Proc. IEEE International
Conference on Acoustics, Speech, and Signal Processing,
April 16-20, Honolulu, HI USA,
accepted for publication.
Optimal OFDMA Subcarrier, Rate, and Power Allocation
for Ergodic Rates 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 information (CSI).
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 (imperfect) CSI.
We consider ergodic weighted sum discrete rate 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
10-3 (99.999% optimal).
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Last Updated 12/12/14.