Received signal strength based device-free localization applications utilize a model that relates the measurements to position of the wireless sensors and person, and the underlying inverse problem is solved either using an imaging method or a nonlinear Bayesian filter. In this paper, it is shown that Bayesian filters nearly reach the posterior Cramer-Rao bound and they are superior with respect to

Human mobility trajectories are increasingly collected by ISPs to assist academic research and commercial applications. In this paper, we collected a large-scale ground-truth trajectory dataset from 2,161,500 users of a cellular network, and two matched external trajectory datasets from a large social network (56,683 users) and a check-in/review service (45,790 users) on the same user population. We

Traditional power-based localization methods suffer from low accuracy in the practical application environment. The main challenges are the antenna directivity and fading effect. Conventional methods assume omnidirectional antenna directivity such that the solution is the intersections of multiple circle-shape contours. This strong assumption results in significant localization error in practical non-isotropic

With the development of smart cities, Internet services will be pervasively accessible for moving vehicles. It is envisioned that the video content demand of vehicles will explode in the near future. However, the strategy to efficiently distribute video content in large-scale vehicular networks is still absent due to challenges arising from the huge video population, heavy bandwidth consumption, heterogeneous

As an emerging service architecture, microservice enables decomposition of a monolithic web service into a set of independent lightweight services which can be executed independently. With mobile edge computing, microservices can be further deployed in edge clouds dynamically, launched quickly, and migrated across edge clouds easily, providing better services for users in proximity. However, the user

In this study, an energy-efficient self-organized framework for sub-channel allocation and power allocation is presented for ultra-dense small cell networks, which can operate in both licensed and unlicensed bands. In order to protect legacy WiFi devices(operating in unlicensed bands), we consider the LTE operation in unlicensed bands based on CSAT, in which ‘ON’ and ‘OFF’ dutycycle approach is utilized

Distributed Interactive Applications (DIAs) such as virtual reality and multiplayer online game usually require fast processing of tremendous data and timely exchange of delay-sensitive action data and metadata. This makes traditional mobile-based or cloud-based solutions no longer effective. Thanks to edge computing, DIA Service Providers (DSPs) can rent resources from Edge Infrastructure Providers

In this paper, joint resource management for device-to-device (D2D) communication assisted multi-tier fog computing is studied. In the considered system model, each subscribed mobile end user can choose to offload its computation task to either an edge server deployed at the base station via the cellular connection or one nearby third-party fog node via the direct D2D connection. After receiving offloading

We consider a public blockchain realized in the mobile edge computing (MEC) network, where the blockchain miners compete against each other to solve the proof-of-work puzzle and win a mining reward. Due to limited computing capabilities of their mobile terminals, miners offload computations to the MEC servers. The MEC servers are maintained by the service provider (SP) that sells its computing resources

A key technology in the movement tracking of marine animals is localization using acoustic transmitters. These are attached to marine animals and are detected by an array of receivers. Then, offline localization is performed by multilateration. However, due to the transmitter's low power and environmental conditions, emissions may be detected by only a limited number of receivers, causing localization

In-app advertising has served as the major revenue source for millions of app developers in the mobile Internet ecosystem. Ad networks play an important role in app monetization by providing third-party libraries for developers to choose and embed into their apps. Various ad mediations help developers manage all of the ad libraries used in apps to show the best available ad among received ads from

Unmanned Aerial Vehicle (UAV) Networks have recently attracted great attention as being able to provide convenient and fast wireless connections. One central question is how to allocate a limited number of UAVs to provide wireless services across a large number of regions, where each region has dynamic arriving flows and flows depart from the system once they receive the desired amount of service (referred

Unmanned Aerial Vehicle (UAV) have emerged as a promising technique to rapidly provide wireless services to a group of mobile users simultaneously. The paper aims to address a challenging issue that each user is selfish and may misreport his location or preference for changing the optimal UAV location to be close to himself. Using algorithmic game theory, we study how to determine the final location

WiFi based gesture recognition has received significant attention over the past few years. However, the key limitation of prior WiFi based gesture recognition systems is that they cannot recognize the gestures of multiple users performing them simultaneously. In this paper, we address this limitation and propose WiMU, a WiFi based Multi-User gesture recognition system. The key idea behind WiMU is that

Powering cellular networks with hybrid energy supplies is not only environment-friendly but can also reduce the on-grid energy consumption, thus being emerging as a promising solution for green networking. Intelligent management of spectrum and power can increase the network utility in cellular networks with hybrid energy supplies, usually at the cost of higher energy consumption. Unlike prior studies

