By Topic

Resource Allocation Based on Channel Distribution Information for Elastic and Streaming Traffic in OFDMA Networks: A Heuristic Algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Mokari, N. ; Dept. of Electr. & Comput. Eng., Tarbiat Modares Univ., Tehran, Iran ; Javan, M.R. ; Navaie, K.

In this paper, we propose a low complexity heuristic algorithm for radio resource allocation in orthogonal frequency division multiple access (OFDMA) systems based on subcarrier channel distribution information (CDI). We consider practical rate adaptation in which rate is adapted using a predefined set of modulation levels, which is in contrast to previous works that consider continuous rate. We formulate the problem of resource allocation in an OFDMA system with streaming traffic which requires a minimum guaranteed average rate, and elastic traffic with flexible rate requirements. The main objective is to maximize the total transmission rate of the elastic users, while average rate guarantees for streaming traffic as well as maximum transmission power constraints are satisfied. To reduce the computational complexity, we decouple the resource allocation problem into two sub-problems corresponding to two traffic types. For streaming traffic, we optimally allocate subcarrier and power and then the remaining radio resources including the unassigned subcarriers and unallocated transmission power of the base station are optimally allocated to the elastic traffic. We then develop a heuristic algorithm based on Lagrangian method to obtain an approximation of the optimal solution. Using simulations, we study the impact of number of fading regions. Simulations also provides insight on the trade-off between the number of streaming and elastic users.

Published in:

Vehicular Technology Conference Fall (VTC 2009-Fall), 2009 IEEE 70th

Date of Conference:

20-23 Sept. 2009