Energy ratio based WiFi OFDM leakage detection in LTE downlink for in-device interference avoidance

To allow users to access wireless networks and services ubiquitously, more and more user equipments (UEs) are equipped with multiple radio transceivers. However, due to the proximity of transmit and receive frequencies of indevice wireless technologies, the transmitter (TX) of one in-device wireless technology can interfere with the reception of another wireless technology within the same device, and the spurious emissions of the aggressor TX may result in unacceptable interference at the victim receiver which is co-located in the same device. Without central control or cooperation of these transceivers, the receiver (RX) cannot determine the source of the interference. Hence, it has been attracting strong attention to detect in-device interference and adapt strategies to avoid harmful interference. In this paper, we consider the scenario of LTE coexisting with WiFi OFDM signal in the same device. Different from traditional spectrum sensing in cognitive radio, the WiFi leakage detection problem in this paper aims to detect WiFi leakage in the background of LTE signal and Gaussian noise (due to the short distance, AWGN channel will be dominant scenario). Therefore, traditional spectrum sensing algorithms such as energy detection cannot be applied directly. By identifying unique features of the WiFi leakage, we propose a simple yet effective detection algorithm based on energy ratio to successfully detect the WiFi leakage. Specifically, taking advantage of the unbalanced spectrum feature of the WiFi leakage, we utilize the energy ratio between the higher frequency component and the total frequency component as the detection metric. We theoretically analyze the energy ratio, and derive the detection probability and false alarm probability. Simulation results are presented to illustrate the effectiveness and efficiency of the proposed scheme, and validate the theoretical analysis.