Telcordia designed and implemented a new Fractional Frequency Reuse (FFR) algorithm for LTE inter-cell interference coordination that could improve network performance by 3-8 times over Single Frequency Reuse.

A cognitive technique was developed that can predict proximity to congestive transition for networks, so that steps can be taken to throttle future traffic to avoid the congestion state.

Telcordia designed an optically integrated solid-state deterministic single photon source and identification of a material platform for its construction, a critical component for operation of a viable quantum computer.

A novel approach was created to capture experts’ knowledge for problem diagnosis in the form of the Extensible Bayesian Inference Tool that allows easy capture of expert knowledge into a Bayesian network model via a simple question and answer dialogue.

Telcordia established an integrated wireless-optical network laboratory that allows development of simulation and modeling tools to address customer-defined challenges. For example, it can help identify optical and wireless architecture trade-offs and analyze technology choices.

Two techniques were developed for improving Multiple Input Multiple Output (MIMO) communications in a high-speed vehicular roadway environment. The higher throughput achieved would result in the ability to provide data-intensive services like streaming movies to moving vehicle.

Telcordia created hybrid end-to-end system level analysis models for packet-level analyses of end-to-end system involving LTE Femtocells, Macrocells, DSL and Cellular Backhaul, using “efficient” discrete event simulation techniques to provide end-to-end loss and delay (QoS/SLA) information.

This effort involved construction of a mechanism to alleviate information overload for active and casual end-users through use of filter augmentation to support serendipitous information access. This mechanism has the potential to significantly improve filter effectiveness and adoption.

Telcordia Implemented a Java MIDLet-based prototype of MediAlly, a mobile healthcare services platform, which (a) uses a combination of local and cloud data sources to infer an individual’s context and (b) provides an extensible, graph-based, low-overhead mechanism to store and reconstruct the provenance of such contextual history. This could be a key enabling technology for supporting low-overhead, long-term remote monitoring of medical sensor streams via a mobile phone.

This project involved creation of a general-purpose toolkit of fast algorithms and methodologies for multiscale analysis of large, high-dimensional, multi-modal data sets that enables information representation, data fusion, profiling, real-time event detection, constant time search, realistic synthesis, missing data approximation and visualization. This toolkit provides an order of magnitude improvement in computational complexity over existing methods.

Telcordia developed a unified QoS ontology for mission critical applications, which was assembled and harmonized from a number of studies that explored QoS from specific perspectives. The QoS attributes establish the system’s end-to-end Service Level Agreement, and in an automated design environment provide the parameters that drive the design and configuration decisions.