low-complexity iterative approximated water-filling based power allocation in an ultra-dense network

Clicks: 153
ID: 208186
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #313 of 406 articles by views in European journal of medicinal chemistry

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 406 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
It is highly possible that future wireless communication systems will adopt ultra-dense deployment to cope with the increasing demand on spectrum efficiency and energy efficiency. The pivotal issue to achieve the potential benefits of the ultra-dense network is to deal with the complex inter-site interference. In this paper, in order to maximize the spectrum efficiency of the system, we first make a reasonable approximation on the inter-site interference to convert the problem into a convex optimization problem. Then, the Lagrangian Multiplier method is adopted to obtain the expression of the optimum power allocation, and the water filling algorithm, as one of the most classical algorithms in the information theory, can be applied to maximize the sum rate or spectrum efficiency of the system. Since the classical iteratively searching water filling algorithm needs many iterations to converge to the optimal solution, we develop a low-complexity iterative approximate water filling algorithm. Simulation results show that the developed algorithm can achieve very close performance to the classical iteratively searching water filling based power allocation with only a few iterations under different scenarios, which leads to a significant complexity reduction.
Reference Key
su2016entropylow-complexity Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Xin Su;Bei Liu;Xiaopeng Zhu;Jie Zeng;Chiyang Xiao
Journal European journal of medicinal chemistry
Year 2016
DOI
10.3390/e18050158
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.