Isaac Cushman

Adaptive threshold based combined energy and spectrum-width detection for RF channel sensing in cognitive networks using USRP B200 GNU radios: An experimental study

Spectrum sensing is the process of determining whether a wireless channel is active or idle. It is mainly implemented in dynamic spectrum access in cognitive radio networks which is a potential solution for spectrum scarcity created by static allocation of RF spectrum for exclusive use. In this paper, we investigate adaptive threshold based spectrum sensing using USRP B200 GNU radios. We use adaptive threshold based method for width and energy detection to find active channels which are avoided by the cognitive radio network users. Energy detection based approach may result in high false alarm since it does not consider the width of the signal spectra. Thus to avoid this, we consider both width of the signal spectra and energy level to detect the signal in a given band. Once cognitive radio identifies active channels, it avoids those active channels if it chooses to use them for opportunistic communications and/or reports those idle channels to database for other unlicensed secondary users. We evaluate the performance of the proposed adaptive approach using B200 GNU radios through false alarm and misdetection probabilities. We found that proposed method help to get low false alarm and misdetection probabilities.

Securing Real-Time Opportunistic Spectrum Access in Cognitive Networks against Malicious Secondary Users

Communications in future wireless systems are expected to rely on opportunistic RF spectrum access where unlicensed secondary users either sense RF spectrum to find idle channels or search for idle channels in a geolocation database of idle spectrum. To avoid channel sensing uncertainties, the FCC mandates that secondary users should query geolocation database to find idle channels for given location and time to communicate opportunistically. However, malicious secondary users can fake their geolocations using GPS spoofing techniques to pretend to be in a place where more idle channels are available. In this paper, we implement and investigate how to secure real-time opportunistic spectrum access in cloud based cognitive radio networks (aka ROAR) against malicious secondary users using angle-of- arrival, received signal strength and time-of- arrival. The proposed approach checks the legitimacy of geolocation reported by the secondary users using cloud computing platform before releasing any idle channel information to them to protect licensed primary users. We implement three step detection process to differentiate the legitimate secondary users from malicious ones which help secure ROAR against untrustworthy secondary users. The proposed approach is illustrated through numerical results obtained from both simulations and experiments.

A Framework and the Design of Secure Mobile Cloud with Smart Load Balancing

The use of mobile devices has exponentially expanded in recent years. A device which was made with the sole purpose of making mobile audio phone calls is now the leading basis for functionality in the social world. The types of applications widely vary from audio and video calls, internet browsing, healthcare applications, to mobile games with online connectivity, among many others. These applications have expanded the original idea of what a mobile device could be, however there have been constant drawbacks to these devices, namely short battery life and limited available storage memory. Another current issue that exists with mobile devices is the higher data consumption when on mobile network data. To solve this problem, it is possible to use cloud computing to mitigate these large applications and use less data. Integrating in a mobile cloud system to allocate and store these applications will allow for the mobile devices to conserve battery and memory by avoiding large computational processes. Another major concern is security breaches resulting in data theft and/or invasion of privacy. In this paper, we present a new framework that will allow for a smart load balancer to efficiently allocate resources to increase application processing speed for data and request response of memory stored by mobile devices in a secure manner.

Performance Evaluation of Vehicular Ad Hoc Networks for Rapid Response Traffic Information Delivery

Vehicular transportation has received rapid growth in many areas thanks to the increase in population density and massive city expansion. Such advancement however leads to the loss of time, money and human lives due to many reasons including driver distraction and serious roadway conditions. Recent trends have shown improvement of vehicular safety on account of design and manufacturing innovations such as additional airbags and pre-collision detection and warning using sensors. Nonetheless, the national averages of fatality, injuries, and property damages due to roadway vehicular crashes still remain at high levels. For the purpose of saving lives, reducing fuel costs and travel time on road, it is demanded to have a vehicular communication system that rapidly learns about the environment and promptly respond and notify drivers for decision making. Our research in this paper aims to design a system that utilizes the communications among vehicles in a Vehicular Ad Hoc Network (VANET) and roadside infrastructure-based devices. Our design and analysis indicate that such system can be applied to assist drivers in adjusting their driving for better safety and making route decisions to save time and fuel costs.

Experimental study of dynamic spectrum access for opportunistic mobile communications using USRP devices

Opportunistic spectrum access is regarded as an emerging technique to utilize scarce RF spectrum efficiently. The performance study of opportunistic spectrum often overlooks the impact of unlicensed SU mobility. Many of the methods assume secondary users stationary or with low mobility. In this paper, we investigate the impact of mobility of wireless devices for opportunistic spectrum access and communications using National Instrument Universal Software Radio Peripherals (USPR) 292x devices. Each USRP device sends its geolocation to query the spectrum database for idle channels using dedicated links such as cellular link periodically. If the USRP user is within the contour of idle channels, it gets a list of channels. Then, transmitter and receiver with their respective lists of channels choose a common channel for communications using quorum based rendezvous. Numerical results obtained from experiments are presented to evaluate the proposed approach and we found that the longer (shorter) query interval results in higher (lower) false list of channels for the users.

Adaptive threshold-based RF spectrum scanning through joint energy and bandwidth detection with USRPs in cognitive sensor networks for ROAR architecture

Opportunistic spectrum access in cognitive radio networks is regarded as an emerging technology for efficient utilization of under utilized of idle radio frequency spectrum. For opportunistic spectrum access, wireless devices are required to identify idle spectrum through spectrum sensing. The performance study of existing spectrum sensing algorithms often overlooks bandwidth of the detected signal while detecting the signal using peak of the energy spectrum that crosses the pre-specified threshold. This results in high false alarm probability. In this paper, we evaluate an adaptive threshold based RF spectrum sensing approach using USRP Software Defined Radio (SDR) for real-time opportunistic spectrum access in cloud based cognitive radio networks (ROAR) architecture where both signal energy and band-width of the signal are taken into account. We evaluate the performance of the proposed approach using probability of misdetection and false alarms metrics. The proposed approach can be particularized to a scenario with energy based detection or bandwidth based detection. The proposed approach is illustrated through numerical results obtained from experiments.