POWDER Research Highlights Fall 2021

POWDER Research Highlights Fall 2021

New Research Highlights from the POWDER Platform:


Millimeter Wave (mmWave) Modeling

The optimization of millimeter wave (mmWave) networks will improve signal reach and user coverage, making these high-frequency links more viable in the commercial market. A team from Purdue University used the POWDER platform to test a 28GHz mmWave radio and produce datasets making it possible to generate new signal propagation models, beam-alignment configurations, and path-loss maps.


Bharath Keshavamurthy and Nicolo Michelusi of Arizona State University, Christopher R. Anderson of the United States Naval Academy, Yaguang Zhang, James V. Krogmeier, and David J. Love of Purdue University

28 GHz BYOD measurement campaign using a sliding correlator channel sounder implemented atop a fully-autonomous robotic antenna alignment & tracking platform:

  • The setup constituted a fixed roof-top mounted Tx and a mobile vehicle-mounted Rx traversing select routes around the University of Utah campus in Salt Lake City, UT.
  • GPS data, IMU samples, and power-delay profiles were collected for these routes – which involved both urban and suburban radio environments around the UofU campus in SLC.
  • 28 GHz propagation models, beam-alignment configurations (fully-autonomous and semi-autonomous), and path-loss maps were generated off of this collected dataset (~340 GB).
  • A conference paper outlining the design of this system is planned to be presented at the National Radio Science Meeting (NRSM) in January 2022 – along with a more detailed journal paper evaluating subsequent developments on this collected dataset.
  • Resources used: POWDER computing resources, frequency reservations, in-field assistance, and technical support.



Full-Duplex Research in a Massive MIMO (mMIMO) System

Enabling full-duplex signaling – or the ability to transmit and receive signals in the same channel simultaneously – requires an in-depth understanding of signal interference patterns. A team from Rice University has modified and applied a channel sounding tool to measure self-interference between all antennas in a massive MIMO (mMIMO) array.


RENEW Team from Rice University

One of the key research interests of our group is full-duplex communications, where a wireless device is capable of bidirectional communication in the same temporal and spectral resource block. This is made possible through a combination of passive and active self-interference cancellation. We are currently using POWDER’s massive MIMO base stations to measure the self-interference between all antennas in the array. The current setup at POWDER has allowed us to compare data from a controlled setting (i.e., inside the anechoic chamber), where we expect minimal signal reflections, against data from real-world outdoor deployments where we have little control over the environment. We have modified the RENEWLab Sounder tool to send time-orthogonal pilots from all antennas in the base station and collect from all other antennas in the same array. These modifications allow us to measure all channel pairs across the entire array to understand the impact of one radio’s transmission on a neighboring receiving radio. We have generated several HDF5 formatted files containing raw IQ samples and experiment metadata. Using the available RENEWLab Python analysis tools we can process the IQ data and estimate the different channels to evaluate various active digital cancellation strategies.



Improving Capacity of Low-Power Wide-Area Networks (LPWANs)

Low-Power Wide-Area Networks (LPWANs) typically provide wide geographic coverage, but limited throughput. A team from Florida State University is using the POWDER platform to test their own LPWAN technology – ZCNET – and evaluate its ability both to deliver higher capacity links and to support enhanced security with a new PHY layer solution.


Zhenghao Zhang and Raghav Rathi of Florida State University

We are currently working on setting up real-time experiments to evaluate ZCNET with one Access Point (AP) and multiple nodes. ZCNET is a novel Low-Power Wide-Area Network (LPWAN) technology we recently proposed that is expected to offer much higher capacity than the existing LPWAN technologies, such as LoRa, Sigfox, and RPMA. We have relied on POWDER for the experimental evaluation of ZCNET, because POWDER covers a large area with links over long distances, such as over 1 mile, and offers a much more realistic setting for the evaluation of LPWAN technologies than what we can set up by ourselves. We have evaluated the Physical (PHY) layer of ZCNET on POWDER, focusing the performance of one-to-one links, and have published our results in IEEE MASS 2020 . We are working on implementing and testing the real-time code, which will allow us to test the network-wide performance of ZCNET when multiple nodes transmit to the AP simultaneously.

We have also started exploring new directions, such as enhancing the security of LPWANs with PHY layer solutions. We submitted a proposal to the NSF RINGS program on 8/12/2021, which contains our preliminary results obtained from POWDER. To be more specific, we proposed a new secure data modulation scheme and demonstrated it with real-world transmissions between two POWDER nodes. We are planning to solve further problems discussed in our proposal and demonstrate them on POWDER.

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