A Low Complexity 16QAM Based on Geometric Shaping for Fiber Optics Transmission System

A robust and low complexity adaptive algorithm for mimo eigenmode transmission system with experimental validation

IEEE Transactions on Wireless Communications ◽

10.1109/twc.2006.1673089 ◽

2006 ◽

Vol 5 (7) ◽

pp. 1775-1784 ◽

Cited By ~ 17

Author(s):

See Ho Ting ◽

K. Sakaguchi ◽

K. Araki

Keyword(s):

Adaptive Algorithm ◽

Experimental Validation ◽

Low Complexity ◽

Transmission System

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Season Cycling Gas Storage in Stogit Fields. A Real-Time Data Transmission System

10.2118/205206-ms ◽

2021 ◽

Author(s):

Graciela Eva Naveda ◽

France Dominique Louie ◽

Corinna Locatelli ◽

Julien Davard ◽

Sara Fragassi ◽

...

Keyword(s):

Natural Gas ◽

Real Time ◽

Fiber Optics ◽

Data Transmission ◽

Distribution Networks ◽

Gas Storage ◽

Transmission System ◽

Lessons Learned ◽

Time Data ◽

Real Time Data

Abstract Natural gas has become one of the major sources of energy for homes, public buildings and businesses, therefore gas storage is particularly important to ensure continuous provision compensating the differences between supply and demand. Stogit, part of Snam group, has been carrying out gas storage activities since early 1960's. Natural gas is usually stored underground, in large storage reservoirs. The gas is injected into the porous rock of depleted reservoirs bringing the reservoir nearby to its original condition. Injected gas can be withdrawn depending on the need. Gas market demands for industries and homes in Italy are mostly guaranteed from those Stogit reservoirs even in periods when imports are in crisis. Typically, from April to October, the gas is injected in these natural reservoirs that are "geologically tested"; while from November to March, gas is extracted from the same reservoirs and pumped into the distribution networks to meet the higher consumer demand. Thirty-eight (38) wells, across nine (9) depleted fields, are completed with downhole quartz gauges and some of them with fiber-optics gauges. Downhole gauges are installed to continuously measure and record temperature and pressure from multiple reservoirs. The Real Time data system installed for 29 wells is used to collect, transmit and make available downhole data to Stogit (Snam) headquarter office. Data is automatically collected from remote terminal units (RTUs) and transferred over Stogit (Snam) network. The entire system works autonomously and has the capability of being remotely managed from anywhere over the corporate Stogit (Snam) IT network. Historical trends, including fiber optics gauges ones, are visualized and data sets could be retrieved using a fast and user-friendly software that enables data import into interpretation and reservoir modeling software. The use of this data collection and transmission system, versus the traditional manual download, brought timely data delivery to multiple users, coupled with improved personnel safety since land travels were eliminated. The following pages describe the case study, lessons learned, and integrated new practices used to improve the current and future data transmission deployments.

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Enhanced access and visualization of fiber-optics data using a simple transmission system

2015 International Field Exploration and Development Conference (IFEDC 2015) ◽

10.1049/cp.2015.0586 ◽

2015 ◽

Author(s):

J.L. Serrano Acevedo ◽

E.G.E. Naveda ◽

A. Azancot ◽

P. Maguet ◽

F.D. Louie ◽

...

Keyword(s):

Fiber Optics ◽

Transmission System

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Power Allocation Algorithm for an Energy-Harvesting Wireless Transmission System Considering Energy Losses

Algorithms ◽

10.3390/a12010025 ◽

2019 ◽

Vol 12 (1) ◽

pp. 25

Author(s):

Su Zhao ◽

Gang Huang ◽

Qi Zhu

Keyword(s):

Energy Harvesting ◽

Power Allocation ◽

Online Algorithm ◽

Optimization Methods ◽

Low Complexity ◽

Transmission System ◽

Wireless Transmission ◽

Energy Losses ◽

Average Throughput ◽

Allocation Algorithm

For an energy-harvesting wireless transmission system, considering that a transmitter which can harvest energy from nature has two kinds of extra energy consumption, circuit consumption and storage losses, the optimization models are set up in this paper for the purpose of maximizing the average throughput of the system within a certain period of time for both a time-invariant channel and time-varying channel. Convex optimization methods such as the Lagrange multiplier method and the KKT (Karush–Kuhn–Tucker) condition are used to solve the optimization problem; then, an optimal offline power allocation algorithm which has a three-threshold structure is proposed. In the three-threshold algorithm, two thresholds can be achieved by using a linear search method while the third threshold is calculated according to the channel state information and energy losses; then, the offline power allocation is based on the three thresholds and energy arrivals. Furthermore, inspired by the optimal offline algorithm, a low-complexity online algorithm with adaptive thresholds is derived. Finally, the simulation results show that the offline power allocation algorithms proposed in this paper are better than other algorithms, the performance of the online algorithm proposed is close to the offline one, and these algorithms can help improve the average throughput of the system.

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