Convolutional Neural Networks Based Indoor Wi-Fi Localization with a Novel Kind of CSI Images

Indoor Wi-Fi localization of mobile devices plays a more and more important role along with the rapid growth of location-based services and Wi-Fi mobile devices.In this paper,a new method of constructing the channel state information(CSI)image is proposed to improve the localization accuracy.Compared with previous methods of constructing the CSI image,the new kind of CSI image proposed is able to contain more channel information such as the angle of arrival(AoA),the time of arrival(TOA)and the amplitude.We construct three gray images by using phase differences of different antennas and amplitudes of different subcarriers of one antenna,and then merge them to form one RGB image.The localization method has off-line stage and on-line stage.In the off-line stage,the composed three-channel RGB images at training locations are used to train a convolutional neural network(CNN)which has been proved to be efficient in image recognition.In the on-line stage,images at test locations are fed to the well-trained CNN model and the localization result is the weighted mean value with highest output values.The performance of the proposed method is verified with extensive experiments in the representative indoor environment.

WiFace:A Secure GeoSocial Networking System Using Wi-Fi Based Multihop MANET

A number of mobile Online Social Networking （OSN） services have appeared in the market in recent times. While most mobile systems benefit greatly from cloud services, centralized servers and communications infrastructure is not always available. Nor are location-based services offered to mobile devices without GPS. To take advantage of cloud and to address these problems, a Wi-Fi based multihop networking system called MoNet is proposed. On top of MONET we propose a privacy-aware geosocial networking service called WiFace. Where there is no infrastructure, a distributed content sharing protocol significantly shortens the relay path, reduces conflicts, and improves data availability. Furthermore, a security mechanism is developed to protect privacy. Comprehensive experiments performed on MoNet show that the system is more than sufficient to support social networking and even audio and video applications.

A Framework for Multi-Hop Ad-Hoc Networking over Wi-Fi Direct with Android Smart Devices

The wide diffusion of mobile devices that natively support ad hoc communication technologies has led to several protocols for enabling and optimizing Mobile Ad Hoc Networks (MANETs). Nevertheless, the actual utilization of MANETs in real life seems limited due to the lack of protocols for the automatic creation and evolution of ad hoc networks. Recently, a novel P2P protocol named Wi-Fi Direct has been proposed and standardized by the Wi-Fi Alliance to facilitate nearby devices’ interconnection. Wi-Fi Direct provides high-performance direct communication among devices, includes different energy management mechanisms, and is now available in most Android mobile devices. However, the current implementation of Wi-Fi Direct on Android has several limitations, making the Wi-Fi Direct network only be a one-hop ad-hoc network. This paper aims to develop a new framework for multi-hop ad hoc networking using Wi-Fi Direct in Android smart devices. The framework includes a connection establishment protocol and a group management protocol. Simulations validate the proposed framework on the OMNeT++ simulator. We analyzed the framework by varying transmission range, number of hops, and buffer size. The results indicate that the framework provides an eventual 100% packet delivery for different transmission ranges and hop count values. The buffer size has enough space for all packets. However, as buffer size decreases, the packet delivery decreases proportionally.

Cambium Networks推出Wi-Fi墙壁面板解决方案

全球领先的无线网络解决方案提供商Cambium Networks今天宣布推出新的云管理企业级Wi-Fi墙壁面板接入点cnPilot e430W。该接入点支持802.11ac Wave 2标准,是为酒店、度假村和多住宅单元(MDU)提供连接的最佳解决方案。该接入点安装在墙上,使用多个千兆以太网(Gig E)端口通过托管门户提供室内WiFi和有线端口网络接入。Frontera Consulting联合创始人Drew

Aruba Networks携手YinzCam为观众带来全新的体育场馆Wi-Fi体验

如今，越来越多体育场馆、剧场及其他大型公共场所的观众使用移动设备上传视频、分享照片、查看信息并通过社交媒体相互联系。然而，电信运营商的蜂窝网络现在已无法在如此高密度的设备环境下，为这些占用大量带宽资源的应用提供足够的网络容量。虽然一些场馆已经部署了wi-Fi，但其中大部分网络还是无法充分满足不断增加的移动设备连接网络的需求。

