Impact of interferences on connectivity in ad hoc networks

Abstract

Abstract-We study the impact of interferences on the connectivity of large-scale ad-hoc networks, using percolation theory. We assume that a bi-directional connection can be set up between two nodes if the signal to noise ratio at the receiver is larger than some threshold. The noise is the sum of the contribution of interferences from all other nodes, weighted by a coefficient γ, and of a background noise.We find that there is a critical value of γ above which the network is made of disconnected clusters of nodes. We also prove that if γ is non zero but small enough, there exist node spatial densities for which the network contains a large (theoretically infinite) cluster of nodes, enabling distant nodes to communicate in multiple hops. Since small values of γ cannot be achieved without efficient CDMA codes, we investigate the use of a very simple TDMA scheme, where nodes can emit only every n-th time slot. We show qualitatively that it even achieves a better connectivity than the previous system with a parameter γ/n.

Analysing wireless sensor network deployment performance using connectivity

“…This model takes the impact of the interference with other nodes of the network and the noise of the environment. The SINR model 4 uses a predefined threshold of SINR θ to decide whether the data is received in the transceiver or not:…”

Interference Power Sum with Log-Normal Components in Ad-Hoc and Sensor Networks

“…This results into an interfering node density of 0.44 (with MAC class 3 and ξ = 0.8). In this figure the dotted vertical lines indicate the distance of the first to the 6th interfering node calculated by (5). The marked curves show the actual distribution of the position of interfering nodes that are found by simulations.…”

“…In our calculations of interference power sums we can use (5) to estimate the expected distance of each interfering node to the center node. In other words, we have assumed that interfering nodes have a uniform distribution around the center node.…”

“…However, (5) predicts an interfering node at distance 0.72 to the center node (the left most dotted vertical line in Figure 8) that never seems to appear in simulations. The explanation is that a node at distance 0.72 would be connected to the center node with high probability 5 . Due to MAC class 3 restrictions this node is then not allowed to transmit a signal while the center node is receiving data from an other node.…”

“…The weighting method is described in the next section. 5 The exact probability is calculated using (2): With ξ = 2.4/3.0 = 0.8 we obtain p( r) = 0.95. …”