AT&T Labs

About: AT&T Labs is a based out in . It is known for research contribution in the topics: Network packet & The Internet. The organization has 1879 authors who have published 5595 publications receiving 483151 citations.

WiFi: what's next?

Abstract: WiFi, also known as 802.11b, has become the preferred technology for wireless local area networking in both business and home environments. Even though it was designed primarily for private applications, WiFi is also being deployed in public places to create so-called hotspots, where WiFi-capable users can obtain broadband Internet access. This new domain of application could be the major future market opportunity for WiFi, but in order to take advantage of it, several key challenges, both technical and business-related, must be overcome. We outline these challenges and discuss approaches to solutions.

Squashing flat files flatter

Abstract: A feature of data mining that distinguishes it from “classical” machine learning (ML) and statistical modeling (SM) is scale. The community seems to agree on this yet progress to this point has been limited. We present a methodology that addresses scale in a novel fashion that has the potential for revolutionizing the field. While the methodology applies most directly to flat (row by column) data sets we believe that it can be adapted to other representations. Our approach to the problem is not to scale up individual ML and SM methods. Rather we prefer to leverage the entire collection of existing methods by scaling down the data set. We call the method squashing. Our method demonstrably outperforms random sampling and a theoretical argument suggests how and why it works well. Squashing consists of three modular steps: grouping, momentizing, and generating (GMG). These three steps describe the squashing pipeline whereby the original (very large data set) is sectioned off into mutually exclusive groups (or bins); within each group a series of low-order moments are computed; and finally these moments are passed off to a routine that generates pseudo data that accurately reproduce the moments. The result of the GMG squashing pipeline is a squashed data set that has the same structure as the original data with the addition of a weight for each pseudo data point that reflects the distribution of the original data into the initial groups. Any ML or SM method that accepts weights can be used to analyze the weighted pseudo data. By construction the resulting analyses will mimic the corresponding analyses on the original data set. Squashing should appeal to many of the sub-disciplines of

A high-resolution technique for multidimensional NMR spectroscopy

Abstract: A scheme for estimating frequencies and damping factors of multidimensional nuclear magnetic resonance (NMR) data is presented-multidimensional NMR data can be modeled as the sum of several multidimensional damped sinusoids. The estimated frequencies and damping factors of multidimensional NMR data play important roles in determining protein structures. The authors present a high-resolution subspace method for estimating the parameters of NMR data, Unlike other methods, this algorithm makes full use of the rank-deficiency and Hankel properties of the prediction matrix composed of NMR data. Hence, it can estimate the signal parameters under low signal-to-noise ratio (SNR) by using a few data points. The effectiveness of the new algorithm is confirmed by computer simulations and it is tested by experimental data.

Ultra-High-Capacity DWDM transmission system for 100G and beyond

Abstract: We review and summarize several 100G per channel high-capacity transmission systems enabled by advanced technologies such as multilevel modulation format, new low-loss and large effective area fiber, hybrid EDFA/Raman amplification, and digital coherent detection technologies. We show that high-speed QPSK, 8PSK, 8QAM, and 16QAM can all be generated using commercially available optical modulators using only binary electrical drive signals through novel synthesis methods, and that all of these modulation formats can be detected using digital coherent detection. We also show our latest research results on 400 Gb/s and 1 Tb/s per channel by using orthogonal DWDM transmission technologies.

Fast and scalable wireless handoffs in supports of mobile Internet audio

Abstract: Future internetworks will include large numbers of portable devices moving among small wireless cells. We propose a hierarchical mobility management scheme for such networks. Our scheme exploits locality in user mobility to restrict handoff processing to the vicinity of a mobile node. It thus reduces handoff latency and the load on the internetwork. Our design is based on the Internet Protocol (IP) and is compatible with the Mobile IP standard. We also present experimental results for the lowest level of the hierarchy. We implemented our local handoff mechanism on Unix-based portable computers and base stations, and evaluated its performance on a WaveLAN network. These experiments show that our handoffs are fast enough to avoid noticeable disruptions in interactive audio traffic. For example, our handoff protocol completes less than 10 milliseconds after a mobile node initiates it. Our mechanism also recovers from packet losses suffered during the transition from one cell to another. This work helps extend Internet telephony and teleconferencing to mobile devices that communicate over wireless networks.