Cross-Tier Interference Mitigation in 3D HetNets for LTE and Wi-Fi Access

Due to the unprecedented rate of transformation in thefield of wireless communication industry,there is a need to prioritise the coverage,network power and throughput as preconditions.In Heterogeneous Networks(HetNets)the low power node inclusion like Femto and Pico cells creates a network of Multi-Tier(M-Tier)which is regarded as the most significant strategy for enhancing the coverage,throughput,4G Long Term Evolution(LTE)ability.This work mainly focuses on M-Tier 3D Heterogeneous Networks Energy Efficiency(EE)based Carrier Aggregation(CA)scheme for streaming real-time huge data like images.Atfirst,M-Tier 3D HetNets scheme was made for investigating Signal to Noise Interference Ratio(SNIR)on assessing the collective Pico-tier and Femto-tier interference.Next,the scheme of channel allocation is scrutinised so as to esti-mate throughput from the multiple tiers.Additionally,with the use of CA technique,the problem of energy efficiency for M-Tier 3D Heterogeneous Network(HetNet)in relation to energy metrics and throughput was evaluated with the use of LTE and Wireless Fidelity(Wi-Fi)coexistence.The simulation is carried out in a MATLAB setting,and the outcomes reveal a huge impact on EE.The simulation is carried in terms of EE,transmission time,throughput,packet success rate,convergence probability,and coverage region.The analysis from simu-lation shows that on improving the output of the device,interference among small cell base stations is reduced on increasing EE.The outcomes attained aid in the effective creation of M-Tier 3D HetNets for enhancing EE by employing Multi-Stream Carrier Aggregation(MSCA)in HetNets.

An Improved Convolutional Neural Network Based Indoor Localization by Using Jenks Natural Breaks Algorithm

With the rapid growth of the demand for indoor location-based services(LBS), Wi-Fi received signal strength(RSS) fingerprints database has attracted significant attention because it is easy to obtain. The fingerprints algorithm based on convolution neural network(CNN) is often used to improve indoor localization accuracy. However, the number of reference points used for position estimation has significant effects on the positioning accuracy. Meanwhile, it is always selected arbitraily without any guiding standards. As a result, a novel location estimation method based on Jenks natural breaks algorithm(JNBA), which can adaptively choose more reasonable reference points, is proposed in this paper. The output of CNN is processed by JNBA, which can select the number of reference points according to different environments. Then, the location is estimated by weighted K-nearest neighbors(WKNN). Experimental results show that the proposed method has higher positioning accuracy without sacrificing more time cost than the existing indoor localization methods based on CNN.

Multi-Criteria Prediction Mechanism for Vehicular Wi-Fi Offloading

The growing demands of vehicular network applications,which have diverse networking and multimedia capabilities that passengers use while traveling,cause an overload of cellular networks.This scenario affects the quality of service(QoS)of vehicle and non-vehicle users.Nowadays,wireless fidelity access points Wi-Fi access point(AP)and fourth generation long-term evolution advanced(4G LTE-A)networks are broadly accessible.Wi-Fi APs can be utilized by vehicle users to stabilize 4G LTE-A networks.However,utilizing the opportunistic Wi-Fi APs to offload the 4G LTE-A networks in a vehicular ad hoc network environment is a relatively difficult task.This condition is due to the short coverage of Wi-Fi APs and weak deployment strategies of APs.Many studies have proposed that offloading mechanisms depend on the historical Wi-Fi connection patterns observed by an interest vehicle in making an offloading decision.However,depending solely on the historical connection patterns affects the prediction accuracy and offloading ratio of most existing mechanisms even when AP location information is available.The present study proposed a multi-criteria wireless availability prediction(MWAP)mechanism,which utilizes historical connection patterns,historical data rate information,and vehicular trajectory computation to predict the next available AP and its expected data capacity in making offloading decisions.The proposed mechanism is decentralized,where each vehicle makes the prediction by itself.This characteristic helps the vehicle users make a proactive offloading decision that maintains the QoS for different applications.A simulation utilizing MATLAB was conducted to evaluate the performance of the proposed mechanism and benchmark it with related state-of-the-art mechanisms.A comparison was made based on the prediction error and offloading ratio of the proposed mechanism in several scenarios.The MWAP mechanism exhibited a lower prediction error(i.e.,below 20%)and higher offloading ratio(i.e.,above 90%)than the existing mechanisms for several tested scenarios.

