Blended Data Transmission Network for MTC Routing
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Solution Overview
Problem
Current machine-to-machine (M2M) communication systems face inefficiencies in data transmission, particularly in handling varying message sizes across different networks, leading to congestion and suboptimal resource utilization.
Innovation Solution
A blended data transmission network is implemented, utilizing intelligent eNodeBs to route messages based on PLMN IDs, separating data into short messaging and data-intensive networks, and employing network resource partitioning and congestion control to efficiently manage MTC communications, supporting both small and large data sizes through LTE and additional networks like WLAN/PAN.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If M2M communications are transmitted over a unified high-speed data transmission network, then network coverage and accessibility are improved, but network congestion and resource utilization efficiency deteriorate
Solution Approach 1:
The patent divides the unified data transmission network into separate short messaging network and data-intensive network based on message size characteristics. This segmentation allows small messages to be transmitted through the short messaging network while large messages use the data-intensive network, preventing network congestion and improving overall resource utilization efficiency.
Solution Approach 2:
The patent applies different network transmission characteristics to different message sizes. Small messages are routed through the short messaging network with appropriate QoS parameters, while large messages are routed through the data-intensive network, optimizing resource allocation and transmission efficiency for each message type.
2Device complexity
If all MTC data is routed through a single network, then routing complexity is reduced, but transmission efficiency and congestion control deteriorate
Solution Approach 1:
The patent performs preliminary classification of MTC data based on message size before routing. The eNodeB determines whether to route data through the short messaging network or data-intensive network based on pre-defined size thresholds, enabling efficient congestion control and optimized transmission paths without adding significant routing complexity.
3Reliability
If network resource partitioning is implemented for MTC, then congestion control is improved, but network management complexity increases
Solution Approach 1:
The patent uses QoS class indicators (QCIs) as a parameter to differentiate and manage MTC data streams. By assigning specific QCI values to short messaging and data-intensive traffic, the network can automatically apply appropriate resource allocation and congestion control policies without requiring complex manual management, thus improving reliability while keeping management complexity acceptable.
Data Source
AI summary
A method includes broadcasting, from an evolved node b (eNodeB), a plurality of Public Land Mobile Networks (PLMN) identifiers (IDs). The plurality of PLMN-IDs include at least one PLMN-ID for a data intensive network and at least one M-PLMN-ID for machine type communications (MTC) in a short messaging network. The method includes receiving a request to transmit MTC data from a MTC device and determining whether the MTC device includes the at least one M-PLMN-ID. The method includes determining whether the MTC data is in a class required to be sent by the data intensive network. The method also includes determining whether the message size is less than the length of structured small data (SSD), and sending the message via the short messaging network in response to a determination that the message size is less than the length of the SSD.