Distributional Substitution for Intersensor Distances in Random Fields

Abstract

The distance between wireless sensors in random fields is crucial for performance analysis and sensor network deployment. However, the exact distribution models are normally of great complexity and can hardly lead to closed-form analytics for most cases. In this letter, we investigate the intersensor distance distribution in random fields, propose a polynomial intersensor distance distributional substitute, and develop two strategies for distributional parameter mapping for different application scenarios. Simulation results presented in this letter verify the effectiveness and efficiency of the low-complexity distributional substitution technique. The verified analyses given in this letter can help to provide mathematically tractable performance metrics for wireless sensor networks where sensors are randomly distributed over the 2-D space.