Multiple user pair scheduling in bi-directional single relay assisted FSO systems

2014 ◽  
Author(s):  
Parul Puri ◽  
Parul Garg ◽  
Mona Aggarwal ◽  
Prabhat Kumar Sharma
Keyword(s):  
Multiple User ◽  
Single Relay

scholarly journals A Deep Learning-Assisted Cooperative Diversity Method under Channel Aging

2020 ◽  
Author(s):  
Wei Jiang
Keyword(s):  
Deep Learning ◽  
Relay Selection ◽  
Carrier Frequency Offset ◽  
Cooperative Diversity ◽  
Channel State ◽  
Timing Offset ◽  
Multiple User ◽  
Spatially Distributed ◽  
Efficient Scheme ◽  
Single Relay

Single-relay selection is a simple but efficient scheme for cooperative diversity among multiple user devices. However, the wrong selection of the best relay due to aged channel state information (CSI) remarkably degrades its performance, overwhelming this cooperative gain. Multi-relay selection is robust against channel aging but multiple timing offset (MTO) and multiple carrier frequency offset (MCFO) among spatially-distributed relays hinder its implementation in practical systems. In this paper, therefore, we propose a deep learning-based cooperative diversity method coined predictive relay selection (PRS) that chooses a single relay with the largest predicted CSI, which can alleviate the effect of channel aging while avoiding MTO and MCFO. Performance is evaluated analytically and numerically, revealing that PRS clearly outperforms the existing schemes with a negligible complexity burden.

scholarly journals A Deep Learning-Assisted Cooperative Diversity Method under Channel Aging

2020 ◽  
Author(s):  
Wei Jiang
Keyword(s):  
Deep Learning ◽  
Relay Selection ◽  
Carrier Frequency Offset ◽  
Cooperative Diversity ◽  
Channel State ◽  
Timing Offset ◽  
Multiple User ◽  
Spatially Distributed ◽  
Efficient Scheme ◽  
Single Relay

Single-relay selection is a simple but efficient scheme for cooperative diversity among multiple user devices. However, the wrong selection of the best relay due to aged channel state information (CSI) remarkably degrades its performance, overwhelming this cooperative gain. Multi-relay selection is robust against channel aging but multiple timing offset (MTO) and multiple carrier frequency offset (MCFO) among spatially-distributed relays hinder its implementation in practical systems. In this paper, therefore, we propose a deep learning-based cooperative diversity method coined predictive relay selection (PRS) that chooses a single relay with the largest predicted CSI, which can alleviate the effect of channel aging while avoiding MTO and MCFO. Performance is evaluated analytically and numerically, revealing that PRS clearly outperforms the existing schemes with a negligible complexity burden.

Plug-in scripts for EFTEM automation

1996 ◽  
Vol 54 ◽  
pp. 546-547
Author(s):  
N. D. Evans ◽  
M. K. Kundmann
Keyword(s):  
Electron Microscopy ◽  
National Laboratory ◽  
Oak Ridge ◽  
Multiple User ◽  
Transmission Electron ◽  
Short Period ◽  
User Facility ◽  
Instrument Control ◽  
And Control ◽  
Research Equipment

Post-column energy-filtered transmission electron microscopy (EFTEM) is inherently challenging as it requires the researcher to setup, align, and control both the microscope and the energy-filter. The software behind an EFTEM system is therefore critical to efficient, day-to-day application of this technique. This is particularly the case in a multiple-user environment such as at the Shared Research Equipment (SHaRE) User Facility at Oak Ridge National Laboratory. Here, visiting researchers, who may oe unfamiliar with the details of EFTEM, need to accomplish as much as possible in a relatively short period of time.We describe here our work in extending the base software of a commercially available EFTEM system in order to automate and streamline particular EFTEM tasks. The EFTEM system used is a Philips CM30 fitted with a Gatan Imaging Filter (GIF). The base software supplied with this system consists primarily of two Macintosh programs and a collection of add-ons (plug-ins) which provide instrument control, imaging, and data analysis facilities needed to perform EFTEM.

