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Sub-channel and Power Allocation for Multiuser OFDM
Systems with Proportional Rate Constraints Based
on Genetic Algorithms
Weihai Li, Yunxiao Zu, and Yue Jia
School of Electronic Engineering
Beijing University of Posts and Telecommunications
Beijing, China
{liweihai,zuyx}@bupt.edu.cn,jiayue1@vip.qq.com
Abstract.
This paper considers sub-channel and power allocation based on ge-
netic algorithms to maximize the overall system capacity using proportional
rate constraints in multiuser orthogonal frequency division multiplexing
(OFDM) systems. The proposed algorithm first performs sub-channel allocation
using a rough rate constraint under the premise of equal power allocation
among the sub-channels. Then power allocation proceeds based on the sub-
channel allocation scheme to implement proportional fairness and maintain
maximum system capacity. Owing to the separation of sub-channel and power
allocation, the computational complexity can be reduced from exponential to li-
near. Additionally, both the sub-channel allocation and power allocation are
based on genetic algorithms, so the computational complexity of the proposed
resource allocation algorithm can be further reduced. Simulation results show
that the proposed algorithm achieves about 95% of the maximum capacity in an
eight-user system and that the ratio of data rates among users can be set freely.
Keywords:
sub-channel allocation, power allocation, multiuser OFDM, propor-
tional fairness, system capacity, genetic algorithm.
1
Introduction
Orthogonal frequency division multiplexing (OFDM), which is a key technique in 4G
mobile communication systems, has recently attracted a great deal of attention owing
to its ability to combat multiple path interference. The basic idea is to divide the
available bandwidth into N orthogonal sub-channels [1-3]. Meanwhile, the associated
resource allocation has also become a key research focus. There are two types of re-
source allocation schemes, fixed resource allocation and dynamic resource allocation.
The former scheme allocates independent dimensions of sub-channels and power to
each user. This is obviously not optimal, since channel conditions are not considered.
Instead, dynamic resource allocation adaptively adjusts the allocation scheme accord-
ing to the changing wireless channel environment to make full use of the limited sys-
tem resource [4] [5].
In a previous resource allocation study, Jang and Lee proposed an optimized algo-
rithm to maximize total capacity by assigning each sub-channel to the user with the
