IEEE Transactions on Communications,
vol. 57, no. 1, Jan. 2009, pp. 232-241.
Optimal Resource Allocation in OFDMA
Systems 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 78712-1084 USA
OFDMA Resource 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 both continuous and discrete ergodic weighted sum rate
maximization subject to total power constraints, and average bit error
rate constraints for the discrete rate case.
We approach these problems using a dual optimization framework, allowing
us to solve these problems 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 for continuous rates and less than 10-3 for
discrete rates in simulations based on realistic parameters.
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