Using beta distributions for modeling distances in random finite networks
Research output: Contribution to journal › Article
Distance distributions in random networks affect various performance metrics and operating protocols. For scenarios with the uniform node distribution, the statistical models of distances have been derived for common shapes of operating areas such as disks, rectangles, and regular polygons. Fewer results have been reported for scenarios where node distributions are nonuniform. Often, the closed-form statistical models are described by complicated expressions making their further usage challenging. In this work, we study the application of beta distributions as substitutes to statistical models of distances. We show that this approximation results in accurate and analytically tractable estimates for different operating scenarios. The proposed approach provides uniform solutions to design and analysis tasks for different node distributions and shapes of operating areas.
|Number of pages||4|
|Journal||IEEE Communications Letters|
|Publication status||Published - 1 Feb 2016|
|MoE publication type||A1 Journal article-refereed|
- Distance distribution, Finite random networks, Outage probability, Wireless networks