On the Capacity of Fractal D2D Social Networks With Hierarchical Communications

TL;DR

This paper analyzes the maximum capacity of fractal D2D social networks with direct and hierarchical communications, revealing how capacity scales with network size and fractal structure parameters.

Contribution

It derives the capacity bounds for fractal D2D social networks considering both direct and hierarchical communications, highlighting the impact of fractal structure on capacity.

Findings

Capacity scales as 1/√(n log n) for direct contacts with uniform communication.

Capacity improves to 1/log n when contact probability depends on social distance.

Hierarchical communication capacity is influenced by the fractal correlation exponent , with specific reductions for different  values.

Abstract

The maximum capacity of fractal D2D (device-to-device) social networks with both direct and hierarchical communications is studied in this paper. Specifically, the fractal networks are characterized by the direct social connection and the self-similarity. Firstly, for a fractal D2D social network with direct social communications, it is proved that the maximum capacity is $ \Theta\left(\frac{1}{\sqrt{n\log n}}\right) $ if a user communicates with one of his/her direct contacts randomly, where $ n $ denotes the total number of users in the network, and it can reach up to $ \Theta\left(\frac{1}{\log n}\right) $ if any pair of social contacts with distance $ d $ communicate according to the probability in proportion to $ d^{-\beta} $. Secondly, since users might get in touch with others without direct social connections through the inter-connected multiple users, the fractal D2D social network with these hierarchical communications is studied as well, and the related capacity is further derived. Our results show that this capacity is mainly affected by the correlation exponent $\epsilon$ of the fractal structure. The capacity is reduced in proportional to $ \frac{1}{{\log n}} $ if $ 2<\epsilon<3 $, while the reduction coefficient is $ \frac{1}{n} $ if $ \epsilon=3 $.