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Adaptive subcarrier and bit allocation in OFDMA systems supporting heterogeneous services

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Abstract

Orthogonal Frequency Division Multiple Access (OFDMA) is an efficient multiple access method for the future wireless systems. This paper studies the adaptive subcarrier and bit allocation problem in OFDMA systems to support heterogeneous services. The goal of the considered resource optimization technique is to maximize the total system throughput under the overall transmit power constraint while guaranteeing the QoS requirement of realtime users and supporting proportional fairness among non-realtime users. First, we introduce a Rate Adaptive (RA) resource allocation algorithm for non-realtime users and a Margin Adaptive (MA) algorithm for realtime users. Then, based on the previous algorithms, a novel algorithm is proposed to allocate the resource to both classes of users, which makes an efficient tradeoff between the resource usage of realtime users and non-realtime users. The algorithm is locally optimal solution provided that the MA and RA algorithms are utilized. Also, to reduce the computational complexity, a suboptimal method based on the balancing of the average power per subcarrier is also introduced. Monte Carlo simulation results show that all the proposed algorithms outperform the existing counterparts. The results also show that the suboptimal method for heterogeneous services can efficiently reduce the computational complexity at the cost of very little performance degradation.

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Author information

Correspondence to Guanding Yu.

Additional information

This work was supported by the National Natural Science Foundation of China (Nos. 60472079, 60572115), and by the Natural Science Foundation of Zhejiang Province (No. Z104252), China.

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Yu, G., Zhang, Z. & Qiu, P. Adaptive subcarrier and bit allocation in OFDMA systems supporting heterogeneous services. Wireless Pers Commun 43, 1057–1070 (2007). https://doi.org/10.1007/s11277-007-9283-2

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Keywords

  • OFDMA
  • Adaptive subcarrier and bit allocation
  • Heterogeneous services
  • QoS
  • Fairness