A Kalman Filter Approach for Distinguishing Channel and Collision Errors in IEEE 802.11 Networks

In the last years, several strategies for maximizing the throughput performance of IEEE 802.11 networks have been proposed in literature. Specifically, it has been shown that optimizations are possible both at the medium access control (MAC) layer, and at the physical (PHY) layer. In fact, at the MAC layer, it is possible to minimize the channel waste due to collisions and backoff expiration times, by tuning the minimum contention window as a function of the network congestion level. At the PHY layer, it is possible to improve the transmission robustness, by selecting a suitable modulation/coding scheme as a function of the channel quality perceived by the stations. However, the feasibility of these optimizations rely on the availability of MAC/PHY measurements, which are often impracticable or very rough. In this paper, we propose a joint MAC/PHY estimator based on a bi-dimensional extended Kalman filter, devised to separately track the collision probability and the channel error probability suffered by each station. To this purpose, we derive a relationship between the unobservable system state and measurements which are performed in a distributed way by all the competing stations.