Learning to Optimize for Resource Allocation in LTE-U Networks

This paper proposes a deep learning(DL)resource allocation framework to achieve the harmonious coexistence between the transceiver pairs(TPs)and the Wi-Fi users in LTE-U networks.The nonconvex resource allocation is considered as a constrained learning problem and the deep neural network(DNN)is employed to approximate the optimal resource allocation decisions through unsupervised manner.A parallel DNN framework is proposed to deal with the two optimization variables in this problem,where one is the licensed power allocation unit and the other is the unlicensed time fraction occupied unit.Besides,to guarantee the feasibility of the proposed algorithm,the Lagrange dual method is used to relax the constraints into the DNN training process.Then,the dual variable and the DNN parameter are alternating update via the batch-based gradient decent method until the training process converges.Numerical results show that the proposed algorithm is feasible and has better performance than other general algorithms.

SDN-Based Data Offloading for 5G Mobile Networks

The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applications and terminals with improved multi- media. Wi-Fi is an essential approach to alleviating mobile data traffic load on a cellular network because it provides extra capacity and improves overall performance. In this paper, we propose an integrated LTE/Wi-Fi architecture with software-defined networking （SDN） abstraction in mobile baekhaul and enhanced components that facilitate the move towards next-generation 5G mo- bile networks. Our proposed architecture enables programmable offloading policies that take into account real-time network conditions as well as the status of devices and applications. This mechanism improves overall network performance by deriving real- time policies and steering traffic between cellular and Wi-Fi networks more efficiently.

A Software Defined Open Wi-Fi Platform

Wireless local area network(WLAN) is an indivisible part of the next generation wireless system. In this paper, an open Wi-Fi platform is designed and developed with special consideration of real-time signal processing. Such system can help accelerate research and development of future wireless network, especially in the case of cellular/Wi-Fi co-existing networks. This platform is based on the Intel general-purpose processor and the universal software radio peripheral(USRP) radio front end. The design including the physical layer implementations is purely software and is optimized for real-time signal processing on the general purpose processor. In the lab experiment, this platform supports baseband rate up to 700 Mbps with 2 transmitters in 80 MHz bandwidth. A cellular-Wi-Fi signaling interface between the Wi-Fi access point(AP) and the 5G core network is also developed and validated as an example for wireless resource allocation.

Drone Based Wireless Mesh Network for Disaster/Military Environment

In recent years, researches of disseminating wireless network have been conducted for areas without network infrastructure such as disaster situation or military disputes. However, conventional method was to provide a communication infrastructure by floating large aircraft as UAV or hot-air balloon in the high air. Therefore, it was difficult to utilize previous method because it requires a lot of time and cost. But it is possible to save money and time by using a drone which is already used in many areas as a small UAV. In this paper, we design a drone that can provide wireless infrastructure using high speed Wi-Fi. After reaching the target area, the drone can provide Wi-Fi using wireless mesh network and transmit the situation of local area through attached camera. And the transmitted videos can be monitored in the control center or cell phone through application in real time. The proposed scheme provides wireless communication of up to 160 Mbps in a coverage of about 200 m and video transmission with a coverage of about 120 m, respectively.

Towards Practical Implementation of Data and Energy Integrated Networks

With the rapid development of the mobile internet and the massive deployment of the Internet of Things, mobile devices, including both the consumer electronics and the sensors, become hungrier for the energy than ever before. Conventional cable based charging largely restrict the movement of the mobile devices. Wireless charging hence emerges as an essential technique for enabling our ultimate goal of charging anytime and anywhere. By efficiently exploiting the legacy of the existing communication infrastructure, we propose a nov- el data and energy integrated network （DEIN） in order to re- alise the radio frequency （RF） based wireless charging with- out degrading the information transmission. In this treatise, we focus on the implementation of the DEIN in both the theoretical and practical aspects, concerning the transceiver architecture design and the rectifier circuit design. Furthermore, we also present a Wi-Fi based testbed for demonstrating the availability of the RF based wireless charging.

