The Experts below are selected from a list of 243 Experts worldwide ranked by ideXlab platform

Yu Chang - One of the best experts on this subject based on the ideXlab platform.

  • Diversity analysis of orthogonal space-time modulation for distributed wireless relays
    2004 IEEE International Conference on Acoustics Speech and Signal Processing, 2004
    Co-Authors: Yu Chang
    Abstract:

    For ad hoc mobile networks, parallel wireless relays with space-time modulation have recently been discovered, and their potential to increase network capacity has been found to be significant. In this paper, we provide an analytical study of the Diversity Factor achievable by two relays with orthogonal space-time modulation. Unlike two transmitters or two receivers in the conventional MIMO setting for which the averaged bit error rate (BER) is proportional to 1/SNR/sup 2/, the averaged BER of two relays is shown to be proportional to ln(SNR)/SNR/sup 2/. This insight explains a difference between the Diversity of multiple relays and the Diversity of multiple receivers/transmitters. A switching scheme applied to two relays is also analyzed.

  • A networking perspective of mobile parallel relays
    3rd IEEE Signal Processing Education Workshop. 2004 IEEE 11th Digital Signal Processing Workshop 2004., 2004
    Co-Authors: Yu Chang
    Abstract:

    For mobile ad hoc networking, relaying is one of the most fundamental functions. The traditional relaying strategy is serial, where data packets hop from a single node to another, and the nodes neighboring a transmitting node or a receiving node are suppressed from transmission to avoid radio interference. We consider a parallel relaying strategy where neighboring nodes may act as parallel relays with space-time modulation. We demonstrate the feasibility of parallel relaying in ad hoc networks by presenting a generic route discovery algorithm for establishing routes of parallel relays. We also formulate a link layer protocol for forwarding packets through parallel relays. We then provide analytical results of packet loss rate and link delay time to highlight some of the potential benefits of parallel relays. With N parallel relays at each link, a Diversity Factor, N-squared, is achievable. A power saving of 10 dB or more is possible from serial relaying to parallel relaying.

  • Wireless antennas - making wireless communications perform like wireline communications
    2003 IEEE Topical Conference on Wireless Communication Technology, 2003
    Co-Authors: Yu Chang
    Abstract:

    We first provide an overview of some of the latest developments in wireless communications using multiple transmitters and multiple receivers. We point out the importance of SNR control in fast random fading environments. For applications where large antenna arrays are not suitable, we introduce the concept of wireless antennas or wireless relays that are distributed between a source and a destination. We propose Hurwitz-Radon space-time code for the wireless relays. Each relay receives a noisy baseband signal simultaneously from the source. The baseband signals (symbols) are not decoded into information bits at the (non-regenerative) relays, but rearranged (i.e., space-time modulated) in their orders, amplitudes and phases according to the Hurwitz-Radon code. The relays do not exchange symbols with each other, but forward the modified sequences of symbols in parallel to the destination. Our study shows that with R relays, a Diversity Factor around R/2 can be achieved, i.e., the averaged bit error rate is in the order of 1/SNR/sup R/2/ as opposed to 1/SNR for a single (regenerative) relay system. More than 10 dB power saving, from the baseline of a single relay system, is possible with eight relays. Issues such as channel estimation, symbol synchronization, medium access protocols and signal processing hardware are also discussed.

S.j. Watson - One of the best experts on this subject based on the ideXlab platform.

  • Monte Carlo simulation of residential electricity demand for forecasting maximum demand on distribution networks
    IEEE Transactions on Power Systems, 2004
    Co-Authors: D.h.o. Mcqueen, P.r. Hyland, S.j. Watson
    Abstract:

    The prevalent engineering practice (PEP) for maximum demand estimation in low-voltage (LV) electricity networks is based on an After Diversity Maximum Demand (ADMD) modified by a Diversity Factor. This method predicts the maximum likely voltage drop accounting for consumer Diversity. However, this approach does not take into account the stochastic nature of the demand and is inconsistent with international power quality standards. We present a Monte Carlo simulation model of consumer demand taking into account the statistical spread of demand in each half hour using data sampled from a gamma distribution. The parameters of the gamma distribution are based on data metered at a number of residential properties fed by one transformer. The simulated demand is corrected for temperature and total consumption. The simulated profiles at the residential properties are aggregated and the simulated maximum demand is compared with actual maximum demand at a given transformer and an entire distribution network showing good agreement in both cases.

Barry Mather - One of the best experts on this subject based on the ideXlab platform.

