Hughes Network Systems, LLC

Ying Wang

Rajeev Kubba

Shivaram Sitaram

Emanuel Harrington

Frank Li

Junyu Gong

A system and method for identifying devices with WiFi connection incompatibility are described. Data related to connectivity for at least one customer premise equipment (CPE) connected to each terminal in a satellite network is collected in order to generate a set of metrics associated with each of the at least CPE using the collected data. A first set of results indicative of network incompatibility is determined for each of the CPEs. Next, a second set of results indicative of network incompatibility is determined for each CPE using at least one machine learning algorithm. Information indicative of network incompatibility is subsequently generated for each CPE based on the first set of results and the second set of results.

WiFi device compatibility analyzer for satellite networks

An apparatus and method for optimizing selection of data cap limited service plans. A model is created in order to predict bandwidth usage by existing subscribers in a satellite communication system. The model is trained with usage data for all subscribers of the satellite communication system over a predetermined time interval, and used to analyze usage patterns of each subscriber. Bandwidth usage is predicted for each subscriber relative to an existing service plan based, at least one recommendation is generated for optimizing use of bandwidth in the satellite communication system based on the analysis and predicted bandwidth usage.

Optimizing data cap limited service plans

An apparatus and method for data cap management of users exceeding or violating bandwidth policies in a communication system. A model is created for identifying super heavy users, and trained usage data for all current users of the communication system for a predetermined time interval. Usage patterns of each user are analyzed over a second duration using the trained model in order to identify current super heavy users based, at least in part, on the analysis. Traffic flow control restrictions are then applied to some or all of the traffic associated with identified super heavy users.

Data cap management of super heavy users based on monthly usage and service plan limits

Embodiments for a method and apparatus are described for non-linear noise cancelation and in phase quadrature (I/Q) modulation error correction. The embodiments include receiving a signal, the signal including a plurality of data segments. A first data segment in the received signal is demodulated and decoded to produce a recovered segment of a bitstream. At least one correction factor is applied to a first demodulation support element and a second demodulation support element during demodulation of a second data segment in the received signal. The correction factor is determined based on the received first data segment and a representation of the first data segment reconstructed from the recovered segment of the bitstream.

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Germantown, MD, United States of America

Ying Wang