In this paper, we propose a low-complexity fair scheduling algorithm for wireless multiuser MIMO communication systems in which users are multiplexed via time-, frequency-, and space-division multiple access (SDMA) schemes. In such systems, the transmission quality considerably degrades if users with spatially correlated channels are to be served at the same time and frequency. The approach presented here works with both zero-and nonzero-forcing SDMA precoding schemes by deciding, for each time and frequency slot, which users are to be served in order to maximize the precoding performance. The number of users is not a fixed parameter of the algorithm (as often assumed for other schedulers present in the literature), but it is also adjusted in accordance to the channel conditions. While smaller SDMA groups allow us to transmit with a higher average power per user, larger groups lead to higher multiplexing gains. Our algorithm ProSched is based on a novel interpretation of the precoding process using orthogonal projections which permit us to estimate the precoding results of all user combinations of interest with significantly reduced complexity. In addition, the possible user combinations are efficiently treated with the help of a tree-based sorting algorithm. The ProSched takes advantage of a perfect channel state information, when available, or, alternatively, of second-order channel statistics. The individual-user quality-of-service requirements can be considered in the decision-making process. The effectiveness of the algorithm is illustrated with simulations based on the IlmProp channel model, which features realistic correlation in space, time, and frequency.
The introduction and development of wireless sensor network technology has resulted in rapid growth within the field of structural health monitoring (SHM), as the dramatic cable costs associated with instrumentation of large civil structures is potentially alleviated. Traditionally, condition assessment of bridge structures is accomplished through the use of either vibration measurements or strain sensing. One approach is through quantifying dynamic characteristics and mode shapes developed through the use of relatively dense arrays of accelerometers. Another widely utilized method of condition assessment is bridge load rating, which is enabled through the use of strain sensors. The Wireless Sensor Solution (WSS) developed specifically for diagnostic bridge monitoring provides a hybrid system that interfaces with both accelerometers and strain sensors to facilitate vibration-based bridge evaluation as well as load rating and static analysis on a universal platform.This paper presents the development and testing of a wireless bridge monitoring system designed within the Laboratory for Intelligent Infrastructure and Transportation Technologies (LIITT) at Clarkson University. The system interfaces with low-cost MEMS accelerometers using custom signal conditioning for amplification and filtering tailored to the spectrum of typical bridge vibrations, specifically from ambient excitation. Additionally, a signal conditioning and high resolution ADC interface is provided for strain gauge sensors. To permit compensation for the influence of temperature, thermistor-based temperature sensing is also enabled. In addition to the hardware description, this paper presents features of the software applications and host interface developed for flexible, userfriendly in-network control of and acquisition from the sensor nodes. The architecture of the software radio protocol is also discussed along with results of field deployments including relatively large-scale networks and throughput rates sufficient for bridge monitoring.
Recent developments in wireless sensor technology afford the opportunity to rapidly and easily deploy large-scale, low-cost, and low-power sensor networks across relatively sizeable environmental regions. Furthermore, the advancement of increasingly smaller and less expensive wireless hardware is further complemented by the rapid development of open-source software components. These software protocols allow for interfacing with the hardware to program and configure the onboard processing and communication settings. In general, a wireless sensor network topology consists of an array of microprocessor boards, referred to as motes, which can engage in two-way communication among each other as well as with a base station that relays the mote data to a host computer. The information can then be either logged and displayed on the local host or directed to an http server for network monitoring remote from the site. A number of wireless sensor products are available that offer off-the-shelf network hardware as well as sensor solutions for environmental monitoring that are compatible with the TinyOS open-source software platform. This paper presents an introduction to wireless sensing and to the use of external antennas for increasing the antenna radiation intensity and shaping signal directivity for monitoring applications requiring larger mote-to-mote communication distances.
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