Dynamic Packet Field Suppression in Broadband Wireless Systems
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Solution Overview
Problem
Current broadband wireless communication systems, such as those adhering to IEEE 802.16 standards, are limited in their ability to suppress repetitive packet fields, requiring pre-defined values and allowing only single-value suppression, which restricts the efficiency of packet data transmission.
Innovation Solution
A method for packet field suppression in broadband wireless communication systems that determines which fields can be suppressed based on predefined rules, and if not, automatically learns new suppression rules and indices, allowing for dynamic field suppression and transmission to improve communication efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pre-defined suppression rules with single values are used, then system complexity is reduced, but suppression capability and adaptability are limited
Solution Approach 1:
The system transitions from static pre-defined suppression rules to dynamic rule generation and learning mechanisms. The base station and remote station automatically learn packet field patterns and generate suppression rules during operation, allowing the system to adapt to varying traffic types and field structures without manual reconfiguration.
Solution Approach 2:
The communication system performs self-learning and self-configuration of suppression rules. The base station and remote station autonomously identify repetitive packet fields, learn their patterns, and establish suppression rules without external intervention, enabling the system to improve its own efficiency through automatic adaptation.
2Productivity
If automatic learning of suppression rules is implemented, then suppression capability is improved, but processing overhead and system complexity increase
Solution Approach 1:
The system performs preliminary learning of packet field patterns during initial communication phases. By identifying and storing suppression rules in advance based on observed traffic patterns, the system prepares for efficient suppression in subsequent transmissions, reducing processing overhead during normal operation.
Solution Approach 2:
The base station and remote station exchange feedback information about packet field patterns and suppression rule effectiveness. This feedback mechanism allows the system to continuously refine its learning, adjust suppression rules based on actual performance, and optimize communication efficiency while managing processing overhead.
Data Source
AI summary
A method for packet field suppression in broadband wireless communication is provided. Values for packet suppression can be learned and subsequently used for suppression. The learning can involve determining a new packet field suppression rule and a packet field suppression index. Packets can be suppressed based on the learned values.