Application of Wireless Local Area Network Technology in Mobile Robot for Finned Tube Inspection

This paper introduces a novel robot for outer surface inspection of boiler tubes. The paper describes the hardware system, wireless communication strategy, communication procedure and system software of the robot. The WLAN technology is used in the robot. It solves the problem of shielding generated by iron boiler and 11Mbps bandwidth made it possible for video and control stream real-time transmit within the same channel. Though TCP/IP protocol is robust, serial server is a transparent channel but cannot detect error and retransmit the data. In order to improve the reliability of serial communication, a new communication protocol is proposed. Key words boiler tubes - mobile robotics - wireless local area network Project Supported by the National High-Tech Program (Grant No. 2002AA420080)

Resource Exhaustion Attack Detection Scheme for WLAN Using Artificial Neural Network

IEEE 802.11 Wi-Fi networks are prone to many denial of service(DoS)attacks due to vulnerabilities at the media access control(MAC)layer of the 802.11 protocol.Due to the data transmission nature of the wireless local area network(WLAN)through radio waves,its communication is exposed to the possibility of being attacked by illegitimate users.Moreover,the security design of the wireless structure is vulnerable to versatile attacks.For example,the attacker can imitate genuine features,rendering classificationbased methods inaccurate in differentiating between real and false messages.Althoughmany security standards have been proposed over the last decades to overcome many wireless network attacks,effectively detecting such attacks is crucial in today’s real-world applications.This paper presents a novel resource exhaustion attack detection scheme(READS)to detect resource exhaustion attacks effectively.The proposed scheme can differentiate between the genuine and fake management frames in the early stages of the attack such that access points can effectively mitigate the consequences of the attack.The scheme is built through learning from clustered samples using artificial neural networks to identify the genuine and rogue resource exhaustion management frames effectively and efficiently in theWLAN.The proposed scheme consists of four modules whichmake it capable to alleviates the attack impact more effectively than the related work.The experimental results show the effectiveness of the proposed technique by gaining an 89.11%improvement compared to the existing works in terms of detection.

Adaptive rate control on wireless transcoder

To guarantee the real-time transmission of a video stream, based on the stochastic optimal control method, a frame layer adaptive rate control algorithm for the wireless transcoder is proposed, which is capable of dynamically determining the transcoder＇s objective bit rate, according to the bandwidth variation of the wireless channel and the buffer occupancy. Then the transient performance, steady performance, and computational complexity of the algorithm are analyzed. Finally, the experiment results demonstrate that the algorithm can improve the synthetic performance of rate control through the compromise between the end-to-end delay and the playout quality.

Multiusers Parallel Competitive Channel Protocol Based on Unsaturated Service

In order to enhance the area throughput of next generation wireless local area network(WLAN)in high density scenarios,orthogonal frequency division multiple access(OFDMA)has been adopted as one of the key technologies in the next generation WLAN communication standards.However,the performance of the existing media access control(MAC)degrades significantly under unsaturated services.Therefore,this paper proposes a multi-user parallel contention channel MAC(MU-MAC)based on unsaturated services,which can effectively reduce the channel access conflict and improve the OFDMA access efficiency of cluster member nodes.On this basis,MU-MAC is enhanced for the spatial clustering group(SCG)formation protocol and support for the unsaturated service characteristics.Further,the optimal access radius when the service is in a non-saturated state is analyzed to make the relevant theoretical analysis more generally,and the expressions for the throughput and area throughput of the proposed protocol are modeled and derived.The simulation results verify the correctness of the theoretical analysis and the efficiency of the protocol performance.The results show that MU-MAC outperforms IEEE 802.11ax and OMAX protocol in area throughput by 40.72%and 104.15%,respectively.

Security Analysis of Application Layer Protocols on Wireless Local Area Networks

This paper aims at analyzing the security issues that lie in the application layer (AL) protocols when users connect to the Internet via a wireless local area network (WLAN) through an access point. When adversaries launch deauthentication flood attacks cutting users' connection, the connection managers will automatically research the last access point's extended service set identifier (ESSID) and then re-establish connection. However, such re-connection can lead the users to a fake access point with the same ESSID set by attackers. As the attackers hide behind users' access points, they can pass AL's authentication and security schemes, e.g. secure socket layer (SSL). We have proved that they can even spy on users' account details, passwords, data and privacy.

