Misbehavior Detection in Wi-Fi/LTE Coexistence Over Unlicensed Bands

We address the problem of detecting misbehavior in the coexistence etiquette between LTE and Wi-Fi systems operating in the 5GHz U-NII unlicensed bands. We define selfish misbehavior strategies for the LTE that can yield an unfair share of the spectrum resources. Such strategies are based on manipulating the operational parameters of the LTE-LAA standard, namely the backoff mechanism, the traffic class parameters, the clear channel access (CCA) threshold, and others. Prior methods for detecting misbehavior in homogeneous settings are not applicable in a spectrum sharing scenario because the devices of one system cannot decode the transmissions of another. We develop implicit sensing techniques that can accurately estimate the operational parameters of LTE transmissions under various topological scenarios and
without decoding.
These techniques apply correlation-based signal detection to infer the required information. Our techniques are validated through experiments on a USRP testbed. We further apply a statistical inference framework for determining deviations of the LTE behavior from the coexistence etiquette. By characterizing the detection and false alarm probabilities, we show that our framework yields high detection accuracy at a very low false alarm rate. Although our methods focus on detecting misbehavior of the LTE system, they can be generalized to detect Wi-Fi misbehavior and to other coexistence scenarios.