ABSTRACT
Several studies have shown that the DCF protocol is very sensitive to the number of competing terminals that access the wireless channel [2-7], and that a way to optimize the network performance is to make the parameters of the backoff window depend on the number of terminals competing for the medium. However, estimating the number of competing terminals is not an easy task. While a terminal could cache the identity of the past senders in the network, the number of competing terminals is the number of terminals that have data to send at any given time, so a simple list of neighbors is not sufficient. The estimation of the number of competing terminals faces two problems. First, the number of competing terminals is a non-Gaussian nonlinear dynamic system that is difficult to track accurately with conventional filters. Advanced estimators such as the extended Kalman filter (EKF)-based one from [3] provide better results, but they are subject to critics due to their complexity [8]. Second, the performance of the IEEE 802.11 DCF is extremely sensitive to the number of competing terminals [2], particularly in the typical operating point of one to fifteen terminals. This makes approximate methods such as [5, 9, 10] to yield suboptimal operation of the protocol compared with the theoretical optimum. Hence, there is a need for an accurate estimation algorithm that is able to efficiently track the number of competing terminals in an IEEE 802.11 network and, at the same time, is easy to implement. As we will see, sequential Monte Carlo methods are appropriate for this purpose.
