scholarly journals Reducing dynamic power consumption in next generation DS-CDMA mobile communication receivers

2004 ◽  
Author(s):  
Vikram Chandrasekhar ◽  
F. Livingston ◽  
J. Cavallaro
Keyword(s):  
Power Consumption ◽  
Mobile Communication ◽  
Next Generation ◽  
Dynamic Power

scholarly journals Towards an Efficient CNN Inference Architecture Enabling In-Sensor Processing

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1955
Author(s):  
Md Jubaer Hossain Pantho ◽  
Pankaj Bhowmik ◽  
Christophe Bobda
Keyword(s):  
Power Consumption ◽  
High Speed ◽  
Image Sensor ◽  
Machine Learning Algorithms ◽  
Hierarchical Optimization ◽  
Computation Method ◽  
Optimization Approach ◽  
Efficient Computation ◽  
Feature Maps ◽  
Dynamic Power

The astounding development of optical sensing imaging technology, coupled with the impressive improvements in machine learning algorithms, has increased our ability to understand and extract information from scenic events. In most cases, Convolution neural networks (CNNs) are largely adopted to infer knowledge due to their surprising success in automation, surveillance, and many other application domains. However, the convolution operations’ overwhelming computation demand has somewhat limited their use in remote sensing edge devices. In these platforms, real-time processing remains a challenging task due to the tight constraints on resources and power. Here, the transfer and processing of non-relevant image pixels act as a bottleneck on the entire system. It is possible to overcome this bottleneck by exploiting the high bandwidth available at the sensor interface by designing a CNN inference architecture near the sensor. This paper presents an attention-based pixel processing architecture to facilitate the CNN inference near the image sensor. We propose an efficient computation method to reduce the dynamic power by decreasing the overall computation of the convolution operations. The proposed method reduces redundancies by using a hierarchical optimization approach. The approach minimizes power consumption for convolution operations by exploiting the Spatio-temporal redundancies found in the incoming feature maps and performs computations only on selected regions based on their relevance score. The proposed design addresses problems related to the mapping of computations onto an array of processing elements (PEs) and introduces a suitable network structure for communication. The PEs are highly optimized to provide low latency and power for CNN applications. While designing the model, we exploit the concepts of biological vision systems to reduce computation and energy. We prototype the model in a Virtex UltraScale+ FPGA and implement it in Application Specific Integrated Circuit (ASIC) using the TSMC 90nm technology library. The results suggest that the proposed architecture significantly reduces dynamic power consumption and achieves high-speed up surpassing existing embedded processors’ computational capabilities.

A review on mmWave based energy efficient RoF system for next generation mobile communication and broadband systems

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Parvin Kumar ◽  
Sanjay Kumar Sharma ◽  
Shelly Singla ◽  
Varun Gupta ◽  
Abhishek Sharma
Keyword(s):  
Wireless Communication ◽  
Optical Fiber ◽  
Millimeter Wave ◽  
Mobile Communication ◽  
Energy Efficient ◽  
Mobile Station ◽  
Base Station ◽  
Electrical Signal ◽  
Next Generation ◽  
Efficient System

Abstract In today’s scenario, wireless communication is turning into a decisive and leading backbone to access the worldwide network. Therefore, the usage of mobile phones and broadband is rising staggeringly. To satisfy their expulsive needs, it demands increment in data rates while providing higher bandwidth and utilizing optical fiber in wireless communication, and this becomes a worldwide analysis area. Radio over fiber (RoF) system is taken into account as best solution to fulfill these needs. In RoF system, the radio frequency signal operated at millimeter wave (30–300 GHz) is centralized and processed at control station (CS) and also, the CS upconverts this electrical signal to optical domain. By employing optical fiber link, this signal reaches to base station (BS). Then, the received optical signal converts back to electrical domain at the respective BS. Now BS radiates the electrical signal to corresponding mobile station (MS) in commission with the millimeter wave frequency bands. This RoF system is providing massive bandwidth, facilitating large mobility for RF frequency signals, small loss, fast and cost effective setup, wonderful security, and unlicensed spectrum etc. The RoF system introduces microcells structure for BS cells to boost the frequency reuse and needed capacity. It has benefits in terms of ability to fulfill increasing bandwidth demands to cut back the power consumption and the dimensions of the handset devices. This paper firstly explains the overview of existing wireless mobile communication and broadband systems and then, targets the review of RoF system which will become energy efficient system for next generation mobile communication and future broadband systems. This paper also includes the performance degradation and evaluation parameters. Finally, this paper presents the various research opportunities for its implementation zone.

Mobile e-Learning for Next Generation Communication Environment

2010 ◽  
pp. 1844-1855
Author(s):  
Tin-Yu Wu ◽  
Han-Chieh Chao
Keyword(s):  
Mobile Communication ◽  
Knowledge Economy ◽  
Smart Phones ◽  
Fourth Generation ◽  
Next Generation ◽  
Embedded Devices ◽  
Available Bandwidth ◽  
Online Test ◽  
Interactive Classroom ◽  
E Learning

This article develops an environment for mobile e-learningthat includes an interactive course, virtual online labs, an interactive online test, and lab-exercise training platform on the fourth generation mobile communication system. TheNext Generation Learning Environment (NeGL) promotes the term “knowledge economy.” Inter-networking has become one of the most popular technologies in mobile e-learning for the next generation communicationenvironment. This system uses a variety of computer embedded devices to ubiquitously access multimedia information, such as smart phones and PDAs. The most important feature is greater available bandwidth. The learning mode in the future will be an international, immediate, virtual, and interactive classroom that enables learners to learn and interact.

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