2008/04/26 by Sunil Srinivasa, Srinivasa, Sunil, Martin Haenggi +1 · 2 citations
Computer Science · Engineering · Mathematics · #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Information Theory (cs.IT) #Millimeter-Wave Propagation and Modeling #Mobile Ad Hoc Networks #Opportunistic and Delay-Tolerant Networks #Stochastic processes and statistical mechanics #cs.IT #math.IT
paper · pdf · doi:10.48550/arxiv.0804.4204
Published in IEEE Transactions on Vehicular Technology
openalex publication_date 2008/04/26 · arxiv created 2012/01/23 · arxiv updated 2012/01/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In wireless networks, the knowledge of nodal distances is essential for several areas such as system configuration, performance analysis and protocol design. In order to evaluate distance distributions in random networks, the underlying nodal arrangement is almost universally taken to be an infinite Poisson point process. While this assumption is valid in some cases, there are also certain impracticalities to this model. For example, practical networks are non-stationary, and the number of nodes in disjoint areas are not independent. This paper considers a more realistic network model where a finite number of nodes are uniformly randomly distributed in a general d-dimensional ball of radius R and characterizes the distribution of Euclidean distances in the system. The key result is that the probability density function of the distance from the center of the network to its nth nearest neighbor follows a generalized beta distribution. This finding is applied to study network characteristics such as energy consumption, interference, outage and connectivity.