Distributed Learning MAC Protocol for Wireless Mesh Networks

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing Medium Access protocols for Wireless LAN, such as IEEE 802.11, do not efficiently support multihop communication in mesh networks, leading to inefficiencies in channel access and network capacity.

Innovation Solution

A new Medium Access Control (MAC) protocol that allows mesh points to estimate the environment and determine whether simultaneous transmissions are possible by calculating Carrier over Interference (CoI) ratios, using a distributed algorithm to negotiate transmission opportunities (TxOPs) and create a world model to predict interference and optimize spatial reuse.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional Medium Access protocols (e.g., IEEE 802.11) are used in mesh networks, then network compatibility and ease of operation are maintained, but channel access efficiency and network capacity deteriorate due to inability to support multihop communication effectively

Engineering Contradiction:

Improvechannel access efficiencyVSAvoidprotocol complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent changes the fundamental parameter of medium access control from traditional contention-based or scheduled approaches to a distributed learning-based approach where nodes continuously adapt their transmission decisions based on observed interference patterns and calculated CoI ratios, enabling efficient multihop communication while maintaining reasonable operational complexity

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

Each mesh point autonomously learns the network environment, calculates interference metrics, and makes transmission decisions without centralized coordination, allowing the system to self-organize and optimize channel access efficiency distributed across multiple hops

Inventive Principle:

Principle #25Self-service

2Productivity

If simultaneous transmissions are allowed on the same communication link, then network capacity and productivity increase through better spatial reuse, but interference management complexity and difficulty of detecting and measuring interference increase

Engineering Contradiction:

Improvenetwork capacityVSAvoidinterference detection difficulty

Core Design Contradiction:

ProductivityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent replaces traditional physical layer interference avoidance mechanisms with a higher-layer distributed learning system that uses statistical analysis and probability calculations (CoI ratios) to manage interference, enabling simultaneous transmissions while maintaining acceptable error rates through intelligent decision-making rather than conservative physical separation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

Each node continuously monitors the wireless medium, calculates Carrier over Interference ratios based on observed signals, and uses this feedback to dynamically adjust transmission decisions, creating a closed-loop system that adapts to changing interference conditions and enables safe simultaneous transmissions

Inventive Principle:

Principle #23Feedback

3Productivity

If mesh points calculate CoI ratios and negotiate transmission opportunities using distributed algorithms, then spatial reuse and channel access efficiency improve, but device complexity and processing requirements increase

Engineering Contradiction:

Improvespatial reuse efficiencyVSAvoidprocessing complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent implements partial action by having nodes calculate CoI ratios only for relevant neighboring transmissions and make transmission decisions based on probabilistic thresholds rather than exhaustive analysis of all possible interference scenarios, reducing processing complexity while maintaining spatial reuse efficiency

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The distributed learning process is segmented into independent modular operations: signal detection, CoI ratio calculation, threshold comparison, and transmission decision-making, allowing each mesh point to implement the complex algorithm through simple localized operations without requiring global coordination

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS8532060B2Distributed learning method for wireless mesh networks

Publication Date: 2013.09.10 KONINKLIJKE PHILIPS NV

AI summary

In a wireless mesh network, an algorithm is used by mesh points in the network to predict the success of and interference created by a new transmission opportunity. In particular, it is provided a method for mesh points, in a mesh network, to determine whether to transmit to another mesh point simultaneously while another transmission is taking place on the same communication link. A mesh point should not transmit to another mesh point if the mesh point's transmission interference disturbs a simultaneous transmission from another mesh point. Furthermore, a transmitting mesh point should not transmit to a receiving mesh point if the transmission will be disturbed at the receiving mesh point from interference from a simultaneous transmission from another mesh point.