The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Distance Distributions in Finite Uniformly Random Networks: Theory and Applications
Open accessAbstract
In wireless networks, knowledge of internode distances is essential for performance analysis and protocol design. When determining distance distributions in random networks, the underlying nodal arrangement is almost universally taken to be a stationary Poisson point process. While this may be a good approximation in some cases, there are also certain shortcomings to this model, such as the fact that, in practical networks, the number of nodes in disjoint areas is not independent. This paper considers a more-realistic network model where a known and fixed number of nodes are independently distributed in a given region and characterizes the distribution of the Euclidean internode distances. The key finding is that, when the nodes are uniformly randomly placed inside a ball of arbitrary dimensions, the probability density function (pdf) of the internode distances follows a generalized beta distribution. This result is applied to study wireless network characteristics such as energy consumption, interference, outage, and connectivity.
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Chetlur, V. V., & Dhillon, H. S. (2017) · IEEE Transactions on Communications · doi:10.1109/tcomm.2017.2722500 · Cited by 361
Deep Learning Empowered Task Offloading for Mobile Edge Computing in Urban Informatics
Zhang, K., Zhu, Y., Leng, S., He, Y., Maharjan, S., & Zhang, Y. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2903191 · Cited by 309
Metadata
- Authors
- Srinivasa, S., & Haenggi, M.
- Venue
- IEEE Transactions on Vehicular Technology
- Published
- 2010-02
- Volume
- 59
- Issue
- 2
- Pages
- 940-949
- ISSN
- 0018-9545 (ISSN-L)
- 1939-9359
- OpenAlex
- W2122224951
- Cited by
- 285
- References
- 11
- FWCI
- 13.07
- Type
- journal article
- Language
- en
- Open access
- green
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