Mobile Edge Computing (MEC) pushes computing functionalities away from the centralized cloud to the proximity of data sources, thereby reducing service provision latency and saving backhaul network bandwidth. Although computation offloading for MEC systems has been extensively studied in the literature, service placement is an equally, if not more, important design topic of MEC, yet receives much less

Deep learning models are being deployed in many mobile intelligent applications. End-side services, such as intelligent personal assistants, autonomous cars, and smart home services often employ either simple local models on the mobile or complex remote models on the cloud. However, recent studies have shown that partitioning the DNN computations between the mobile and cloud can increase the latency

Thanks to flexible deployment and excellent maneuverability, autonomous drones are regarded as an effective means to enable aerial data capture in large-scale wireless sensor networks with limited to no cellular infrastructure, e.g., smart farming in a remote area. A key challenge in drone-assisted sensor networks is that the autonomous drone's maneuvering can give rise to buffer overflows at the ground

360-degree video streaming provides users with immersive experience by letting users determine their field-of-views (FoVs) in real time. To enhance the users' quality of experience (QoE) given their limited bandwidth, recent works have proposed a viewport adaptive 360-degree video streaming model by exploiting the bitrate adaptation in spatial and temporal domains. Under this video streaming model

Wireless virtualization has become a key concept in future cellular networks which can provide virtualized wireless networks for different mobile virtual network operators (MVNOs) over the same physical infrastructure. Resource allocation is a main challenging issue in wireless virtualization for which auction approaches have been widely used. However, for most existing auction-based allocation schemes

Natural disasters affect millions of people every year. Finding missing persons in the shortest possible time is of crucial importance to reduce the death toll. This task is especially challenging when victims are sparsely distributed in large and/or difficult-to-reach areas and cellular networks are down. In this paper we present SARDO, a drone-based search and rescue solution that exploits the high

Existing mobile photo crowdsensing approaches focus on the participant-to-server photo pre-selection, i.e., reducing the photo redundancy from participants to a server. The server may still receive plenty of photos for a target area. Yet, another important problem is to select a proper photo subset of an area from the server to a requester. This is a challenging problem because the selected subset

Network transmission over millimeter-wave (mmW) bands has a big potential to provide orders of higher bandwidth. However, beamforming is generally needed to compensate for the high path loss. As mmW antennas have a potentially large number of candidate beamforming directions, to achieve high network throughput, the finding of a high gain direction between a base station and each mobile in the mmW network

Video streaming over mobile is flourishing, and most commercial players use adaptive bitrate (ABR) streaming to deliver video in varying network conditions. Using network capacity and buffer occupancy as system states, ABR algorithms adjust bitrate based on the instantaneous system states, which is able to adapt to network changes in real-time and ensure high quality of experience (QoE). However, they

We present the model, design, and implementation of SMARS, the first practical Sleep Monitoring system that exploits Ambient Radio Signals to recognize sleep stages and assess sleep quality. This will enable a future smart home that monitors daily sleep in a ubiquitous, non-invasive and contactless manner, without instrumenting the subject's body or the bed. The key enabler underlying SMARS is a statistical

We consider the problem of efficient packet dissemination in wireless networks with point-to-multipoint wireless broadcast channels. We propose a dynamic policy, which achieves the broadcast capacity of the network. This policy is obtained by first transforming the original multi-hop network into a precedence-relaxed virtual single-hop network and then finding an optimal broadcasting policy for the

Mobile edge caching/computing (MEC) has been emerging as a promising paradigm to provide ultra-high rate, ultra-reliable, and/or low-latency communications in future wireless networks. In this paper, we introduce a novel MEC network architecture that leverages the optimal joint caching-delivering with horizontal cooperation among mobile edge nodes (MENs). To that end, we first formulate the content-access

This paper considers a scenario in which an access point (AP) is equipped with a server of finite computing power, and serves multiple resource-hungry users by charging users a price. This price helps to regulate users’ behavior in offloading jobs to the AP. However, existing works on pricing are based on abstract concave utility functions, giving no dependence on physical layer parameters. To that

In a variety of network applications, there exists a significant amount of shared data between two end hosts. Examples include data synchronization services that replicate data from one node to another. Given that shared data may have a high correlation with new data to transmit, we question how such shared data can be best utilized to improve the efficiency of data transmission. To answer this, we

Mobile location-based services are important context-aware services that are more and more used for enforcing security policies, for supporting indoor room navigation, and for providing personalized assistance. However, a major problem still remains unaddressed—the lack of solutions that work across buildings while not using additional infrastructure and also accounting for privacy and reliability

