Integrated Sensing in Wireless Networks With Local SF Processing
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Solution Overview
Problem
Existing wireless communication networks lack integrated sensing capabilities, relying on bridged technology solutions that interface between sensor technology and wireless networks, leading to increased network overhead and delayed signaling.
Innovation Solution
Locally integrate sensing capabilities within the wireless network, enabling local processing of sensing data by terminals, base stations, and edge computing, rather than solely relying on core network processing, through a new network function (SF) that processes sensing data and communicates with other network elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If sensing capabilities are integrated locally within the wireless network, then network overhead and latency are reduced, but device complexity increases
Solution Approach 1:
The patent segments sensing processing functions across multiple levels: local processing at user equipment/base stations for immediate response, edge computing for regional coordination, and core network for centralized management. This segmentation reduces latency for time-critical sensing tasks while distributing complexity across the network architecture rather than concentrating it in single devices.
Solution Approach 2:
The patent introduces edge computing nodes as intermediary elements between local devices and the core network. These intermediaries handle sensing data processing, reducing the burden on end devices while maintaining low latency through localized processing. The edge nodes act as mediators that manage the complexity burden, absorbing processing tasks and coordinating between local and centralized systems.
2Device complexity
If sensing data processing is centralized in the core network, then device complexity is reduced, but network overhead increases
Solution Approach 1:
The patent implements local quality by enabling user equipment and base stations to perform sensing data processing locally rather than transmitting all raw data to the core network. This local processing capability filters and pre-processes sensing data, reducing the volume of information that must traverse the network. Only processed results or critical data are transmitted upward, significantly reducing network overhead while maintaining simplified device architectures through shared network capabilities.
Data Source
AI summary
Techniques discussed herein can facilitate integrated sensing and communication (ISC), where a wireless network is used for both sensing and for wireless communications. One example aspect is sensing function entity configured to receive a sensing service request from an access and mobility function (AMF) entity, where the sensing service request is received by an access and mobility function/sensing function (AMF/SF) interface. The SF entity is further configured to transmit, by the AMF/SF interface, a sensing service response to the AMF entity and subsequently receive sensing data associated with the sensing service response, where the sensing data is received by a base station/sensing function (BS/SF) interface. The SF entity is further configured to process the sensing data, and transmit the sensing response after processing the sensing data.