3G Evolution, Second Edition: HSPA and LTE for Mobile Broadband
3G Evolution, Second Edition: HSPA and LTE for Mobile Broadband
LTE, The UMTS Long Term Evolution: From Theory to Practice
LTE, The UMTS Long Term Evolution: From Theory to Practice
Adaptive subcarrier allocation schemes for wireless OFDMA systems in WiMAX networks
IEEE Journal on Selected Areas in Communications - Special issue on broadband access networks: Architectures and protocols
Dynamic frequency allocation in fractional frequency reused OFDMA networks
IEEE Transactions on Wireless Communications
Resource allocation in an LTE cellular communication system
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Radio Resource Allocation Algorithms for the Downlink of Multiuser OFDM Communication Systems
IEEE Communications Surveys & Tutorials
Multiuser adaptive subcarrier-and-bit allocation with adaptive cell selection for OFDM systems
IEEE Transactions on Wireless Communications
Cross-layer optimization for OFDM wireless networks-part I: theoretical framework
IEEE Transactions on Wireless Communications
Capacity of fading channels with channel side information
IEEE Transactions on Information Theory
Transmit power adaptation for multiuser OFDM systems
IEEE Journal on Selected Areas in Communications
Resource Allocation for Wireless Multiuser OFDM Networks
IEEE Transactions on Information Theory
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In multi-user OFDMA systems, adaptive resource allocation has been identified as one of the key technologies to have more flexibility and higher efficiency. Several adaptive subcarrier allocation algorithms with the objective to maximize spectral efficiency or fairness have been proposed. However, quality of service (QoS) requirement of each user may not be supported. Some algorithms considering user's QoS requirement have been introduced, but they do not consider the case that every user's QoS requirement cannot be guaranteed with limited resources. In this paper, we propose a maximum achievement rate allocation (MARA) algorithm as a new adaptive resource allocation algorithm. The proposed MARA algorithm has a goal to improve overall throughput while maximizing achievement rate, i.e., maximize the number of users meeting QoS requirements. In addition, we investigate that MARA is more effective when fractional frequency reuse (FFR) is adopted as a frequency partitioning scheme. Simulation results show that the MARA algorithm improves the achievement rate as well as overall throughput. Moreover, further performance gains are achieved when FFR is adopted.