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Signal Processing Commons

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Full-Text Articles in Signal Processing

Path Loss In An Urban Peer-To-Peer Channel For Six Public-Safety Frequency Bands, David W. Matolak, Qian Zhang, Qiong Wu Jun 2013

Path Loss In An Urban Peer-To-Peer Channel For Six Public-Safety Frequency Bands, David W. Matolak, Qian Zhang, Qiong Wu

Faculty Publications

We provide path loss data and models for a peer-to-peer wireless channel for an urban environment in six public safety bands, for simultaneous transmission to five spatially separated receiving sites. Results are from measurements in Denver, Colorado. The six frequencies at which we measured are (in MHz) 430, 750, 905, 1834, 2400, and 4860. Both line-of-sight and non-line-of-sight conditions were covered, and we quantify path loss exponents and linear-fit standard deviations as functions of frequency and location. Line-of-sight results agree with prior work, but non-line-of-sight exponents, from 3.6-7.3, are generally larger than in most other references.


Reverberation-Chamber Test Environment For Outdoor Urban Wireless Propagation Studies, Helge Fielitz, Kate A. Remley, Christopher L. Holloway, Qian Zhang, Qiong Wu, David W. Matolak Mar 2010

Reverberation-Chamber Test Environment For Outdoor Urban Wireless Propagation Studies, Helge Fielitz, Kate A. Remley, Christopher L. Holloway, Qian Zhang, Qiong Wu, David W. Matolak

Faculty Publications

We introduce a test environment to replicate the well-known clustering of reflections in power delay profiles arising from late-time delays and reflections. Urban wireless propagation environments are known to exhibit such clustering. The test setup combines discrete reflections generated by a fading simulator with the continuous distribution of reflections created in a reverberation chamber. We describe measurements made in an urban environment in Denver, CO, that illustrate these multiple distributions of reflections. Our comparison of measurements made in the urban environment to those made in the new test environment shows good agreement.


Detection For A Statistically-Known, Time-Varying Dispersive Channel, David W. Matolak, S. G. Wilson Dec 1996

Detection For A Statistically-Known, Time-Varying Dispersive Channel, David W. Matolak, S. G. Wilson

Faculty Publications

Detection for the statistically known channel (SKC) is aimed at obtaining good performance in situations where our statistical knowledge of a time-varying channel is good, and where other equalization/detection schemes are either too complex to implement, or their performance is limited due to the rapidity of channel fading, or where we are simply unable to perform channel estimation. By using a statistical characterization of the channel, we develop a new detector that performs maximum-likelihood sequence estimation (MLSE) (given the channel model) on blocks of N symbols. Both symbol-spaced and fractionally spaced samples are used, to obtain two different detectors, that …