Grant Huang

Facilitating Remote Laboratory Deployments Using a Relay Gateway Server Architecture

Hands-on experiments prepare students to deal with real-world problems and help to efficiently digest theoretical concepts and relate those to practical tasks. However, shortage of equipment, high costs, and the lack of human resources for laboratory maintenance and assistance decrease the implementation capacity of the hands-on training laboratories. At the same time, the Internet has become a common networking medium and is increasingly used to enhance education and training. In addition, experimental equipment at many sites is typically underutilized. Thus, remote laboratories accessible through the Internet can resolve cost and access constraints as they can be used at flexible times and from various locations. While many solutions have been proposed so far, this paper addresses an important issue of facilitating remote lab deployments by providing remote connectivity services to lab providers using a Relay Gateway Server architecture. A proof-of-concept solution is described which also includes other previously reported useful features. The system has been tested in engineering labs and student assessment is provided.

Measurement and Characterization of Channel Delays for Broadband Power Line Communications

Power Line Communications (PLC) emerged as a competitive technology for indoor broadband communications. It exploits the existing power line infrastructure for data transmissions. Transmission delays may essentially degrade the performance of applications relying on two-way communications such as videoconferencing, remote control systems, online games, and so on. Reported PLC channel models indirectly characterize signal propagation delays through channel transfer functions or impulse responses, but they do not address more important delays occurring because of multiple retransmissions of lost data packets in noisy PLC channels. This paper proposes a cost-efficient data delay measurement and a high-level statistical modeling approach for applications that are sensitive to data delays. Hybrid statistical distributions are explored for accurate delay characterization.

Measurement and Modeling of Network Delays for MS-Based A-GPS Assistance Delivery

While conventional global positioning system (GPS) receivers have gained popularity for applications in open-sky environments, their performance degrades in challenging conditions, such as urban canyons and indoors. The assisted GPS (A-GPS) concept enhanced receiver capability to operate in weak signal conditions using terrestrial links to communicate helpful information such as satellite orbital parameters, coarse estimates of time and location, and so forth. The A-GPS mode has been standardized for many wireless networks and is integrated in high-end simulators to support development and testing efforts. As the terrestrial-assistance data channel becomes an important link for the receiver, the statistical modeling of information delivery delays should be addressed to simulate more adequate operation scenarios. This paper addresses this aspect by presenting a delay measurement and modeling approach for Mobile Station Based assistance data. Even though the approach can be applied to other measurement setups, this paper is presented for standardized secure user plane location architecture that exploits data channels of wireless networks to deliver assistance data. Measurement data are collected and modeled for various scenarios of relative deployment of assistance servers and receivers. Delays are modeled for LAN, WLAN, third-generation mobile telecommunication, high-speed downlink packet access, and fourth-generation long-term evolution networks, with the transmission control protocol and the Internet protocol connection between a server and receiver.

Network delay modeling for assisted GPS

Currently, conventional Global Positioning System (GPS) receivers work well in open-sky environments. However, location finding in weak-signal conditions, such as urban canyons and indoors, is challenging and has been the subject of extensive research. Assisted GPS (A-GPS) is one of the concepts that helps receivers acquire weak signals by receiving assistance data from wireless networks, such as orbital parameters, and coarse time and location references. A-GPS also improves time-to-first-fix (TTFF) through faster delivery of information that is recovered from navigation data broadcast by GPS satellites. Receiver technology developers rely on signal simulators for testing real-world scenarios. While A-GPS support has been integrated in many simulators, probabilistic models of delays occurring during assistance data delivery have not been studied properly. This paper provides a methodology of A-GPS network delay modeling that is applicable to various simulation environments. Particularly, a testbed is designed to collect delay data, model them statistically and integrate the model in a simulator. The testbed employs secure user plane location (SUPL) architecture in two modes, mobile station (MS) based (MS-based) and MS-assisted, where data channels are used to communicate A-GPS assistance data.Measurement campaigns are conducted and network delay models are derived for various representative distances between assistance servers and receivers, and for various networks that users connect to, such as LAN, WLAN, third-generation mobile telecommunication (3G), high-speed downlink packet access (HSDPA), and fourth-generation long term evolution (4G LTE), with the Transmission Control Protocol and the Internet Protocol (TCP/IP) connection between a server and a receiver.

A land mobile channel modeling in LabVIEW

This paper presents a case study implementation of a fading channel model for a recently introduced Global Positioning System (GPS) simulator from National Instruments. Existing models are discussed and implementation aspects are presented for a model which combines statistical properties of different multipath channels. The NIs GPS simulator is implemented in an open development environment, LabVIEW, which allows an incorporation of user-defined models. Computational optimization issues are also discussed.