IEEE Global Communications Conference,
November 16-20, Washington, DC USA,
accepted for publication.
OFDMA Resource Allocation for Ergodic Capacity
Maximization with Imperfect Channel Knowledge
Ian C. Wong and
Brian L. Evans
Department of Electrical
and Computer Engineering,
Engineering Science Building,
The University of Texas at Austin,
Austin, TX 78712 USA
Allocation Results by Prof. Evans' Group
from Dr. Ian Wong's PhD Dissertation
Previous research efforts on OFDMA resource allocation have
typically assumed the availability of perfect channel state
Unfortunately, this is unrealistic, primarily due to channel
estimation errors, and more importantly, channel feedback delay.
In this paper, we develop optimal resource allocation algorithms
for OFDMA systems assuming the availability of only partial
We consider ergodic weighted sum capacity maximization subject
to total power constraints.
We approach this problem using a dual optimization framework,
allowing us to solve this problem with O(M K)
complexity per symbol for an OFDMA system with K used
subcarriers and M active users, while achieving relative
optimality gaps of less than 10-5 (99.99999% optimal).
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Last Updated 12/12/14.