TY - GEN

T1 - The behavior of unbounded path-loss models and the effect of singularity on computed network interference

AU - Inaltekin, Hazer

AU - Wicker, Stephen B.

PY - 2007

Y1 - 2007

N2 - In this paper we address the utility of the unbounded path-loss model G1(x) = x-α in wireless networking research problems. It is known that G1(x) is not valid for small values of x due to the singularity at 0. We compare G1 to a more realistic bounded path-loss model, showing that the effect of the singularity on the total network interference power is significant and cannot be disregarded when the nodes are uniformly distributed over the network domain. In particular, we show that the interference probability density function becomes heavy-tailed under the unbounded path-loss model. However, it decays to zero exponentially fast under the bounded pathloss model. We also prove that a phase transition occurs in the interference behavior at a critical value α* α. For α ≤ α*, as the network size grows to infinity, interference converges (either in probability or in distribution) only if we scale it by an appropriate sequence of constants cn with cn → ∞ as n → ∞. On the other hand, it naturally converges in distribution to a real valued random variable without needing any scaling constants for α > α*. All of our results are invariant under any finite node density λ > 0.

AB - In this paper we address the utility of the unbounded path-loss model G1(x) = x-α in wireless networking research problems. It is known that G1(x) is not valid for small values of x due to the singularity at 0. We compare G1 to a more realistic bounded path-loss model, showing that the effect of the singularity on the total network interference power is significant and cannot be disregarded when the nodes are uniformly distributed over the network domain. In particular, we show that the interference probability density function becomes heavy-tailed under the unbounded path-loss model. However, it decays to zero exponentially fast under the bounded pathloss model. We also prove that a phase transition occurs in the interference behavior at a critical value α* α. For α ≤ α*, as the network size grows to infinity, interference converges (either in probability or in distribution) only if we scale it by an appropriate sequence of constants cn with cn → ∞ as n → ∞. On the other hand, it naturally converges in distribution to a real valued random variable without needing any scaling constants for α > α*. All of our results are invariant under any finite node density λ > 0.

UR - http://www.scopus.com/inward/record.url?scp=48049089626&partnerID=8YFLogxK

U2 - 10.1109/SAHCN.2007.4292855

DO - 10.1109/SAHCN.2007.4292855

M3 - Conference proceeding contribution

AN - SCOPUS:48049089626

SP - 431

EP - 440

BT - 2007 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

T2 - 2007 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON

Y2 - 18 June 2007 through 21 June 2007

ER -