Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: IResearch Article Adaptive Resource Allocation with Strict Delay Constraints in OFDMA System | Hindawi Publishing Corporation EURASIP Journal on Wireless Communications and Networking Volume 2010 Article ID 121080 14 pages doi 2010 121080 Research Article Adaptive Resource Allocation with Strict Delay Constraints in OFDMA System Naveed Ul Hassan and Mohamad Assaad Department of Telecommunications Ecole Superieure d Electricite Supelec Plateau de Moulon 3 rue Joliot Curie 91192 Gif-sur-Yvette Cedex France Correspondence should be addressed to Naveed Ul Hassan Received 18 September 2009 Revised 20 April 2010 Accepted 5 August 2010 Academic Editor A. Lee Swindlehurst Copyright 2010 N. Ul Hassan and M. Assaad. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. We consider the adaptive resource allocation problem in downlink Orthogonal Frequency Division Multiple Access OFDMA system with strict packet delay constraints in the range of 1 D o. In this range of delay constraints resource optimization has to be simultaneously performed over multiple time slots. Thus optimal allocation decisions require future Channel State Information CSI and packet arrival rate information. The causal nature of CSI combined with the increase in the number of optimization variables makes it a very challenging problem. We propose a two-step solution by separating scheduling from subcarrier and power allocation. Our proposed causal scheduler ensures delay guarantees by deriving a minimum data rate out of the user queues while minimizing transmit power in every time slot. The output rates are fed to the resource allocation block and the problem is formulated as a convex optimization problem. The subcarrier and power allocation decisions are made in order to satisfy the demanded rates within the peak power constraint. We address the feasibility of the physical layer resource allocation problem and .
