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Fig. 7.
Minimum user capacity with a different number of users
Fig. 7 shows the minimum user capacity for an increasing number of users in an
OFDM system. We can see that the adaptive algorithms, including the proposed
algorithm and the algorithm given in [7], show significant improvement over the non-
adaptive TDMA method. The proposed algorithm with optimal sub-channel and pow-
er allocation achieves even higher capacity than the method proposed in [7].
5
Conclusion
In this paper we presented an algorithm based on genetic algorithms for adaptive re-
source allocation in a multiuser OFDM system. The algorithm first carries out sub-
channel allocation using a rough rate constraint to achieve maximum capacity. Using
the sub-channel allocation solution, optimal power allocation is implemented to achieve
proportional fairness and maintain maximum system capacity. Simulation results show
that the proposed algorithm not only effectively satisfies the requirements of maximum
capacity and proportional fairness, but also reduces computational complexity.
Acknowledgment
. This study is supported by "Fundamental Research Fund for he
Central Universities"(2013RC0203, and Beijing Key Laboratory of Work Safety In-
telligent Monitoring (Beijing University of Posts and Telecommunications).
References
1.
Sampath, H., Talwar, S., Tellado, J., Erceg, V., Paulraj, A.: A fourth-generation MIMO-
OFDM broadband wireless system: Design, performance, and field trial results. IEEE
Commun. Mag. 40(9), 143-149 (2002)
