An Improved Upper-Bounded Capacity Algorithm For Wireless Sensor Network

Capacity analysis is a hot topic in wireless sensor network research. This paper proposes an improved algorithm for the upper bound transmission capacity. Firstly, we introduce the signal-to-interference and noise ratio (SINR) interference model based on the traffic rate. The closed-form expression of the upper-bound transmission capacity was derived based on the Weber model for wireless sensor network, where the node distribution follows a Poisson point process. The effects of parameters such as communication range, density, and SINR threshold were evaluated through sensitivity analysis to determine the upper-bounded transmission capacity. The numerical simulation indicates that the upper limit of transmission capacity can be achieved with an optimum node density though dichotomizing searching algorithm. The results of simulation show capacity increases initially and then decreases as the node density increases