The Impact of Interference Cognition on the Reliability and Capacity of Industrial Wireless Communications
Yichen Guo, Tao Peng, Yujie Zhao, Yijing Niu, Wenbo Wang

TL;DR
This paper examines how the accuracy of interference cognition affects the reliability and capacity of industrial wireless networks, highlighting the importance of precise interference information for optimal system performance.
Contribution
It introduces a novel analytical framework to quantify the impact of interference information precision on achievable rate in industrial wireless networks.
Findings
Higher interference information precision improves achievable rate.
Instantaneous interference information benefits signal links more.
Precise interference knowledge is critical for optimal network performance.
Abstract
Interference significantly impacts the performance of industrial wireless networks, particularly n severe interference environments with dense networks reusing spectrum resources intensively. Although delicate interference information is often unavailable in conventional networks, emerging interference cognition techniques can compensate this critical problem with possibly different precision. This paper investigates the relationship between precision of interference cognition and system performance. We propose a novel performance analysis framework that quantifies the impact of varying interference information precision on achievable rate. Specifically, leveraging the Nakagami- fading channel model, we analytically and asymptotically analyze the average achievable rate in the finite blocklength regime for different precision levels of signal and interference information.…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Cognitive Radio Networks and Spectrum Sensing · Wireless Communication Security Techniques