Radio map updated method based on subscriber locations in indoor WLAN localization

With the rapid development of wireless local area network （WLAN） technology, an important target of indoor positioning systems is to improve the positioning accuracy while reducing the online calibration effort to overcome signal time-varying. A novel fingerprint positioning algorithm, known as the adaptive radio map with updated method based on hidden Markov model （HMM）, is proposed. It is shown that by using a collection of user traces that can be cheaply obtained, the proposed algorithm can take advantage of these data to update the labeled calibration data to further improve the position estimation accuracy. This algorithm is a combination of machine learning, information gain theory and fingerprinting. By collecting data and testing the algorithm in a realistic indoor WLAN environment, the experiment results indicate that, compared with the widely used K nearest neighbor algorithm, the proposed algorithm can improve the positioning accuracy while greatly reduce the calibration effort.

Improving throughput through dynamically tuning contention window size in dense wireless network

With the boom of wireless devices, the number of wireless users under wireless local area networks （WLANs） has increased dramatically. However, the standard baekoff mechanism in IEEE 802.11 adopts fixed initial contention window （CW） size without considering changes of network load, which leads to a high collision probability and low channel utilization in bursty arrivals. In this paper, a novel CW dynamic adjustment scheme is proposed to achieve high throughput performance in dense user environment. In the proposed scheme, the initial CW size is dynamically adjusted to optimum according to the measured packet collision probability. Simulation results show that the proposed scheme can significantly improve the throughput performance.

A Semi-Supervised WLAN Indoor Localization Method Based on l1-Graph Algorithm

For indoor location estimation based on received signal strength( RSS) in wireless local area networks( WLAN),in order to reduce the influence of noise on the positioning accuracy,a large number of RSS should be collected in offline phase. Therefore,collecting training data with positioning information is time consuming which becomes the bottleneck of WLAN indoor localization. In this paper,the traditional semisupervised learning method based on k-NN and ε-NN graph for reducing collection workload of offline phase are analyzed,and the result shows that the k-NN or ε-NN graph are sensitive to data noise,which limit the performance of semi-supervised learning WLAN indoor localization system. Aiming at the above problem,it proposes a l1-graph-algorithm-based semi-supervised learning( LG-SSL) indoor localization method in which the graph is built by l1-norm algorithm. In our system,it firstly labels the unlabeled data using LG-SSL and labeled data to build the Radio Map in offline training phase,and then uses LG-SSL to estimate user's location in online phase. Extensive experimental results show that,benefit from the robustness to noise and sparsity ofl1-graph,LG-SSL exhibits superior performance by effectively reducing the collection workload in offline phase and improving localization accuracy in online phase.

Modeling and Simulation of P-Aloha,CSMA /CA and MACAW Protocols for Underwater Acoustic Channel

Medium access control( MAC) protocol of underwater acoustic communication network is a key technology for underwater acoustic networks( UANs). Most of the MAC protocols for wireless terrestrial communication networks have been designed with negligible propagation delay. If it is deployed directly in an underwater environment,the UANs will perform inefficiently. In this paper,the characteristics of underwater acoustic channel are modeled and simulated by using the OPNET simulation tool,which are the speed of sound, propagation loss, and four sources for ambient noise: the turbulence,shipping,wind driven waves and thermal noise. The performance of pure Aloha( P-Aloha),carrier sense multiple access with collision avoidance( CSMA / CA) and multiple access collision avoidance for wireless local area network( MACAW) protocols in underwater acoustic channel environment are evaluated. The different performance of protocols in underwater environment is compared in the simulation.

Improved MIMO-OFDM scheme for the next generation WLAN

The research and application of wireless local area networks （WLAN） technology are in a stage of rapid development. It has been one of research focuses of the wireless communications field. Through the use of enhanced single-user （SU）/multi-user （MU） multiple input multiple output （MIMO）-orthogonal frequency division multiplexing （OFDM） technology, the next generation WLAN IEEE 802.1 lac dramatically increases the throughput. An improved MIMO-OFDM scheme based on modulation diversity is proposed for the next generation WLAN. It uses two-dimensional modulation diversity to the current IEEE 802.11ac transmission scheme. Through the space-time-frequency component inter- leaver and the rotational modulation, the proposed scheme ex- hibits high spectral efficiency and low error rate in fading channels. The simulation results show that the proposed scheme significantly outperforms the SU/MU MIMO-OFDM scheme in the current IEEE 802.11 ac standard, which is up to 5 dB.

