Adaptive Beacon Transmission in Cognitive-OFDM-Based Industrial Wireless Networks

Abstract

Wireless interferences from heterogeneous networks in the crowded industrial scientific medical band set up technical barriers for reliable communication of industrial wireless network (IWN). In this letter, an adaptive beacon transmission strategy is proposed for dynamically scheduling the cognitive-OFDM IWN to avoid channel interferences without using a dedicated control channel. Preambles of beacons are specifically designed in the PHY layer to embed specific information. A generalized likelihood ratio test (GLRT)-based approach is applied to detect the beacon transmission and a maximum likelihood estimator is employed to estimate the beacon information embedded in the preamble. The performance of the GLRT approach to detect the adaptive beacon transmission is evaluated through simulations and practical experiments. The detection and decoding accuracies of the proposed adaptive beacon transmission are close to 100% with reasonable signal-to-noise ratio even under interference.