engleski

Cancellation of 802.11 WLAN Interference in Bluetooth Networks

The investigation of using neural networks in interference rejection in Bluetooth networks caused by nearby operating 802.11 WLAN devices was main goal of our work. Since both Bluetooth and IEEE 802.11 WLAN devices use the same frequency band and there is great possibility to be close together, interference may cause significant performance degradation. This interference impact on the performance may be critical in multimedia applications. An adaptive filter, based on neural network with Least Mean Squares (LMS) learning rule, is designed. The filter parameters are optimized through extensive simulations to mitigate the effect of IEEE 802.11 interferer. The BER curves, as the measure of quality of service, are presented to describe possibility of Bluetooth and IEEE 802.11b coexistence.

Bluetooth; IEEE 802.1b WLAN; interference; coexistence; neural network; adaptive filter; LMS learning rule; BER.

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