Wireless Resource Allocation via Data Metrics and Transmission Formats
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Solution Overview
Problem
Wireless communication systems face challenges in optimizing resource allocation for diverse data flows, where some applications require high throughput but are delay tolerant, while others need low throughput but are highly delay sensitive, necessitating efficient resource management to meet these varied needs without excessive resource consumption.
Innovation Solution
A base station calculates data metrics for each data flow, determines separate transmission metrics for different formats, and selects an optimum format for data transmission, considering constraints like packet capacity and addressing, to optimize resource allocation and ensure efficient data delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resources are allocated to meet high throughput needs of delay tolerant applications, then throughput is improved, but delay sensitivity of other applications deteriorates
Solution Approach 1:
The patent segments data flows into different queues based on application type (delay tolerant vs delay sensitive) and calculates separate bit metrics for each queue. This segmentation allows independent optimization of resource allocation for different application requirements, resolving the contradiction between throughput and delay by treating different data flows differently rather than uniformly
Solution Approach 2:
The patent applies local quality by calculating bit metrics specific to each queue based on local characteristics (arrival time, deadline, average throughput experienced and desired). This allows the system to optimize resource allocation locally for each application type while maintaining overall system efficiency, enabling delay tolerant applications to get high throughput without compromising delay sensitive applications
2Productivity
If multiple transmission formats are evaluated to optimize data metrics, then resource allocation efficiency is improved, but system complexity increases
Solution Approach 1:
The patent performs preliminary action by pre-calculating bit metrics for data in queues before transmission occurs. The metrics are computed based on arrival time, deadline, and throughput characteristics, allowing the system to evaluate multiple transmission formats in advance and select the optimum format efficiently without excessive real-time complexity
Solution Approach 2:
The patent changes parameters by introducing bit metrics as a new parameter for evaluating data flows, which combines multiple factors (arrival time, deadline, throughput) into a single optimization criterion. This parameter transformation simplifies the complex task of comparing multiple transmission formats by reducing the decision space to a single metric optimization problem
Data Source
AI summary
Systems and methods for optimizing the allocation of resources to serve different types of data flows in a wireless communication system are disclosed. An exemplary method involves calculating data metrics for data in a plurality of queues. Each queue corresponds to a different data flow in the wireless communication system. The data metrics are used to determine a separate transmission metric for each of a plurality of possible transmission formats. The transmission metric for a given transmission format is dependent on the data metrics corresponding to allocated data for the given transmission format. A transmission format is selected that has an optimum transmission metric. The allocated data for the selected transmission format is transmitted on the forward link in accordance with the selected transmission format.