Serial thin sectioning for pre- and post-embedding immunohistochemistry: Achieving consistent and reliable results for a 3-D reconstruction

1993 ◽  
Vol 51 ◽  
pp. 328-329
Author(s):  
Antonia M. Milroy
Keyword(s):  
Nervous System ◽  
Computer Assisted ◽  
Serial Sectioning ◽  
Electron Microscopic ◽  
High Quality ◽  
New Techniques ◽  
3 Dimensional ◽  
Multiple User ◽  
Thin Sectioning ◽  
Subcellular Level

In recent years many new techniques and instruments for 3-Dimensional visualization of electron microscopic images have become available. Higher accelerating voltage through thicker sections, photographed at a tilt for stereo viewing, or the use of confocal microscopy, help to analyze biological material without the necessity of serial sectioning. However, when determining the presence of neurotransmitter receptors or biochemical substances present within the nervous system, the need for good serial sectioning (Fig. 1+2) remains. The advent of computer assisted reconstruction and the possibility of feeding information from the specimen viewing chamber directly into a computer via a camera mounted on the electron microscope column, facilitates serial analysis. Detailed information observed at the subcellular level is more precise and extensive and the complexities of interactions within the nervous system can be further elucidated.We emphasize that serial ultra thin sectioning can be performed routinely and consistently in multiple user electron microscopy laboratories. Initial tissue fixation and embedding must be of high quality.

Performance Enhancement of Encoding–Decoding Multidiagonal and Walsh Hadamard Codes for Spectral Amplitude Coding-Optical Code Division Multiple Access (SAC-OCDMA) Utilizing Dispersion Compensated Fiber

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Majidah H. Majeed ◽  
Riyadh Khlf Ahmed
Keyword(s):  
Multiple Access ◽  
Performance Enhancement ◽  
Optical Network ◽  
Spectral Amplitude ◽  
Q Factor ◽  
Data Traffic ◽  
Eye Diagram ◽  
Multiple User ◽  
Spectral Amplitude Coding ◽  
Code Division Multiple

AbstractSpectral Amplitude Coding-Optical Codes Division Multiple Access (SAC-OCDMA) is a future multiplexing technique that witnessed a dramatic attraction for eliminating the problems of the internet in optical network field such as multiple-user access and speed’s growth of the files or data traffic. In this research article, the performance of SAC-OCDMA system based on two encoding–decoding multidiagonal (MD) and Walsh Hadamard (WH) codes is enhanced utilizing three different schemes of dispersion compensating fiber (DCF): pre-, post- and symmetrical compensation. The system is simulated using Optisystem version 7.0 and Optigrating version 4.2. The performance of the proposed system is specified in terms of bit error rate (BER), Q-factor and eye diagram. It has been observed that the compensated system based on MD code is performs much better compared to the system based on WH code. On the other hand, the compensated SAC-OCDMA system with symmetrical DCF has the lowest values of BER and largest values of Q-factor, so it is considered the best simulated scheme contrasted with pre- and post-DCF.

scholarly journals Optimal Multi-Antenna Transmission for the Cooperative Non-Orthogonal Multiple-Access System

2021 ◽  
Vol 11 (5) ◽  
pp. 2203
Author(s):  
Duckdong Hwang ◽  
Janghoon Yang ◽  
Sung Sik Nam ◽  
Hyoung-Kyu Song
Keyword(s):  
Interference Cancellation ◽  
Multiple Access ◽  
Average Power ◽  
Access Point ◽  
Power Performance ◽  
Multiple User ◽  
Structure Simulation ◽  
Rank One ◽  
Multiple Access System ◽  
Optimal Beamforming

We investigate the beamforming for the multi antenna cooperative non-orthogonal multiple access (NOMA) system, where an access point (AP) delivers messages for multiple user terminals (UT) with successive interference cancellation (SIC) reception method. Some UTs with multiple antennas cooperate with the AP transmission to improve the diversity and the average power performance. We formally present two optimal beamforming schemes at the AP and at the cooperative UTs. One scheme has no power limitation for the cooperative UTs, while the other one does have such limitation. We guarantee that the rank one beamformer is sufficient to achieve the optimal points so that the proposed schemes have rank one semi-definite programming (SDP) structure. Simulation results show the performance gain of the multi-antenna cooperative NOMA schemes in the sense of diversity and the average power.

