BLE Mesh Routing via Neighbor Table Signal Strength
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Solution Overview
Problem
BLE mesh networks face instability and reliability issues due to fluctuating RSSI values and fixed advertisement channels, leading to data losses and increased power consumption, as existing routing methods like hop-count and signal strength-based methods fail to ensure stable communication.
Innovation Solution
A neighbor table is created and maintained to track signal strength and quality of radio links between network nodes, allowing for the selection of reliable associations for route creation and friendship establishment, thereby increasing communication reliability and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If hop-count based routing method is used, then route selection is simple, but communication reliability deteriorates due to fluctuating RSSI values
Solution Approach 1:
The patent changes the routing parameter from simple hop-count to a composite metric that incorporates RSSI (Received Signal Strength Indicator) values. This allows the system to account for signal quality fluctuations while maintaining a relatively simple routing decision process. The modified parameter considers both the number of hops and the cumulative signal strength, providing a more reliable basis for route selection without significantly increasing complexity.
Solution Approach 2:
The patent implements feedback by continuously monitoring RSSI values along potential routes and using this information to adjust route selection. The system collects signal strength measurements from intermediate nodes and uses this feedback to determine the most reliable path, rather than relying solely on static hop-count information. This feedback mechanism enables dynamic adaptation to changing wireless conditions.
2Reliability
If signal strength based routing method is used, then communication reliability is improved, but device complexity increases due to continuous RSSI monitoring
Solution Approach 1:
The patent modifies the routing parameter to combine hop-count and RSSI into a single composite metric. This parameter change allows the system to consider signal strength without requiring completely separate monitoring and evaluation systems. The composite parameter integrates quality of service considerations directly into the route selection criterion, simplifying the overall decision process while improving reliability.
Solution Approach 2:
The patent performs preliminary RSSI measurements and route evaluations before final route selection. By gathering signal strength information in advance and pre-calculating route quality metrics, the system reduces the need for complex real-time monitoring during active communication. This preliminary action allows for more straightforward routing decisions based on pre-assessed route quality.
3Ease of operation
If flooding method is used for message forwarding, then message delivery is simplified, but power consumption increases due to all nodes participating in forwarding
Solution Approach 1:
The patent applies local quality by having different nodes perform different functions based on their characteristics and current state. Instead of all nodes uniformly participating in message forwarding, the system identifies specific relay nodes with favorable signal conditions and assigns them the forwarding task. This localized approach concentrates forwarding responsibilities on nodes that can perform the function most efficiently, reducing overall network power consumption while maintaining delivery reliability.
Solution Approach 2:
The patent performs preliminary evaluation of potential relay nodes based on their signal strength characteristics before assigning message forwarding tasks. By pre-identifying suitable relay nodes through RSSI monitoring and route quality assessment, the system avoids having all nodes continuously monitor and potentially forward messages. This preliminary selection process enables selective forwarding that reduces power consumption while ensuring messages are handled by capable nodes.
Data Source
AI summary
Embodiments herein relate to e.g. a method performed by a network node (10) for handling communication of data in a Bluetooth Low Energy (BLE) mesh network (1). The network node obtains a neighbor table, wherein the neighbor table is based on messages received from different network nodes; and selects an association between network nodes in the BLE mesh network (1) taking the neighbor table into account.