Mobile crowdsensing (MCS) represents a new sensing paradigm that utilizes the smart mobile devices to collect and share data. Traditional MCS systems mainly leverages the people carried smartphones and other wearable devices which are constrained by the limited sensing capability and battery power. With the popularity of unmanned vehicles like unmanned aerial vehicles (UAVs) and driverless cars, they

Deep learning has been becoming a promising focus in data mining research. With deep learning techniques, researchers can discover deep properties and features of events from quantitative mobile sensor data. However, many data sources are geographically separated and have strict privacy, security, and regulatory constraints. Upon releasing the privacy-sensitive data, these data sources generally no

Connected and automated vehicles will enable advanced traffic safety and efficiency applications thanks to the dynamic exchange of information between vehicles, and between vehicles and infrastructure nodes. Connected vehicles can utilize IEEE 802.11p for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. However, a widespread deployment of connected vehicles and the introduction

We develop CACE (Constraints And Correlations mining Engine), a framework that significantly improves the recognition accuracy of complex daily activities in multi-inhabitant smarthomes. CACE views the implicit relationships between the activities of multiple people as an asset, and exploits such constraints and correlations in a hierarchical fashion, taking advantage of both person-specific sensor

Wireless communication is easily eavesdropped due to the broadcast nature of the wireless medium. This has spurred extensive research into secret key establishment using physical layer characteristics of wireless channels. In all these schemes, the secret keys directly originate from the physical features of the real wireless channel, which is highly dependent on the communication environment nearby

Wireless power transfer (WPT) technology enables a cost-effective and sustainable energy supply in wireless networks. However, the broadcast nature of wireless signals makes them non-excludable public goods, which leads to potential free-riders among energy receivers. In this study, we formulate the wireless power provision problem as a public goods provision problem, aiming to maximize the social

Presents the introductory editorial for this issue of the publication.

Assuring the required quality of service, despite the growing volume and variety of Internet of Things (IoT) traffic, has remained an immense challenge in the popular WiFi networks. The IoT devices using short TCP flows often attain very different levels of service due to the complicated interactions between the transport layer protocol and the shared dynamic wireless medium. We develop in this paper

Satellite-based communication technology has gained much attention in the past few years, where satellites play mainly the supplementary roles as relay devices to terrestrial communication networks. Unlike previous work, we treat the low-earth-orbit (LEO) satellites as secure data storage mediums. We focus on data acquisition from a LEO satellite based data storage system (also referred to as the LEO

We propose a distributed learning algorithm for the resource allocation problem in Device-to-Device (D2D) wireless networks that takes into account the throughput estimation noise. We first formulate a stochastic optimization problem with the objective of maximizing the generalized alpha-fair function of the network. In order to solve it distributively, we then define and use the framework of noisy-potential

Biometric authentication offers advantages over current security practices. Unlike keys and tokens, biometrics are never lost or stolen. Unlike passwords, biometrics cannot be forgotten. However, existing biometric systems are with controversy: once divulged, they are compromised forever. To this end, this paper explores a truly cancelable brain-based biometric system for the first time. Specifically

In this paper, we present a novel learning-aided energy management scheme ($\mathtt {LEM}$LEM) for multihop energy harvesting networks. Different from prior works on this problem, our algorithm explicitly incorporates information learning into system control via a step called perturbed dual learning. $\mathtt {LEM}$LEM does not require any statistical information of the system dynamics for implementation

Accurate forecast of citywide crowd flows on flexible region partition benefits urban planning, traffic management, and public safety. Previous research either fails to capture the complex spatiotemporal dependencies of crowd flows or is restricted on grid region partition that loses semantic context. In this paper, we propose DeepFlowFlex, a graph-based model to jointly predict inflows and outflows

In interfering WLANs, clients are usually non-uniformly distributed. Therefore, their throughput can be improved by association control. WLANs adopt DCF (Distributed Coordinating Function) for media access control. The transmit probability of an AP is governed by its CW (Contention Window). Random Access control is to determine the CW size and hence the transmit probability of each AP. Client association

Cooperative offloading in mobile edge computing enables resource-constrained edge clouds to help each other with computation-intensive tasks. However, the power of such offloading could not be fully unleashed, unless trust risks in collaboration are properly managed. As tasks are outsourced and processed at the network edge, completion latency usually presents high variability that can harm the offered

