The characterization of topological uncertainty in wireless networks using the formalism of graph entropy has received interest in the spatial networks community. In this paper, we develop lower bounds on the entropy of a wireless network by conditioning on potential network observables. Two approaches are considered: 1) conditioning on subgraphs, and 2) conditioning on node positions. The first approach is shown to yield a relatively tight bound on the network entropy. The second yields a loose bound, in general, but it provides insight into the dependence between node positions (modelled using a homogenous binomial point process in this work) and the network topology
Abstract—In this paper, we study the performance of oppor-tunistic scheduling in wireless networks f...
In this paper we derive entropy bounds for hierarchical networks. More precisely, starting from a re...
Abstract. Complex networks are characterized by highly heterogeneous distributions of links, often p...
The characterization of topological uncertainty in wireless networks using the formalism of graph en...
This work provides an analysis of topological uncertainty in wireless networks. Here, we model a wir...
We analyze topological entropy in wireless networks that are subject to local scattering and macrosc...
Abstract—What are the fundamental limits on the communica-tions potential of wireless networks? We c...
We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically...
What are the fundamental limits on the communications potential of wireless networks? We contend tha...
In this paper, we present a detailed framework to analyze the evolution of the random topology of a ...
The degree-based network entropy which is inspired by Shannon’s entropy concept becomes the informat...
Abstract. Generalised degrees provide a natural bridge between local and global topological properti...
Many graph invariants have been used for the construction of entropy-based measures to characterize ...
We introduce the (private) entropy of a directed graph (in a new network coding sense) as well as a ...
Barabási–Albert’s “Scale Free” model is the starting point for much of the accepted theory of the ev...
Abstract—In this paper, we study the performance of oppor-tunistic scheduling in wireless networks f...
In this paper we derive entropy bounds for hierarchical networks. More precisely, starting from a re...
Abstract. Complex networks are characterized by highly heterogeneous distributions of links, often p...
The characterization of topological uncertainty in wireless networks using the formalism of graph en...
This work provides an analysis of topological uncertainty in wireless networks. Here, we model a wir...
We analyze topological entropy in wireless networks that are subject to local scattering and macrosc...
Abstract—What are the fundamental limits on the communica-tions potential of wireless networks? We c...
We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically...
What are the fundamental limits on the communications potential of wireless networks? We contend tha...
In this paper, we present a detailed framework to analyze the evolution of the random topology of a ...
The degree-based network entropy which is inspired by Shannon’s entropy concept becomes the informat...
Abstract. Generalised degrees provide a natural bridge between local and global topological properti...
Many graph invariants have been used for the construction of entropy-based measures to characterize ...
We introduce the (private) entropy of a directed graph (in a new network coding sense) as well as a ...
Barabási–Albert’s “Scale Free” model is the starting point for much of the accepted theory of the ev...
Abstract—In this paper, we study the performance of oppor-tunistic scheduling in wireless networks f...
In this paper we derive entropy bounds for hierarchical networks. More precisely, starting from a re...
Abstract. Complex networks are characterized by highly heterogeneous distributions of links, often p...