Interference-avoidance Dynamic Channel Allocation for Multimedia Broadcast Multicast Service Single Frequency Networks

Zhang Hai-bo; Liu Ying-na; Li Fang-wei; Liu Kai-jian

doi:10.11999/JEIT150044

Volume 37 Issue 10

Sep. 2015

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(10): 2438-2445

Zhang Hai-bo, Liu Ying-na, Li Fang-wei, Liu Kai-jian. Interference-avoidance Dynamic Channel Allocation for Multimedia Broadcast Multicast Service Single Frequency Networks[J]. Journal of Electronics & Information Technology, 2015, 37(10): 2438-2445. doi: 10.11999/JEIT150044

Citation:

Zhang Hai-bo, Liu Ying-na, Li Fang-wei, Liu Kai-jian. Interference-avoidance Dynamic Channel Allocation for Multimedia Broadcast Multicast Service Single Frequency Networks[J]. Journal of Electronics & Information Technology, 2015, 37(10): 2438-2445. doi: 10.11999/JEIT150044

Citation:

Zhang Hai-bo, Liu Ying-na, Li Fang-wei, Liu Kai-jian. Interference-avoidance Dynamic Channel Allocation for Multimedia Broadcast Multicast Service Single Frequency Networks[J]. Journal of Electronics & Information Technology, 2015, 37(10): 2438-2445. doi: 10.11999/JEIT150044

PDF( 926 KB)

Interference-avoidance Dynamic Channel Allocation for Multimedia Broadcast Multicast Service Single Frequency Networks

doi: 10.11999/JEIT150044

1.
2.
(Chongqing Key Laboratory of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)

Funds:

The National Natural Science Foundation of China (61301122)

Received Date: 2015-01-08
Rev Recd Date: 2015-06-05
Publish Date: 2015-10-19

Abstract

Abstract

A dynamic channel allocation algorithm is proposed to avoid all interference and improve spectrum efficiency in Multimedia Broadcast multicast service Single Frequency Networks (MBSFN). Four electromagnetic compatibility constraint functions are redefined according to the topology information of MBSFN. In order to avoid all intra-area and inter-area interference of MBSFN, a novel energy function of Noise-tuning-based Hysteretic Noisy Chaotic Neural Network (NHNCNN) is constructed elaborately based on renewed constraint functions. Also, the judgment process of the stable state of NHNCNN is developed to accelerate system convergence. Specifically, the dichotomy method is adopted jointly to minimize the total number of allocated channels so as to further improve spectrum efficiency. Simulation results show that a feasible solution without any interference can be effectively searched by the improved NHNCNN. Finally, the optimal solution with minimum total channel number is found. Compared with existing algorithms, the proposed algorithm achieves better convergence speed and quality of solution.

FullText(HTML)

References(18)

References

王凡森, 赵拯, 陈志刚. 一种基于子载波合并的多播资源调度算法[J]. 电子与信息学报, 2014, 36(5): 1184-1189.

Wang F S, Zhao Z, and Chen Z G. A multicast resource scheduling algorithm based on subcarrier merger[J]. Journal of Electronics Information Technology, 2014, 36(5): 1184-1189.

Damnjanovic J and Tenny N E. Resource specification for broadcast/multicast services[P]. US, 20140376438, 2014-12-25.

Hu Z, Jiang H, Li H, et al.. A low-complexity decoding algorithm for coded hierarchical modulation in single frequency networks[J]. IEEE Transactions on Broadcasting, 2014, 60(2): 302-311.

Debessu Y G, Wu H C, Jiang H, et al.. New modified turbo decoder for embedded local content in single-Frequency networks[J]. IEEE Transactions on Broadcasting, 2013, 59(1): 129-135.

Lentisco C M, Bellido L, de la Fuente A, et al.. A model to evaluate MBSFN and AL-FEC techniques in a multicast video streaming service[C]. 2014 IEEE 10th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Barcelona, Spain, 2014: 691-696.

Cheng R G, Huang K J, and Yang J S. Radio resource allocation for overlapping MBS zones[C]. Proceedings of the IEEE MWS, Napa Valley, California, 2009: 75-80.

Jiang A X, Feng C Y, and Zhang T K. Research on resource allocation in multi-cell MBMS single frequency networks[C]. Proceedings of the IEEE WOCN, Colombo, Sri Lanka, 2010: 1-5.

Wang M, Zhang S G, Sun Q Y, et al.. Resources allocation scheme based on mode switch for multicast services in MBSFN[J]. Applied Mechanics and Materials, 2014, 543/547: 3044-3048.

Chen S H and Hou T C. Dynamic channel allocation and power control for OFDMA femtocell networks[C]. Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC), Istanbul, 2014: 1721-1726.

Uykan Z and Jantti R. Channel allocation for bidirectional wireless links-part II: algorithms[J]. IEEE Transactions on Wireless Communications, 2014, 13(7): 3991-4002.

Ben M A and Hamdi M. Dynamic multiuser sub-channels allocation and real-time aggregation model for IEEE 802.11 WLANs[J]. IEEE Transactions on Wireless Communications, 2014, 13(11): 6015-6026.

Naparstek O and Leshem A. Fully distributed optimal channel assignment for open spectrum access[J]. IEEE Transactions on Signal Processing, 2014, 62(2): 283-294.

Moretti M, Abrardo A, and Belleschi M. On the convergence and optimality of reweighted message passing for channel assignment problems[J]. IEEE Signal Processing Letters, 2014, 21(11): 1428-1432.

Zhang H B and Wang X X. Resource allocation for downlink OFDM system using noisy chaotic neural network[J]. Electronic Letters, 2011, 47(21): 1201-1202.

Sun M, Zhao L, Cao W, et al.. Novel hysteretic noisy chaotic neural network for broadcast scheduling problems in packet radio networks[J]. IEEE Transactions on Neural Networks, 2010, 21(9): 1422-1433.

Sun M, Xu Y, Dai X, et al.. Noise-tuning-based hysteretic noisy chaotic neural network for broadcast scheduling problem in wireless multihop networks[J]. IEEE Transactions on Neural Networks and Learning Systems, 2012, 23(12): 1905-1918.

Lin S S and Horng S C. Dynamic channel selection and reassignment for cellular mobile system[C]. Proceedings of the IEEE IS3C, Taichung, China, 2014: 1006-1009.

Relative Articles

Supplements(0)

Cited By

Proportional views