Partially Overlapping Channel Assignment Using Bonded and Non-Bonded Channels in IEEE 802.11n WLAN

Nowadays,wireless local area network(WLAN)has become prevalent Internet access due to its low-cost gadgets,flexible coverage and hasslefree simple wireless installation.WLAN facilitates wireless Internet services to users with mobile devices like smart phones,tablets,and laptops through deployment of multiple access points(APs)in a network field.Every AP operates on a frequency band called channel.Popular wireless standard such as IEEE 802.11n has a limited number of channels where frequency spectrum of adjacent channels overlaps partially with each other.In a crowded environment,users may experience poor Internet services due to channel collision i.e.,interference from surrounding APs that affects the performance of the WLAN system.Therefore,it becomes a challenge to maintain expected performance in a crowded environment.A mathematical model of throughput considering interferences from surrounding APs can play an important role to set up a WLAN system properly.While set up,assignment of channels considering interference can maximize network performance.In this paper,we investigate the signal propagation of APs under interference of partially overlapping channels for both bonded and non-bonded channels.Then,a throughput estimation model is proposed using difference of operating channels and received signal strength indicator(RSSI).Then,a channel assignment algorithm is introduced using proposed throughput estimation model.Finally,the efficiency of the proposal is verified by numerical experiments using simulator.The results show that the proposal selects the best channel combination of bonded and non-bonded channels that maximize the performance.

Semi-Supervised Clustering Fingerprint Positioning Algorithm Based on Distance Constraints

With the rapid development of WLAN( Wireless Local Area Network) technology,an important target of indoor positioning systems is to improve the positioning accuracy while reducing the online computation.In this paper,it proposes a novel fingerprint positioning algorithm known as semi-supervised affinity propagation clustering based on distance function constraints. We show that by employing affinity propagation techniques,it is able to use a fractional labeled data to adjust similarity matrix of signal space to cluster reference points with high accuracy. The semi-supervised APC uses a combination of machine learning,clustering analysis and fingerprinting algorithm. By collecting data and testing our algorithm in a realistic indoor WLAN environment,the experimental results indicate that the proposed algorithm can improve positioning accuracy while reduce the online localization computation,as compared with the widely used K nearest neighbor and maximum likelihood estimation algorithms.

Resource Allocation for Uplink CSI Sensing Report in Multi-User WLAN Sensing

Sensing in wireless local area network(WLAN) gains great interests recently. In this paper we focus on the multi-user WLAN sensing problem under the existing 802.11 standards. Multiple stations perform sensing with the access point and transmit channel state information(CSI)report simultaneously on the basis of uplink-orthogonal frequency division multiple access(OFDMA). Considering the transmission resource consumed in CSI report and the padding wastage in OFDMA based CSI report, we optimize the CSI simplification and uplink resource unit(RU)allocation jointly, aiming to balance the sensing accuracy and padding wastage performances in WLAN sensing. We propose the minimize padding maximize efficiency(MPME) algorithm to solve the problem and evaluate the performance of the proposed algorithm through extensive simulations.

Study and simulation of video communications under wireless environment based on blind source separation

A new scheme is proposed to separate several compressed video signals transferred in multiple wireless channels using the blind source separation method.The scheme selects IEEE 802.11b and XVID compression as the wireless communications channel and MPEG-4 video compression,respectively.A simulation model is then made for the video communications under a wireless environment.The model can separate several video sig-nals using blind source separation.Simulations show that the normalized whiten plus cyclic whiten based on cyclo-stationary(NWCW-CS)algorithm based upon the cyclo-stationary characteristics of signals has the best separation performance and fast convergence.Besides,the algorithm can solve the mixing of video signals.The image of the transferred video signals decompressed by XVID is nearly consistent with the source ones.The new method meets the requirement of real-time video communications.

Indoor localization via l^1-graph regularized semi-supervised manifold learning

In this paper, a new -graph regularized semi-supervised manifold learning （LRSML） method is proposed for indoor localization. Due to noise corruption and non-linearity of received signal strength （RSS）, traditional approaches always fail to deliver accurate positioning results. The -graph is constructed by sparse representation of each sample with respect to remaining samples. Noise factor is considered in the construction process of -graph, leading to more robustness compared to traditional k-nearest-neighbor graph （KNN-graph）. The KNN-graph construction is supervised, while the -graph is assumed to be unsupervised without harnessing any data label information and uncovers the underlying sparse relationship of each data. Combining KNN-graph and -graph, both labeled and unlabeled information are utilized, so the LRSML method has the potential to convey more discriminative information compared to conventional methods. To overcome the non-linearity of RSS, kernel-based manifold learning method （K-LRSML） is employed through mapping the original signal data to a higher dimension Hilbert space. The efficiency and superiority of LRSML over current state of art methods are verified with extensive experiments on real data.