Ever-increasing research efforts have been dedicated to radio frequency identification (RFID) systems, such as finding top-k, elephant groups, and missing-tag detection. While group labeling, which is how to tell tags their associated group data, is the common prerequisite in many RFID applications, its efficiency is not well optimized due to the transmission of useless data with only one seed used

For slotted random access systems with a single channel, the slotted ALOHA (S-ALOHA) protocol shows 0.368 (packets/slot) as the maximum throughput, whereas some splitting (or tree) algorithms exhibit 0.487 (packets/slot). The S-ALOHA protocol has been widely adopted even for multi-channel systems such as Long-Term Evolution (LTE), as it is more practically implementable. However, the throughput of

Spectrum sharing has been gaining its popular adoption as a potential solution to improve spectrum utilization in future wireless systems. Both Federal Communications Commission (FCC) and European Telecommunications Standards Institute (ETSI) support dynamic spectrum access (DSA) as an enabling technology for spectrum sharing. To effectively realize DSA in practice, users (from both defense and commercial

The various offsets existed in the commodity WiFi devices greatly limit the use of ubiquitous WiFi signals for indoor applications. In this paper, we focus on the estimation and compensation of the residual carrier frequency offset (CFO) for the commodity WiFi devices. Specifically, we consider a distorted channel state information (CSI) model by taking into consideration various CSI errors such as

Age of information is a new network performance metric that captures the freshness of information at end-users. This paper studies the age of information from a scheduling perspective. To that end, we consider a wireless broadcast network where a base-station (BS) is updating many users on random information arrivals under a transmission capacity constraint. For the offline case when the arrival statistics

Multi-User MIMO (MU-MIMO) has attracted much attention due to its significant advantage of increasing the utilization ratio of wireless channels. However, Frequency-Division Duplex (FDD) systems are vulnerable to eavesdropping, since the explicit CSI feedback can be manipulated. In this paper, we show that Time-Division Duplex (TDD) systems are insecure as well. In particular, we show that it is possible

With the unprecedented convenience brought by Apps on mobile devices, we are facing severe security attacks and privacy leakage caused by them since they may stealthily access unclaimed or unneeded permissions for some purposes. Many works strive to discover these malicious apps using program analysis techniques, however, they fail to tell users why an app needs to request the permission from users’

Android Application Framework is an integral and foundational part of the Android system. Each of the two billion (as of 2017) Android devices relies on the system services of Android Framework to manage applications and system resources. Given its critical role, a vulnerability in the framework can be exploited to launch large-scale cyber attacks and cause severe harms to user security and privacy

Recent diversification of mobile computing devices allows a mobile user to own multiple types of devices for different application scenarios, but also results in various restrictions on the performance and usability of these devices. A viable solution to such restriction is to incorporate and interconnect mobile devices towards a personal mobile cloud where these devices can complement each other via

The emergence of multi-beam directional antennas (MBDAs) has paved the way for fast and high-throughput data communications by providing concurrent multi-directional transmissions. However, the existing routing protocols are not capable of utilizing the advantages of MBDAs. In this paper, we have developed a new routing scheme, called volcano routing, which can exploit the concurrent packet dispatching

Device-to-Device (D2D) communications incorporated with content caching have been regarded as a promising way to offload the cellular traffic data. In this paper, the caching strategy is investigated to maximize the D2D offloading gain with the comprehensive consideration of user collaborative characteristics as well as the physical transmission conditions. Specifically, for a given content, the number

Adaptive bitrate streaming (ABR) has become the de facto technique for video streaming over the Internet. Despite a flurry of techniques, achieving high quality ABR streaming over cellular networks remains a tremendous challenge. ABR streaming can be naturally modeled as a control problem. There has been some initial work on using PID, a widely used feedback control technique, for ABR streaming. Existing

Nowadays, smart wristbands have become one of the most prevailing wearable devices, as they are small and portable. However, due to the limited size of the touch screens, smart wristbands typically have poor interactive experience. There are a few works appropriating the human body as a surface to type on. Yet, by using multiple sensors at high sampling rates, they are not portable and are energy-consuming

In mobile crowd sensing (MCS) applications, a public model of a system is expected to be derived from observations collected by mobile device users, through regression modeling. For example, a model describing the relationship between running speed, heart rate, height, and weight of runner can be constructed using MCS data collected from wristbands. Unique features of MCS data bring regression new

The 802.11ac is a significant landmark in wireless communications, as it pushes towards new rate limits by utilizing downlink multiuser multiple-input multiple-output (MIMO) beamforming to transmit data to various locations simultaneously. However, successful beamforming relies on intelligent user selection which requires, in turn, extensive overhead of channel calibration between the AP and each of