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—The Query Tree Protocol (QT) in [1] is an efficient RFID tag singulation algorithm that is guaranteed to read all the tags in the broadcast range of a reader. However, QT ignores the capture effect. That is, after the reader broadcasts a bit string query prefix, it is assumed that it can distinguish one of three responses, namely {no response, one(More)
We create a distributed storage infrastructure by embedding passive RFID tags in trees, for forest search and rescue. As a hiker moves through the forest, her reader writes a unique identifier (ID) and increasing sequence numbers (SNs) to tags, called (ID,SN) pairs. This creates a digital path for searchers to follow if the hiker is lost. Since tag memory(More)
In this paper, we propose embedding RFID tags in trees in a forest to track hikers. Hikers are equipped with RFID readers, which read from and write to tags. Specifically, as a hiker moves through the forest, his/her reader leaves his/her ID and increasing sequence numbers (SNs) in tags. This creates a digital trail that allows the hiker to backtrack(More)
Cooperative relays can provide spatial diversity and improve performance of wireless communications. In this paper, we study subcarrier power allocation at the relays for orthogonal frequency division multiplexing (OFDM)-based wireless systems. For cooperative relay with amplify-and-forward(AF) and decode-and-forward (DF) algorithms, we investigate the(More)
 Developed and taught a new graduate course entitled Spatial-Temporal Processing for Wireless Communications (ECE8823) in fall 2002: This course introduces current research results in spatial-temporal processing for wireless communication systems to improve performance and increase capacity. It includes receive antenna arrays for diversity and interference(More)
We present an enterprise-level Internet video cache and streaming system that generalizes “cache hits” to videos that are at least similar, human perception-wise. When a user requests a video not in our cache, our system starts streaming the video from the Internet, and forwards it to the user. We efficiently extract feature vectors from the(More)
—We propose a neural networks-based learning mechanism for tracking in an RFID tag field. As users move through the field to a desired destination, they train localities of tags, creating digital trails. Later on, users seeking the destination, but without knowledge of any path, can follow the digital trails. Training information (weights from the neural(More)