Department of Electrical and
University of California, San Diego
Advisor: Prof. Sujit
Battery Efficient Video Delivery Techniques
Evolving 4G networks offering high data rates, and enhanced coverage and mobile devices capable of high quality video streaming/download and web browsing, are fueling explosive growth of mobile data. Mobile data trends indicate that mobile video will contribute to about two thirds of the total traffic making it hte leading multimedia application on mobile devices. With data and compute intensive mobile video poised to become an important driver of mobile device usage, the battery consumption of mobile devices will be dominated by video delivery and playback. With the adoption of Multi Input Multi Output (MIMO)technologies that use multiple antennas and more power consuming baseband processing, the power due to RF nd baseband ocmponents will likely increase significantly, and dominate the power consumption for high bit rate video applications. In this research, we focus on developing battery efficient video delivery techniques that maximizes mobile device battery life while downloading mobile video without compromising user experience. We propose to utilize the "elasticity" of mobile device video buffer to adapt video bit rate and transmission rate depending on buffer level,battery level and channel conditions. The dynamic video rate adatation techniques enable the Base Station (BS)to adapt the Multi Input Multi Output (MIMO) transceiver configurations to reduce battery current required by MIMO components on the mobile device. The proposed techniques also make the Base Station stop video transmission opportunistically, thereby eliminating the battery load imposed by mobile device MIMO components. The proposed battery aware video delivery techniques can be used to augment different delivery tehniques such as adapaptive streaming, progressive download in order to increase "video time" on mobile devices.
Lowering Power Consumption of Base Station by Dynamic Cell Reconfiguration
In order to address the challenges of increasing cellular network power consumption due to explosive growth in multimedia traffic, the research aims to explore the design of "green" cellular network architectures and algorithms to reduce energy consumption. We propose dynamic network planning techniques that dynamically reconfigures cell sizes and capacity of Base Stations in response to changing cellular traffic and user requirements to minimize Base Station power consumption.We further aim to investigate dynamic network planning techniques coupled with battery aware techniques that minimize battery consumption on mobile devices due to multimedia applications. The proposed solutions will significantly reduce the power demands of Base Stations and mobile devices realizing end to end green cellular network which not only provides ubiquitous connectivity, but also caters to ever increasing popular applications such as mobile video and gaming.