Throughput in A Cooperative Network and Channel State Information

Yeh, Yi-Nung; Chen, Kwang-Cheng; Chen, Yi-Chi

doi:10.1007/s11277-015-2509-9

Cited by 2 publications

(2 citation statements)

References 44 publications

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“…It is shown that a game-theoretic approach [14] was able to provide insights into the equilibrium operating point [15,16] and the network performance such as throughput from a decentralized perspective. Later works explore more realistic settings by incorporating the CSI into the ALOHA model to enable each node to make channel-aware decisions [10,12,[17][18][19]. More sophisticated channel models were also investigated towards a more accurate characterization of the fading channel.…”

Section: Introductionmentioning

confidence: 99%

Distributed Transmission Probability Control in Fading Channel with State Information

Xie

Low

Gunawan

2015

International Journal of Distributed Sensor Networks

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A wireless system consisting of a finite number of heterogeneous users transmitting packets over a slotted ALOHA Rayleigh-fading channel is investigated in this paper. In this system, each user tries to minimize its number of transmission attempts while meeting the throughput demand. The user interaction in such an ALOHA network is modeled as a random access game. A novel technique to better exploit the channel state information (CSI) named adaptive CSI transmission method is proposed. Benchmarking with the no-CSI method and threshold-based CSI method, it is revealed that the proposed adaptive CSI method can yield up to 9.9% more throughput and 12.3% power reduction. Two simple yet effective guidelines on selecting among these CSI-related methods are formulated for systems with different SNRs and capture ratios. A distributed algorithm is proposed to find the optimal transmission probability. Both analytical and simulation results show that the algorithm exhibits fast convergence speed and is robustness against changes on the number of active nodes in the network.

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Section: Introductionmentioning

confidence: 99%

Distributed Transmission Probability Control in Fading Channel with State Information

Xie

Low

Gunawan

2015

International Journal of Distributed Sensor Networks

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“…It is shown that a game-theoretic approach [41] was able to provide insights into the equilibrium operating point [42,43] and the network performance such as throughput from a decentralized perspective. Later works explored more realistic settings by incorporating the CSI into the ALOHA model to enable each node to make channel-aware decisions [21,22,38,44,45].…”

Section: Transmission Rate Control In Aloha Networkmentioning

confidence: 99%

Distributed traffic estimation and throughput optimization in random access networks

Xie¹

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I am also thankful to a number of people I have met during my graduate studies. Dr. Lee Guo Xiong and Dr. Soon Jing Jun Charlie, my seniors, have shared their experience and provided valuable advice on the route to getting a Ph.D. degree. Mr. Marc Caesar Talampas, Mr. Ian Kamajaya and Mr. Xing Yitong have shared their expertise on the usage and implementation of wireless hardware modules. I am also grateful to Mr. Han Bo, Mr. Kashyap Narenathreyas and Mr. Shen Qiang for those interesting discussions. I also appreciate the final year student, Miss Seow Hui Chin for helping me set up and test the hardware modules. Many friends have helped me stay sane through these years. Mr. Huang Lihan, a special friend of mine for more than 19 years, has been sharing with me his compelling projects and ideas, which unexpectedly help me reduce stress. I am also very grateful to my best friends, Mr. Chen Tao, Mr. Zhuang Yuezhi and Mr. Zheng Han, for iii exchanging interesting ideas on a daily basis. Dr. Hu Yusong, my schoolmate in both undergraduate and graduate studies, has shared with me the joys and frustrations during the whole journey. I am indebted to Mr.

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Throughput in A Cooperative Network and Channel State Information

Cited by 2 publications

References 44 publications

Distributed Transmission Probability Control in Fading Channel with State Information

Distributed Transmission Probability Control in Fading Channel with State Information

Distributed traffic estimation and throughput optimization in random access networks

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