Small Cell Resource Allocation via Demand-Based Probability
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Solution Overview
Problem
Existing resource allocation methods in small cell networks face challenges with interference between neighboring cells, leading to reduced data throughput and increased control traffic, especially as the network size grows, with centralized approaches being inefficient and distributed methods being too conservative in resource allocation.
Innovation Solution
A distributed resource allocation method where small cells self-allocate resources based on their demand, using a probability algorithm that favors cells with greater resource deficits, allowing them to capture resources from neighboring cells, and iteratively allocate resources to meet their demands, ensuring equitable distribution and dynamic adaptation to changing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a centralized resource management node is used to allocate resources to small cells, then resource allocation equity is improved, but control traffic increases significantly
Solution Approach 1:
Each small cell autonomously determines its resource demand and calculates its own resource allocation based on local information about neighboring cells. The small cell independently performs the allocation algorithm without requiring centralized coordination, thereby reducing control traffic while maintaining equitable resource distribution through demand-based probability calculations
2Quantity of substance
If a distributed resource allocation approach is used where each small cell independently determines its allocation, then control traffic is reduced, but resource allocation becomes too conservative
Solution Approach 1:
The patent introduces a probability-based allocation mechanism where the allocation decision parameter is the ratio of resource demand to current allocation. Small cells with larger resource deficits have higher probability values, making them more likely to capture additional resources. This dynamic parameter adjustment enables aggressive resource capture for cells in need while maintaining conservative behavior for cells with sufficient resources, thereby improving overall resource allocation efficiency
3Productivity
If small cells use the same frequency and time slots to maximize resource utilization, then data throughput increases, but interference between neighboring cells increases
Solution Approach 1:
The patent implements dynamic resource allocation where small cells continuously monitor their resource demand and adjust their allocations iteratively. The allocation is not static but adapts to changing network conditions and interference levels. Small cells can dynamically capture resources from neighboring cells when their demand increases, allowing the system to optimize throughput while managing interference through probabilistic allocation adjustments
Data Source
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AI summary
This invention provides a method of allocating a resource in a network of small cells, and a device for implementing said method, the method comprising the steps of: a first small cell detecting that its resource demand exceeds its resource allocation; the first small cell selecting a new resource that is being used by a second small cell; and the first small cell allocating the new resource to either the first or second small cell, wherein the probability the new resource is allocated to the first small cell is based on the first small cell's resource demand.