T. K. Vu, C. Liu, M. Bennis, M. Debbah and M. Latva-aho, "Path selection and rate allocation in self-backhauled mmWave networks," 2018 IEEE Wireless Communications and Networking Conference (WCNC), Barcelona, 2018, pp. 1-6. doi: 10.1109/WCNC.2018.8377239
Path selection and rate allocation in self-backhauled mmWave networks
|Author:||Vu, Trung Kien1; Liu, Chen-Feng1; Bennis, Mehdi1;|
1Centre for Wireless Communications, University of Oulu
2Mathematical and Algorithmic Sciences Lab, Huawei France R&D
|Online Access:||PDF Full Text (PDF, 0.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2018090334429
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2018-09-03
We investigate the problem of multi-hop scheduling in self-backhauled millimeter wave (mmWave) networks. Owing to the high path loss and blockage of mmWave links, multi-hop paths/routes between the macro base station and the intended users via full-duplex small cells need to be carefully selected. This paper addresses the fundamental question: “how to select the best paths and how to allocate rates over these paths subject to latency constraints?” To answer this question, we propose a new system design, which factors in mmWave-specific channel variations and network dynamics. The problem is cast as a network utility maximization subject to a bounded delay constraint and network stability. The studied problem is decoupled into: (i) a path/route selection and (ii) rate allocation, whereby learning the best paths is done by means of a reinforcement learning algorithm, and the rate allocation is solved by applying the successive convex approximation method. Via numerical results, our approach ensures reliable communication with a guaranteed probability of 99.9999%, and reduces latency by 50.64% and 92.9% as compared to baselines.
IEEE Wireless Communications and Networking Conference
2018 IEEE Wireless Communications and Networking Conference (WCNC)
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
The authors would like to thank Tekes, Nokia, Huawei, MediaTek, Keysight, Bittium and Kyynel for project funding. The Academy of Finland funding via the grant 307492 and the CARMA grants 294128 and 289611, the Nokia Foundation, and the Riitta and Jorma J. Takanen Foundation SR grant are also acknowledged.
|Academy of Finland Grant Number:||
307492 (Academy of Finland Funding decision)
294128 (Academy of Finland Funding decision)
289611 (Academy of Finland Funding decision)
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