1 / 18

by Kyuho Son, Hongseok Kim, Yung Yi, Bhaskar Krishnamachari

Base Station Operation and User Association Mechanisms For Energy-Delay Tradeoffs in Green Cellular Networks. by Kyuho Son, Hongseok Kim, Yung Yi, Bhaskar Krishnamachari. Haluk Celebi / hc2489. Outline. Motivation Problems to be solved System model Solution approaches and algorithms.

tuyet
Download Presentation

by Kyuho Son, Hongseok Kim, Yung Yi, Bhaskar Krishnamachari

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Base Station Operation and User Association Mechanisms For Energy-Delay Tradeoffs in Green Cellular Networks by Kyuho Son, Hongseok Kim, Yung Yi, BhaskarKrishnamachari HalukCelebi/ hc2489

  2. Outline • Motivation • Problems to be solved • System model • Solution approaches and algorithms

  3. Main Motivation • BSs are large underutilized: Traffic is below 10% of peak 45% of the time. • UMTS BS consumes 800-1500W, and radio 30-40W. Thus, not only turning off the transceivers, we need to turn off BS completely.

  4. Problems to be solved • User association: When the set of active BS changes, MT needs to be associated with a new BS • Energy efficient BS operation: finding optimal set of active BS - Paper gives a distributed algorithm to solve 1st problem optimally. For 2nd problem, it offers several greedy algorithms.

  5. System Model and Problem Formulation • arrival rate Traffic load density Set of active BS Transmission rate of user i located at x Fraction of time required to deliver traffic load from BS i to location x

  6. Feasible solution to the problem: utilizations of BSs Note that in optimal case p(x) is either 1 or 0

  7. Cost function • n is the parameter that determines between the flow level performance and the energy level consumption Flow level performance

  8. is a parameter specifying the degree of load balancing Each MT prefers a BS that gives the highest rate Minimizing number of flows, thus delay in M/M/1 queue Thus as α increases, cost function places more importance on traffic load instead of transmission rate

  9. Cost function of Energy Portion of fixed power consumption. Energy that is spend only depends on the radio. In other case, when q =1, regardless of the utilization amount of energy spend is Pi. That`s where turning BS off becomes more important We assume femto cells are more energy proportional (smaller q values) macro cells.

  10. Solution approach to the problem • Solving two cost functions together is hard. • We assume that flow arrival, and departure process is • much faster than the period of determining active and • passive BSs • Decompose problem into two sub-problems • Solve user association problem. For given active BS set find which BS each MT should connect to • BS operation problem

  11. Connection policy It`s proved in the paper that with this policy, each MT is able to choose optimal BS

  12. Energy Efficient BS operation

More Related