Joint Temporal Statistics of Interference in Decentralized Wireless Networks

Characterizing interference statistics is central to the design and analysis of both physical layer and medium access control layer techniques to mitigate interference in a wireless network. The applicability of interference statistics, however, is limited by the assumptions adopted to derive the statistics in closed-form. Common assumptions for a decentralized wireless network include temporally independent user locations and an unbounded pathloss function. In this correspondence, we derive the joint temporal statistics of interference that capture the temporal correlation in the network along with the realistic assumption of a bounded pathloss function. The closed-form statistics are asymptotically exact for low tail probabilities, and match closely in simulations even when the tail probability is fairly high. The primary contributions are to i) show that joint interference statistics follow a multivariate Gaussian mixture distribution under the assumption of a bounded pathloss function, and ii) characterize the joint tail probability decay behavior for both bounded and unbounded pathloss functions.