QoS Mapping in Fixed Wireless Routers for LTE to DSCP Translation
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Solution Overview
Problem
Previous generations of fixed wireless services for bundled media services faced challenges such as high equipment costs, proprietary technology, and low data rates, and struggled with managing quality of service (QoS) in customer premises networks, limiting their adoption.
Innovation Solution
A system is configured with a broadband home router (BHR) that interfaces with an LTE network based on a subscriber profile, using QoS mapping to relate LTE QoS classes to DSCP QoS classes, and a WiFi access point that maps DSCP QoS classes to WiFi QoS classes, prioritizing traffic based on packet types to ensure efficient data delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If QoS mapping is implemented to prioritize real-time traffic, then quality of service is improved, but device complexity increases
Solution Approach 1:
The QoS mapping functionality is segmented into separate mapping tables stored in lookup memory, with each table handling specific QoS parameter mappings. This divides the complex QoS management into manageable discrete units that can be processed independently through table lookups rather than complex real-time calculations.
Solution Approach 2:
Lookup tables serve as intermediary structures between the QoS manager and traffic flow classification. Instead of directly computing QoS parameters from traffic characteristics, the system uses pre-computed mapping tables as intermediaries to translate traffic flow identifiers into QoS parameters, simplifying the real-time decision-making process.
2Reliability
If multiple QoS mapping tables are used to manage different traffic types, then quality of service management is improved, but memory requirements increase
Solution Approach 1:
The lookup tables are designed to be universal and reusable across different QoS mapping scenarios. The same table structure and memory mechanisms serve multiple QoS parameters and different traffic types, eliminating the need for separate dedicated memory structures for each QoS mapping requirement.
Solution Approach 2:
The system changes QoS parameters by selecting different pre-computed mapping tables based on traffic flow characteristics, rather than dynamically computing each parameter. This allows the same physical memory structure to serve multiple QoS configurations by simply changing which table is active, rather than maintaining multiple simultaneous memory structures.
Data Source
AI summary
A method, performed by a fixed wireless router device, may include receiving a packet from a Long Term Evolution network, where the packet is associated with a particular Long Term Evolution Quality of Service class and mapping the particular Long Term Evolution Quality of Service class to a particular Differentiated Services Core Point Quality of Service class. The method may further include assigning a Differentiated Services Core Point Quality of Service class to the packet based on the particular Differentiated Services Core Point Quality of Service class and forwarding the packet to particular device associated with a customer premises network serviced by the fixed wireless router device, based on a priority associated with the assigned Differentiated Services Core Point Quality of Service class.