradiction between ease of operation and measurement precision.
2Measurement precision
If detailed spectrum-aware modeling is applied at lower layers without broad approximations, then the measurement precision and resource allocation accuracy are improved, but the device complexity and computational requirements increase
Solution Approach 1:
The patent introduces a new dimension of abstraction by implementing a multi-layered modeling approach that operates at different levels of detail simultaneously. The packet layer operates at a high-level abstraction for strategic decisions, while the transport and physical layers operate at lower-level abstractions for tactical resource allocation. This dimensional approach allows detailed spectrum-aware modeling to be applied only where necessary, reducing overall system complexity while maintaining precision where critical.
Solution Approach 2:
The patent implements a nested doll structure where the packet layer model contains the transport layer model, which in turn contains the physical layer model. Each layer is nested within the previous layer, with the detailed spectrum-aware modeling nested within the broader packet layer framework. This nesting allows the complex detailed models to be contained within and managed by simpler outer layers, reducing the apparent device complexity while maintaining measurement precision.
3Productivity
If cross-layer optimization with spectrum awareness is implemented, then the productivity and resource utilization are improved, but the difficulty of detecting and measuring and device complexity increase
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing spectral efficiency values and transport capacity parameters for different network conditions and configurations. These pre-computed values are then reused during resource allocation decisions, eliminating the need to perform complex spectral efficiency measurements and calculations in real-time. This preliminary computation reduces the difficulty of detecting and measuring spectral efficiency while maintaining high productivity in resource allocation.
Solution Approach 2:
The patent uses copying by creating simplified representations (models) of complex spectral efficiency relationships. Instead of directly measuring and computing spectral efficiency from first principles during resource allocation, the system uses pre-created model copies that approximate spectral efficiency based on key parameters. These model copies enable fast, accurate resource allocation decisions without the computational burden of real-time spectral efficiency measurement, thus improving productivity while reducing measurement difficulty.
Data Source
AI summary
Allocating network resources to one or more signals that are to be conveyed over the network by calculating a transport capacity for a sublink of the network based on a spectral efficiency of at least one subpath included in the sublink, and allocating the sublink to at least one signal based on the calculated transport capacity.