  • Data-Driven Distribution System Load Modeling for Quasi-Static Time-Series Simulation
    IEEE Transactions on Smart Grid, 2020
    Co-Authors: Barry Mather
    Abstract:

    This paper presents a data-driven distribution system load modeling methodology targeting quasi-static timeseries (QSTS) simulation. The proposed methodology is appropriate for modeling down to the level of the customer transformer, and it has three main features: 1) both load pattern Diversity and intra-second load variability are considered, 2) the load profiles can be populated for multiple nodes on a circuit in such a way that the Diversity Factor of the feeder can be defined and tuned, and 3) the load aggregation method can be used to populate the profiles for different nodes at various load aggregation levels. As the foundation of the modeling methodology, variability and Diversity libraries have been established based on high-resolution load data collected on customer transformers from real utility feeders. The proposed modeling methodology has been used to build load data sets for both the IEEE 123-bus feeder model and a realistic utility feeder model. The QSTS simulation results on the two evaluation feeders have demonstrated that the load data sets established from the proposed modeling methodology can effectively capture the load impact on feeder operations. For the realistic utility feeder, the effectiveness of the proposed methodology has also been validated by comparing the voltage characteristics of the feeder with modeled loads and the voltage characteristics of realistic voltage data from the same feeder.

Jasleen Kaur - One of the best experts on this subject based on the ideXlab platform.

  • client Diversity Factor in https webpage fingerprinting
    Conference on Data and Application Security and Privacy, 2019
    Co-Authors: Hasan Faik Alan, Jasleen Kaur
    Abstract:

    Webpage fingerprinting methods infer the webpages visited in a traffic trace and are serious threats to the privacy of web users. Prior work evaluates webpage fingerprinting methods using traffic samples from a single client and does not consider the client Diversity Factor---webpages can be visited using different browsers, operating systems and devices. In this paper, we study the impact of client Diversity on HTTPS webpage fingerprinting. First, we evaluate 5 prominent fingerprinting methods using traffic samples from 19 different clients. We show that the best performing methods overfit to the traffic patterns of a single client and do not generalize when they are evaluated using the samples from a different client (even if the clients use the same browser and operating system and only differ in device). Then, we investigate the traffic patterns of the clients and find differences in the HTTP messages generated, servers communicated and implementation of HTTP/2 across the clients. Finally, we show that the robustness of the methods can be increased by training them using the samples from a diverse set of clients. This study informs the community towards a realistic threat model for HTTPS webpage fingerprinting and presents an analysis of modern HTTPS traffic.

  • CODASPY - Client Diversity Factor in HTTPS Webpage Fingerprinting
    Proceedings of the Ninth ACM Conference on Data and Application Security and Privacy, 2019
    Co-Authors: Hasan Faik Alan, Jasleen Kaur
    Abstract:

    Webpage fingerprinting methods infer the webpages visited in a traffic trace and are serious threats to the privacy of web users. Prior work evaluates webpage fingerprinting methods using traffic samples from a single client and does not consider the client Diversity Factor---webpages can be visited using different browsers, operating systems and devices. In this paper, we study the impact of client Diversity on HTTPS webpage fingerprinting. First, we evaluate 5 prominent fingerprinting methods using traffic samples from 19 different clients. We show that the best performing methods overfit to the traffic patterns of a single client and do not generalize when they are evaluated using the samples from a different client (even if the clients use the same browser and operating system and only differ in device). Then, we investigate the traffic patterns of the clients and find differences in the HTTP messages generated, servers communicated and implementation of HTTP/2 across the clients. Finally, we show that the robustness of the methods can be increased by training them using the samples from a diverse set of clients. This study informs the community towards a realistic threat model for HTTPS webpage fingerprinting and presents an analysis of modern HTTPS traffic.

Jinjin Li - One of the best experts on this subject based on the ideXlab platform.

  • Intuitionistic Fuzzy Rough Set-Based Granular Structures and Attribute Subset Selection
    IEEE Transactions on Fuzzy Systems, 2019
    Co-Authors: Wei-zhi Wu, Yuhua Qian, Jiye Liang, Jinkun Chen, Jinjin Li
    Abstract:

    Attribute subset selection is an important issue in data mining and information processing. However, most automatic methodologies consider only the relevance Factor between samples while ignoring the Diversity Factor. This may not allow the utilization value of hidden information to be exploited. For this reason, we propose a hybrid model named intuitionistic fuzzy (IF) rough set to overcome this limitation. The model combines the technical advantages of rough set and IF set and can effectively consider the above-mentioned statistical Factors. First, fuzzy information granules based on IF relations are defined and used to characterize the hierarchical structures of the lower and upper approximations of IF rough set within the framework of granular computing. Then, the computation of IF rough approximations and knowledge reduction in IF information systems are investigated. Third, based on the approximations of IF rough set, significance measures are developed to evaluate the approximation quality and classification ability of IF relations. Furthermore, a forward heuristic algorithm for finding one optimal reduct of IF information systems is developed using these measures. Finally, numerical experiments are conducted on public datasets to examine the effectiveness and efficiency of the proposed algorithm in terms of the number of selected attributes, computational time, and classification accuracy.