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Multimedia streaming applications can benefit from bandwidth estimation techniques to perform media scaling and buffer optimization efficiently. However, most current techniques were designed for wired networks and produce relatively inaccurate results and long convergence times on wireless networks where capacity and contention for the capacity can vary dramatically. Therefore, it is difficult to apply current bandwidth estimation tools to multimedia streaming applications in wireless network. This paper presents a newWireless Bandwidth estimation tool (WBest) designed for fast, non-intrusive, accurate estimation of available bandwidth in IEEE 802.11 networks. WBest applies a two-step algorithm: 1) a packet pair technique to estimate the effective capacity of the wireless networks; 2) a packet train technique to estimate the achievable throughput and report the inferred available bandwidth. Using an analytic model, the possible error sources are explored and WBest parameters are optimized given the tradeoffs of accuracy, intrusiveness and convergence time. The advantage of WBest is that it does not depend upon search algorithms to detect the available bandwidth but instead, statistically detects the available fraction of the effective capacity, mitigating estimation delay and the impact of random wireless channel errors. WBest is implemented and evaluated on an 802.11 wireless testbed. Comparing WBest with other popular bandwidth estimation tools shows WBest to have higher accuracy, lower intrusiveness and faster convergence times. Thus, WBest demonstrates the potential for improving the performance of applications that need bandwidth estimation, such as multimedia streaming, on wireless networks.