TECHNICAL FIELD

Embodiments of the present disclosure relate, generally, to systems and methods for identifying wireless signals and protocols, and more particularly, systems and methods for protocol reverse engineering of wireless signals.

BACKGROUND

Wireless communications technology is becoming ubiquitous throughout society. Although Wi-Fi has grown to be the ubiquitous Internet access technology, many other wireless protocols are used, for example, wireless communication systems such as BLUETOOTH®, Wi-Fi, cellular, Apple iBEACON®, Z-WAVE®, and ZIGBEE®. Wireless communications devices are widely used in residential homes, in public safety, emergency response, and critical infrastructure applications.

Widespread use of wireless technology raises security concerns. Unauthorized third parties may attempt to access or intrude into wireless devices and wireless networks illegally. If third-parties do access wireless devices or wireless networks, the security of computers and data is at risk.

Shared spectrum is a model for efficient usage of the wireless spectrum given an ever expanding telecommunication industry and an expanding wireless revolution fueled by emerging infrastructures like IoT (internet of things), autonomous cars, and smart medical devices. For example, the spectrum access system (SAS) model for 3.5 GHz band is intended for naval radars. According to the SAS model, the incumbent users (e.g., naval radars) are guaranteed to have a highest priority and interference-free access of the band while priority access license (PAL) users (e.g., mobile service providers) have prioritized access of the band when incumbents are absent. The band can also be used by generalized authorized access (GAA) (e.g., WiFi) users for whom no priority and interference-free environment is guaranteed.

The inventors of this disclosure foresee a need for efficient techniques and tools for detecting and classifying wireless signals that are useable across a variety of transmission environments. Moreover, the inventors of this disclosure foresee a need for efficient mechanisms and protocols for detecting the presence of incumbent transmitters, channel allocation among PAL users, and spectrum usage enforcement among PALs and GAAs with the tiered access.

Moreover, understanding the surrounding wireless/radio-frequency (RF) environment is a long coveted ability. Early it was for military and defense applications, but with the tremendous increase in the use of wireless devices, the ability to understand wireless environments is becoming a necessity. For example, wireless devices are increasingly being used in modern industrial facilities for automation, monitoring and control of equipment, inventory tracking, and more. There is a growing need for continuous monitoring of wireless signals to identify anomalous wireless usage in industrial facilities, power substations, and nuclear plants, to name a few needs, where, for example, a personal device or external device may interfere with and/or disrupt a wireless system and even lead to hazardous results.

The inventors of this disclosure foresee a need for systems for monitoring wireless environments and detecting and classifying wireless signals that are useable across a variety of wireless environments. Moreover, the inventors of this disclosure foresee a need for systems for monitoring wireless environments that are robust and flexible enough to adapt to changes in a wireless environment, especially changes that occur in critical infrastructure.

Moreover, the inventors of this disclosure foresee a need for monitoring systems that may be deployed quickly into a variety of wireless environments, and that automatically tune to a wireless environment.

BRIEF SUMMARY

Some embodiments of the present disclosure relate to a computer-implemented wireless signal classification method. The method may include: receiving a first wireless signal classification, the first wireless signal classification based on blocks of radio frequency (RF) measurements of a wireless spectrum over a period of time; receiving a second wireless signal classification, the second wireless signal classification based on part of the blocks of RF measurements; weighting the first wireless signal classification and weighting the second wireless signal classification; and merging the weighted first wireless signal classification and the weighted second wireless signal classification to arrive at a classification result.

Some embodiments of the present disclosure relate to a system. The system may include an energy-based detector configured to analyze an entire set of measurements and generate a first signal classification result; a cyclostationary-based detector configured to analyze less than the entire set of measurements and generate a second signal classification result; and a classification merger module configured to merge the first signal classification result and the second signal classification result.

