Network-Controlled Device Location and Routes for Strict QoS
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Solution Overview
Problem
Cellular networks often fail to guarantee required Quality of Service (QoS) due to fluctuating radio conditions, leading to increased latency and packet error rates, which can impact applications like autonomous driving by forcing them to reduce functionality.
Innovation Solution
The network proactively manages device location, route, and sidelink communication policies to maintain QoS by recommending device movement, route changes, and dynamic policy adjustments based on network information and application requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the cellular network increases transmission power to compensate for poor radio signal, then signal quality improves, but energy consumption increases
Solution Approach 1:
The network proactively moves devices to locations with better radio conditions before QoS degradation occurs. By predicting future QoS based on current trajectory and radio conditions, the network can relocate devices in advance to areas with more favorable signal characteristics, avoiding the need for high-power transmission compensation
Solution Approach 2:
The network introduces location management as an intermediary mechanism between the device and radio conditions. Instead of directly increasing transmission power to overcome poor signal, the network mediates by relocating the device to a different geographical location where the radio conditions are inherently better, thus avoiding high energy consumption
2Reliability
If the network physically moves the device to an area with better coverage, then signal quality improves, but device complexity increases
Solution Approach 1:
The device autonomously determines its own relocation by calculating the intersection of its current trajectory with identified sojourn areas. The device independently computes whether moving to a recommended location would improve QoS, and executes the relocation decision without requiring complex network-controlled positioning mechanisms
Solution Approach 2:
The network pre-identifies sojourn areas (locations with better radio conditions) in advance based on predicted device trajectories. When QoS degradation is anticipated, the device is already positioned with knowledge of optimal relocation targets, eliminating the need for complex real-time location control during QoS events
3Reliability
If the network controls device location and route to maintain QoS, then service quality improves, but network complexity increases
Solution Approach 1:
The network applies location control selectively only to devices that require strict QoS guarantees, rather than implementing universal location management for all devices. By identifying specific devices with QoS requirements and their predicted trajectories, the network applies sophisticated control mechanisms only where necessary, keeping the overall system simple
Solution Approach 2:
The network performs preliminary analysis of device trajectories and identifies sojourn areas in advance. This pre-computation allows the network to provide simple location recommendations to devices rather than implementing complex real-time control, reducing network complexity while maintaining QoS guarantees
4Reliability
If the device travels long distances to reach better coverage areas, then signal quality improves, but loss of time increases
Solution Approach 1:
The device moves only partially to the optimal location - specifically to the intersection point of its current trajectory and the sojourn area boundary, rather than traveling the full distance to the center of the sojourn area. This partial movement is sufficient to achieve QoS improvement while minimizing travel time and distance
Solution Approach 2:
The network pre-identifies sojourn areas along the device's predicted trajectory before the device reaches them. By having this information in advance, the device can make immediate relocation decisions when entering these areas without requiring time-consuming searches or complex routing calculations
Data Source
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AI summary
A Network Data Analytic Function (NWDAF) may assist an application server by determining a quality of server (QoS) or delivery timing requirements can be met at a location, e.g., along a route. The NWDAF may collect information from one or more cells near the location, e.g., an Operations and Management (OAM) system. Communications with the NWDAF may be facilitated by a Network Exposure Function (NEF) or an Nnwdaf_AnalyticsInfo_Request service operation. The NWDAF may indicate a potential QoS change at the location. The application server may be a V2X application server.