Distributed Signal Quantization for IoT Communication Efficiency
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Solution Overview
Problem
Distributed communication systems in IoT networks face inefficiencies due to the need for excessive resources and high construction costs in compressing, transmitting, and restoring signals in central computing centers, which can be mitigated by improving signal quantization techniques.
Innovation Solution
A user-cooperative distributed communication method that involves receiving nodes extracting and quantizing combined signal vectors, transmitting these vectors to other nodes, and performing decoding operations to enhance communication performance without relying on central computing centers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If signals are compressed and transmitted to a central computing center for restoration, then communication restoration can be achieved, but excessive resources and construction costs are required
Solution Approach 1:
The patent divides the distributed communication system into multiple receiving nodes that independently perform signal processing operations. Each node extracts combined signal vectors from received signals and performs local quantization, eliminating the need for a centralized computing center. This segmentation distributes the computational burden across multiple nodes, reducing overall resource requirements while maintaining communication restoration capability.
Solution Approach 2:
Each receiving node in the distributed system performs self-service by independently extracting combined signal vectors, quantizing them, and transmitting the quantized vectors to other nodes. The nodes autonomously perform signal processing operations without requiring centralized control or restoration, thereby reducing the resource burden on any single node and eliminating construction costs for centralized facilities.
2Productivity
If distributed receiving devices are deployed at high density, then spatial multiplexing gain is maximized, but system complexity and resource requirements increase
Solution Approach 1:
The patent extracts only the essential combined signal vectors from received signals at each distributed receiving node, rather than processing and transmitting complete signal data. By extracting and quantizing only the necessary signal components, the system achieves spatial multiplexing gain from high-density deployment while significantly reducing the complexity of signal processing and data transmission requirements.
3Measurement precision
If complete reception signal vectors are transmitted for decoding, then decoding accuracy is maintained, but transmission resource consumption increases
Solution Approach 1:
The patent changes the parameter representation of received signals by extracting combined signal vectors and applying quantization operations. Instead of transmitting complete high-precision reception signal vectors, the system transforms the signal representation into quantized combined signal vectors that consume fewer transmission resources while maintaining sufficient decoding accuracy through the distributed processing architecture.
Data Source
AI summary
An operation method of a first receiving node in a distributed communication system may comprise: receiving a signal from a transmitting node; extracting a combined signal vector from a reception signal vector corresponding to a vector of the received signal; obtaining a compressed combined signal vector by extracting a preset number T of combined signal elements from among a plurality of combined signal elements constituting the combined signal vector; quantizing the compressed combined signal vector to obtain a quantized combined signal vector; and transmitting the quantized combined signal vector to a second receiving node included in the distributed communication system.