Linear-in-dB Variable-Gain Downconversion Mixer for Zero Intermediate Frequency Receivers

In-phase/quadrature （I/Q） mismatch is a key problem in zero intermediate frequency （ZIF） receiver architectures. Although integration and careful layout can alleviate I/Q mismatch, circuit and system level calibrations are also needed due to process variations and variable operating conditions. The amplitude im- balance between I/Q channels was calibrated using a modified R-2R ladder to achieve fine linear-in-dB variable gain. A downconversion mixer working in the 2,4-GHz band was developed for a wireless local area network （WLAN） ZIF receiver using 0.25μm complementary metal-oxide semiconductor （CMOS）. The twostage mixer configuration relaxes the tradeoff between noise and linearity. Experimental results verify the fine linear-in-dB variable conversion gain of the mixer, which can also be used as part of an automatic gain control （AGC）loop.

Reliable beacon transmission based MAC protocol for LR-WPANs over WLAN interferences

The use of IEEE 802.15.4 standard based application systems has been rapidly increasing, for example, in medical services, sensor networks, public safety systems, and home automation systems. However, issues arise from the fact that IEEE 802.15.4 standard based low rate wireless personal area networks(LR-WPANs) use the same frequency bands as wireless local area networks(WLANs), and they interfere with each other. Based on past research on this issue, the interference has a more serious impact on LR-WPANs' performance than on WLANs' performance. In this paper we propose a method to improve LR-WPANs' performance while coexisting with WLANs, which is called the reliable beacon transmission based medium access control(MAC) protocol. Since the reliability of a beacon frame is important, in this method, only the beacon frame is transmitted in interference-free channels, and the data packets are transmitted in interfered channels instead of abandoning the channels altogether. This method increases the reliability of beacon frames as well as overall channel utilizations. The effectiveness of the proposed method was evaluated through extensive simulations, and this paper proves that this method improves the performance of IEEE 802.15.4 based wireless sensor networks(WSNs) over WLANs' interferences.

Full-duplex transmission of IEEE 802.11ac-compliant MIMO WLAN signals over a 2-km 7-core fiber

In this Letter, we experimentally demonstrate a full-duplex transmission system of IEEE 802.11ac-compliant multiple-input multiple-output （MIMO） signals over a 2-kin 7-core fiber for in-building wireless local-area net- work （WLAN） distributed antenna systems. For full-duplex 3 x 3 MIMO demonstration, the crosstalk impacts of both fiber-transmission-only and optic-wireless transmission situation are evaluated. The results indicate that the impact of crosstalk on radio-over-fiber （ROF） link performance is not significant and the quality of the cascaded multi-core fiber and wireless channel is mainly determined by the wireless part. To further improve the system capacity, polarization multiplexing （PolMux） technology is employed to achieve a full-duplex 6 × 6 MIMO over a single 7-core fiber. Although employing the PolMux method will slightly decrease the EVM and condition number performance as opposed to a non-PolMux MCF system, it is still a competitive solution in large optical connection demand scenarios that require a low cost.

Two-Level Cross-Talked Admission Control Mechanism for QoS Guarantee in 802.11e EDCA

This paper describes a two-level cross-talked admission control mechanism that guarantees quality of service （QoS） requirements for multimedia applications over wireless local area networks （WLANs）. An enhanced distributed channel access analytical model is used to compute the maximum number of admitted users according to the QoS requirements and the packet arrival characters. Then, some channel resources are reserved for handoff calls based on the maximum number of admitted users and the call-level traffic model. The channel utilization ratio is also measured to reflect the current system traffic load. The maximum number of admitted users and the channel utilization ratio are used for admission control for applications with QoS requirements in the call level and for rate control of best effort applications in the packet level using the p-nonacknowledgement scheme. Thus, the QoS requirements are statistically guaranteed while the system is efficiently utilized. Simulations validate the effectiveness of this mechanism to guarantee the QoS and bandwidth utilization.

A highly linear baseband G_m-C filter for WLAN application

A low voltage,highly linear transconductance-C（G_m-C） low-pass filter for wireless local area network （WLAN） transceiver application is proposed.This transmitter（Tx） filter adopts a 9.8 MHz 3rd-order Chebyshev low pass prototype and achieves 35 dB stop-band attenuation at 30 MHz frequency.By utilizing pseudo-differential linear-region MOS transconductors,the filter IIP_3 is measured to be as high as 9.5 dBm.Fabricated in a 0.35μm standard CMOS technology,the proposed filter chip occupies a 0.41×0.17 mm^2 die area and consumes 3.36 mA from a 3.3-V power supply.