Radio Compression Memory Allocation via Traffic Analysis
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Solution Overview
Problem
Existing radio communication systems face challenges in optimally allocating memory resources for compressors and de-compressors in uplink and downlink communications, particularly in the Radio Access Network (RAN) where memory is a limited resource, requiring a trade-off between compression gain and memory allocation.
Innovation Solution
A method involving a traffic analyzing element that measures properties of radio traffic and predicts the fraction of compressible data, providing information to a memory size estimating element to dynamically adjust the memory sizes of compressors and de-compressors, allowing them to optimize memory usage based on real-time data traffic analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If memory size for compressor and de-compressor is increased to achieve higher compression gain, then compression efficiency is improved, but memory resource consumption increases
Solution Approach 1:
The patent implements dynamic memory size adjustment where the memory allocation for compressor and de-compressor is not fixed but adapts based on real-time traffic analysis. The system continuously monitors traffic properties and adjusts memory sizes accordingly, allowing the compression function to have high memory allocation when needed for compression gain while reducing memory usage when traffic patterns don't require it, thus resolving the contradiction between compression efficiency and memory consumption
Solution Approach 2:
The system changes the memory size parameter dynamically based on measured traffic properties. By adjusting this key parameter according to actual compression needs rather than using a static allocation, the system achieves high compression gain when necessary while minimizing memory resource consumption during normal operation, effectively resolving the technical contradiction
2Adaptability or versatility
If memory size is dynamically adjusted based on traffic analysis, then memory utilization is optimized, but system complexity increases
Solution Approach 1:
The patent introduces a traffic analyzing element as an intermediary component that measures traffic properties and provides input to the memory size estimation. This intermediary handles the complex analysis work, allowing the main compression function to remain relatively simple while still achieving adaptive memory allocation. The traffic analyzing element acts as a mediator between the compression function and memory management, reducing the complexity burden on the core compression algorithm
Data Source
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AI summary
The present disclosure relates to a method performed by a traffic analyzing element 23 in a communication network in which a radio device communicates over a packet switched (PS) radio access bearer (RAB) 7 with a radio access network (RAN) using compression in uplink (UL). The method comprises measuring at least one property of radio traffic between the radio device and the RAN. The method also comprises predicting a fraction of UL data on the PS RAB which will be compressible, based on the measuring. The method also comprises outputting information about the predicted fraction to a memory size estimating element 24 in the communication network. The present disclosure also relates to a method performed by a memory size estimating element, as well as to a memory size estimating element and a traffic analyzing element.