scholarly journals The State of Speech in HCI: Trends, Themes and Challenges

2019 ◽  
Vol 31 (4) ◽  
pp. 349-371 ◽  
Author(s):  
Leigh Clark ◽  
Philip Doyle ◽  
Diego Garaialde ◽  
Emer Gilmartin ◽  
Stephan Schlögl ◽  
...  
Keyword(s):  
Speech Production ◽  
Thematic Analysis ◽  
Design Work ◽  
Wizard Of Oz ◽  
Speech Interfaces ◽  
Interface Interaction ◽  
Multiple User ◽  
Speech Interface ◽  
User Attitudes ◽  
In The Wild

AbstractSpeech interfaces are growing in popularity. Through a review of 99 research papers this work maps the trends, themes, findings and methods of empirical research on speech interfaces in the field of human–computer interaction (HCI). We find that studies are usability/theory-focused or explore wider system experiences, evaluating Wizard of Oz, prototypes or developed systems. Measuring task and interaction was common, as was using self-report questionnaires to measure concepts like usability and user attitudes. A thematic analysis of the research found that speech HCI work focuses on nine key topics: system speech production, design insight, modality comparison, experiences with interactive voice response systems, assistive technology and accessibility, user speech production, using speech technology for development, peoples’ experiences with intelligent personal assistants and how user memory affects speech interface interaction. From these insights we identify gaps and challenges in speech research, notably taking into account technological advancements, the need to develop theories of speech interface interaction, grow critical mass in this domain, increase design work and expand research from single to multiple user interaction contexts so as to reflect current use contexts. We also highlight the need to improve measure reliability, validity and consistency, in the wild deployment and reduce barriers to building fully functional speech interfaces for research.RESEARCH HIGHLIGHTSMost papers focused on usability/theory-based or wider system experience research with a focus on Wizard of Oz and developed systems Questionnaires on usability and user attitudes often used but few were reliable or validated Thematic analysis showed nine primary research topics Challenges identified in theoretical approaches and design guidelines, engaging with technological advances, multiple user and in the wild contexts, critical research mass and barriers to building speech interfaces

EdgeDIPN

2020 ◽  
Vol 14 (3) ◽  
pp. 320-328
Author(s):  
Long Guo ◽  
Lifeng Hua ◽  
Rongfei Jia ◽  
Fei Fang ◽  
Binqiang Zhao ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Attention Mechanism ◽  
Data Sources ◽  
User Intent ◽  
Multiple User ◽  
Shopping Experience ◽  
Data Source ◽  
Intent Prediction ◽  
The Right

With the rapid growth of e-commerce in recent years, e-commerce platforms are becoming a primary place for people to find, compare and ultimately purchase products. To improve online shopping experience for consumers and increase sales for sellers, it is important to understand user intent accurately and be notified of its change timely. In this way, the right information could be offered to the right person at the right time. To achieve this goal, we propose a unified deep intent prediction network, named EdgeDIPN, which is deployed at the edge, i.e., mobile device, and able to monitor multiple user intent with different granularity simultaneously in real-time. We propose to train EdgeDIPN with multi-task learning, by which EdgeDIPN can share representations between different tasks for better performance and saving edge resources in the meantime. In particular, we propose a novel task-specific attention mechanism which enables different tasks to pick out the most relevant features from different data sources. To extract the shared representations more effectively, we utilize two kinds of attention mechanisms, where the multi-level attention mechanism tries to identify the important actions within each data source and the inter-view attention mechanism learns the interactions between different data sources. In the experiments conducted on a large-scale industrial dataset, EdgeDIPN significantly outperforms the baseline solutions. Moreover, EdgeDIPN has been deployed in the operational system of Alibaba. Online A/B testing results in several business scenarios reveal the potential of monitoring user intent in real-time. To the best of our knowledge, EdgeDIPN is the first full-fledged real-time user intent understanding center deployed at the edge and serving hundreds of millions of users in a large-scale e-commerce platform.

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