Wireless Communication Node Disjoint Transmission Windows
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Solution Overview
Problem
Existing approaches to achieve ultra-reliable and low-latency communication (URLLC) in 5G wireless networks either lead to over-resource consumption or high latency, as they either reserve resources proactively or reactively adapt to transmission conditions, without effectively considering the specific requirements of applications.
Innovation Solution
A method that determines disjoint transmission windows based on communication quality and application performance indicators, classifying them into quality of service classes to adapt latency control to the intended application, reducing computational resources and optimizing packet distribution accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If proactive resource reservation is implemented to ensure quality of service, then reliability is improved, but resource consumption increases
Solution Approach 1:
The patent changes the parameter of resource allocation from static reservation to dynamic adjustment based on actual transmission conditions. Transmission parameters are adapted reactively according to channel state, allowing the system to maintain reliability while consuming resources only when necessary, thus resolving the contradiction between guaranteed quality of service and resource efficiency.
Solution Approach 2:
The system transitions from a static resource reservation approach to a dynamic one where resources are allocated based on real-time transmission conditions. The reactive adaptation of communication mechanisms allows the system to respond to changing channel states, maintaining reliability while avoiding unnecessary resource consumption during good transmission conditions.
2Quantity of substance
If reactive adaptation of transmission parameters is implemented, then resource efficiency is improved, but latency increases
Solution Approach 1:
The patent implements preliminary action by pre-configuring multiple communication mechanisms and having ready-to-use transmission parameter sets. When transmission conditions degrade, the system can quickly switch to pre-prepared alternative mechanisms rather than calculating new parameters from scratch, thus reducing latency while maintaining resource efficiency through selective activation of additional resources only when needed.
Solution Approach 2:
The system uses feedback from transmission condition monitoring to trigger reactive adaptation. When channel quality deteriorates, feedback signals initiate parameter adaptation or mechanism switching, allowing the system to respond efficiently to actual needs rather than continuously adjusting parameters, thereby reducing computational overhead and latency while maintaining resource efficiency.
3Quantity of substance
If communication mechanisms are activated adaptively in case of degraded transmission conditions, then resource efficiency is improved, but computational resources increase
Solution Approach 1:
The patent applies partial action by activating additional communication mechanisms only partially or selectively based on the severity of transmission condition degradation. Instead of continuously monitoring and adjusting all parameters, the system activates supplementary mechanisms only when and where needed, reducing computational overhead while maintaining resource efficiency through targeted rather than comprehensive adaptation.
4Productivity
If optimization is based solely on communication channel state, then network performance is improved, but adaptability to application requirements decreases
Solution Approach 1:
The patent applies local quality by tailoring communication parameters and mechanism selection to specific application requirements rather than using a one-size-fits-all approach. Different applications receive customized transmission optimizations based on their specific latency, reliability, and throughput needs, while still benefiting from overall network performance improvements through channel-state-aware resource allocation.
Data Source
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AI summary
This communication method in a wireless communication network, implemented by a processor of a communication node, comprises, for a plurality of packets to be transmitted to a destination node, for a predetermined application: a reception of information (56, 58) relating to a quality of communication in the network and information relating to an application performance indicator, a determination (62, 64, 66) of a plurality of disjoint transmission windows, and calculation, for each transmission window, of an associated central time instant and an associated window width, a classification (68) of the transmission windows, into quality of service classes, according to a statistical distribution of latency and the application performance indicator, and a distribution (70) of the packets to be transmitted in at least one of the transmission windows,the distribution taking into account at least one constraint associated with said predetermined application.