Comparison of Vertical Handover Decision-Based Techniques in Heterogeneous Networks

Industry leaders are currently setting out standards for 5G networks projected for 2020 or even sooner. Future generation networks will be heterogeneous in nature as no single network type will be capable of optimally meeting all the rapid changes in customer demands. With the advent of multi-homed devices and heterogeneous network (HetNet) solution, great concerns arise in the processes involved for successful handover. Active calls that get dropped or cases of poor quality of service experienced by mobile users can be attributed to the phenomenon of delayed handover (HO) or an outright case of an unsuccessful handover procedure. This work compares multiple criteria handover basis to its traditional single relative signal strength (RSS) base counterpart. It analyses the performance of a fuzzy-based VHO algorithm scheme in a Wi-Fi, WiMAX, UMTS and LTE integrated network using OMNeT++ event simulator. The loose coupling network architecture is adopted and simulation results analysed for the two major categories of handover;the multiple and single criteria. Results obtained show a better overall throughput, better call dropped rate and shorter handover time for the multiple criteria based decision method as compared to the single criteria based technique. This work also highlights current research trends, challenges of seamless handover and initiatives for Next Generation HetNet.

Wi-Fi Traffic Enforcement System (WiTE)

This paper proposes a single integrated traffic enforcement system that is able to recognize and report various traffic violations. It consists of a Wi-Fi infrastructure that enables communication between moving vehicles and a central node. Unlike existing solutions, which address single violations, the proposed model encompasses several issues like exceeding speed limits, entering a no entry street, car theft, congestion and tolling. OPNET simulations were run to test the Wi-Fi model and define its different characteristics and limitations. A proof-of-concept case was modeled, and the proposed architecture succeeded in meeting all design requirements.

Wireless Fault-Tolerant Controllers in Cascaded Industrial Workcells Using Wi-Fi and Ethernet

A Wireless Networked Control System using 802.11b is used to model fault-tolerance at the controller level of an industrial workcell. The fault-tolerance study in this paper presents the cascading of two independent workcells where each controller must be able to handle the load of both cells in case of failure of the other one. The intercommunication is completely wireless between the cells and this feature is investigated. The model incorporates unmodified 802.11b and 802.11g for communication. Sensors send sampled data to both controllers and the controllers to exchange a watchdog. The fault-free and faulty models are both simulated using OPNET Network Modeler. External interference on the critical intercommunication link is also investigated. Results of simulations are presented based on a 95% confidence analysis, guaranteeing correct system performance.

香港发展高速 免费Wi-Fi无线局域网

Aruba Networks已宣布为电讯盈科提供无线设备，为覆盖香港350个地区的约2000个Wi—Fi热点提供无线局域网络。根据“香港政府Wi-Fi”计划，未来5年中．香港市民和外来游客可在包括至少3个公园在内的350个政府场所免费上高速Wi—Fi无线网。该项目完成后．网络将有数千个接入点和位于电信盈科网络运营中心的多个多服务流控制器。到2008年3月底，在30多个政府场所已安装有关设备，其余的政府场所将于2009年年中安装完毕。

Aruba Networks:将应用和网络完美结合

日前．Aruba发布了其ClearPass接入管理系统的最新组件ArubaWorkSpace，这一组件与其它系统将整合为一个统一的解决方案。同时，Aruba发布了802．11ac最新解决方案。在发布会上。Aruba中国区总裁徐涌指出Wi—Fi市场发展迅速，例如在电信行业。3G和4G的发展推动了wi-Fi的快速发展。目前中国的AP数约为300万个，尽管数量不算太多，但增长迅速，室9bLTE和室内Wi—Fi结合将成为未来网络覆盖的重要方向。

迎接Wi-Fi控部署全移动网络环境

近日,Aruba Networks发布了Aruba Mobility-Defined Networks,一种用于IT部门建设全移动工作环境的全新架构,可以提升Wi-Fi控的满意度和创造力。配合这种新的架构,Aruba同时发布了5种支持高移动员工网络需求的创新软件,为IT带来高粒度的可见性、性能优化和安全自动化。同时,Aruba新任中国区总经理冯满亮（David Fung）首次亮相,他将继续带领Aruba中国团队扩展企业网络市场,助力客户向新一代全移动网络环境的转型。＂随着Wi-Fi控的到来，大量移动终端和应用聚集在企业网络环境中。

Aruba Networks推出802.11ac解决方案

企业的IT部门经受着海量设备连入其网络以及设备密度不断增加的双重挑战，两者都可能导致wi-Fi连接能力不足。同时．IT管理员还面临着“粘滞“客户端或设备无法自动连接到最佳接入点而造成的速度较慢、不一致和不可靠的连接问题。