Download 4G Femtocells: Resource Allocation and Interference by Haijun Zhang, Xiaoli Chu, Xiangming Wen PDF

By Haijun Zhang, Xiaoli Chu, Xiangming Wen

This short examines source allocation and interference administration for 4G femtocells. It introduces 4G femtocells within the context of 4G cellular networks and discusses similar technical demanding situations in source allocation and interference administration. issues contain ant colony set of rules dependent downlink source allocation, clever scheduling and tool keep an eye on, uplink and downlink for two-tier networks, caliber of carrier (QoS) constraints and the cross-tier interference constraint. The authors current algorithms to relieve universal femtocell-related difficulties corresponding to subchannel energy allocation. The complexity of the proposed source allocation algorithms is analyzed, and the effectiveness of the proposed algorithms is demonstrated via simulations. This concise and useful publication without delay addresses universal difficulties in terms of femtocells and source administration. It serves as a great tool for researchers within the box. Advanced-level scholars or execs attracted to femtocells and networks also will locate the content material helpful.

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It can be seen that the existing algorithm provides a higher capacity than the proposed algorithm for delay-sensitive users, because the subchannel allocation in the proposed algorithm maximizes the capacity of delay-torrent users while ensuring a certain level capacity for delay-sensitive users. However, the subchannel allocation in the existing algorithm maximizes the total capacity of all the users and maintains users’ fairness by allocating at least a subchannel to each user. 4 Simulation Results and Discussions 47 Aveage capacity of each femtocell (bps/Hz) 30 25 20 15 Average Capacity of each Femtocell, Uplink Average Capacity of each Femtocell, Downlink 10 5 0 0 10 20 30 Iteration index t 40 50 Fig.

D. W. K. Ng and R. Schober, “Resource allocation and scheduling in multi-cell ofdma systems with decode-and-forward relaying,” IEEE Trans. , vol. 10, no. 7, pp. 2246–2258, July 2011. 18. C. Y. Wong, R. Cheng, K. Lataief, and R. Murch, “Multiuser ofdm with adaptive subcarrier, bit, and power allocation,” IEEE J. Sel. , vol. 17, no. 10, pp. 1747–1758, Oct. 1999. 19. W. Yu and R. Lui, “Dual methods for nonconvex spectrum optimization of multicarrier systems,” IEEE Trans. , vol. 54, no. 7, pp. 1310–1322, July 2006.

It has been shown through simulations that the proposed interference-aware resource allocation algorithm is able to provide improved capacities of both macrocell and femtocells, together with comparable tiered fairness, as compared with the existing unpriced subchannel allocation and MIWF based power allocation algorithm. Acknowledgements The authors would like to thank Dr. David López-Pérez and Prof. Arumugam Nallanathan for their helpful discussions. This work was supported by the Sci-tech Projects of the Committee on Science and Technology of Beijing (D08080100620802, Z101101004310002), the National Natural Science Foundation of China (61101109), and National Key Technology R&D Program of China (2010ZX03003-001-01, 2011ZX03003-002-01), Co-building Project of Beijing Municipal Education Commission “G-RAN based Experimental Platform for Future Mobile Communications”, “Research on Resource Allocation and Scheduling Strategy of Future Wireless Communication System” and “Cooperative Communications Platform for Multi-agent Multimedia Communications”, Key Fund of Beijing Key Laboratory on Future Network Research.

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