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

TL;DR

This paper presents a novel method for detecting misbehavior in LTE systems coexisting with Wi-Fi in unlicensed bands, using implicit sensing techniques that do not require decoding transmissions, validated through experiments.

Contribution

It introduces implicit sensing techniques for detecting LTE misbehavior in coexistence scenarios without decoding, and develops a statistical inference framework for accurate detection.

Findings

High detection accuracy achieved with low false alarm rate.

Effective implicit sensing methods validated on USRP testbed.

Framework applicable to various spectrum sharing scenarios.

Abstract

We consider the problem of fair coexistence between LTE and Wi-Fi systems in the unlicensed 5 GHz U-NII bands. We focus on the misbehavior opportunities due to the heterogeneity in channel access mechanism and the lack of a common control plane. We define selfish misbehavior strategies for the LTE that 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 {\em 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 other coexistence scenarios.