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Cognitive radio (CR) is considered as a key enabling technology for dynamic spectrum access to improve spectrum efficiency. Although the CR concept was invented with the core idea of realizing "cognition", the research on measuring CR cognition capabilities and intelligence is largely open. Deriving the intelligence capabilities of CR not only can lead to the development of new CR technologies,...
The rapid advances in wireless communication and sensor technologies facilitate the development of viable mobile-Health applications that boost opportunity for ubiquitous real- time healthcare monitoring without constraining patients' activities. However, remote healthcare monitoring requires continuous sensing for different analog signals which results in generating large volumes of data that needs...
In modern cognitive ratio systems, the spectrum is becoming increasingly crowded and expensive; thus spectrum sensing becomes more important than ever before. Traditional spectrum sensing assumes Gaussian noise (or of other given distributions) in general. However when secondary users (SUs) have no prior information about the measurement distributions, the spectrum sensing schemes assuming given distribution...
Crowdsensing recently attracts great attention from both industry and academia. By fusing and analyzing multi- dimensional sensing data collected from crowdsensing users, it is possible to support health caring, environment mentoring, traffic mentoring and social behavior mentoring. Nonetheless, how to preserve users' data privacy during data fusing, e.g., data aggregation, has been rarely discussed...
Satellite communications (SATCOM) are prone to both intentional and unintentional interference, which can significantly degrade the reliability of packet transmissions. Here, we investigate different approaches for interference mitigation in SATCOM based on dynamic frequency hopping (DFH). We consider a star topology, where multiple LEO satellites transmit packets to a common GEO satellite. The FH...
Wireless sensor networks (WSNs) consist of nodes with limited power resources. A potential method to prolong the lifespan of a node is the use of an antenna which can harvest energy from radio frequency (RF) signals. In this paper, we model a network consisting of nodes with energy harvesting capabilities and a number of dedicated energy transmitters (ETs) which send data to the nodes. We identify...
We present a multi-user multiple-input multiple-output (MIMO) cognitive radio system consisting of a secondary receiver that deploys spatial multiplexing to decode signals from multiple secondary transmitters, under the presence of primary transmissions. The secondary receiver carries out minimum mean-squared error detection to decode the secondary data streams, while it performs spectrum sensing...
Doze mode, which was introduced from Android 6.0 aiming at reducing battery consumption when the device is unused for a long time. This work firstly reveals the internal details of the battery-saving feature, especially about the state transitions. Furthermore, we discover several defects in Android's device drivers associated with doze mode. By exploiting the defects, we implement various proof-of-concept...
Mobile crowdsensing (MCS) is a promising paradigm that utilizes the mobility of people and the sensing capabilities of their mobile devices to accomplish a variety of sensing tasks. In this paper, we adopt the Signaling System No.7 (SS7) as the MCS platform since SS7 can well capture trajectories and mobility patterns of the mobile users. We collect a real-world SS7 data of 1.18 million mobile users...
Mobile sensing, which uses mobile sensors to monitor spatially correlated physical fields, is a promising technique to enhance the flexibility and coverage of wireless sensing systems. However, the position errors of mobile sensors can deteriorate the estimation accuracy of the physical fields. Thus, to optimize the estimation performance, it calls for a trade-off between the resource allocated to...
Recently, Unmanned Aerial Vehicle (UAV) networks attracts a lot of interest as one of promising research areas since it can be used for a large portfolio of relevant applications. Among several issues in UAV networks, a collision avoidance among multiple UAVs should be addressed due to its significance. Furthermore, a barrier-coverage is considered as an important coverage concept because it is also...
Sharing the spectrum among multiple operators seems promising in millimeter wave (mmWave) systems. One explanation is the highly directional transmission in mmWave, which reduces the interference caused by one network on the other networks sharing the same resources. In this paper, we model a mmWave cellular system where an operator that primarily owns an exclusive-use license of a certain band can...
Radio frequency (RF) recharging can extend maintenance-free operation of wireless sensor networks. However, the period between recharging is limited by the distance between the most distant sensor node and the master which sends out recharging pulses. To increase this period, we propose a scheme in which nodes are logically grouped into circular zones centered at the master, so that nodes in a given...
White Space (WS) Networking crucially relies on the active monitoring of spatio-temporal spectrum usage (to identify WS opportunities). To achieve this, one way is to gather spectrum data via wide-area sensor deployment and construct better Radio Environment Maps (REMs) with spatial models such as Kriging and Gaussian Process (GP). An economically viable alternative is via incentivized crowdsourcing,...
In this paper, we propose to learn LIfestyles of mobile users via mobile Phone Sensing (LIPS), and we develop a system and algorithms to realize this idea. First, we present the workflow and architecture of our system, LIPS. Combining both unsupervised and supervised learning, we propose a hybrid scheme for lifestyle learning, which consists of two parts: characterization and prediction. Specifically,...
Mobile crowdsensing emerges as a promising sensing paradigm through leveraging the diverse embedded sensors in massive mobile devices. A key objective in mobile crowdsensing is to efficiently schedule mobile device users to perform multiple sensing tasks. Prior work mainly focused on the interactions between the task layer and the user layer, without considering the similarity of tasks' data requirements...
Nowadays, the widespread use of Mobile Devices (MDs) open the door to exploit the presence of multiple nodes to accomplish collaborative tasks. In this paper, a speaker recognition system for MDs based on a multiple-observations approach is presented. We propose different fusion and clustering algorithms aimed at efficiently exploiting signals coming from multiple sensors. Numerical results show that...
This paper proposes an improved method for reconstructing wideband sparse spectrum. We utilize a multicoset setup based on time delay. The simple multicoset setup is more suitable for practical implementation in comparison to more sophisticated sub-Nyquist systems. We first introduce the general reconstruction model that solves for a fixed number of variables. We employ a simple machine learning technique...
Mobile location-based services (LBSs) empowered by mobile crowdsourcing provide users with context- aware intelligent services based on user locations. As smartphones are capable of collecting and disseminating massive user location-embedded sensing information, privacy preservation for mobile users has become a crucial issue. This paper proposes a metric called privacy exposure to quantify the notion...
With the proliferation of mobile devices, spatial crowdsourcing is rising as a new paradigm that enables individuals to participate in tasks related to some locations in the physical world. Nevertheless, how to allocate these tasks to proper mobile users and improve communication efficiency are critical in spatial crowdsourcing. In this paper, we propose Fo-DSC, a fog-based deduplicated spatial crowdsourcing...
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