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Mobile Networks and Applications
Published in: Mobile Networks and Applications 5/2019

18-12-2018

Data-Driven Power Allocation for Medium Access Control in LTE-U Coexisting with Wi-Fi

Authors: Rongfei Fan, Song Jin, Qi Gu, Gongpu Wang

Published in: Mobile Networks and Applications | Issue 5/2019

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Abstract

In this paper, power allocation problem is investigated for an LTE-U (long-term evolution unlicensed) system, in which a cellular system will transmit data on the unlicensed spectrum occupied by Wi-Fi system. One base station and multiple mobile users are considered for both uplink scenario and downlink scenario. To access the base station in uplink scenario or to transmit information to multiple mobile users in downlink scenario, orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) are studied respectively. The transmit power of the base station or multiple mobile users over multiple channels in the unlicensed spectrum are optimized to maximize the system throughput while imposing a probabilistic constraint on the interference to Wi-Fi receiver only with a number of samples of interference channel’s gain. Although being in non-closed-form, the formulated probabilistic constraint is transformed to be two types of closed-form constraints. Then the originally formulated optimization problems fall into convex optimization problems. In addition, it is proved that the OMA mode can achieve the same performance with the NOMA mode for uplink scenario, and one simple solution is developed under OMA mode for downlink scenario. Numerical results are demonstrated to show the performance of our proposed methods.
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Footnotes
1
When channel n is divided by a large number of sub-carriers, \(w_{n,m}, \forall n \in \mathcal {N}, m\in \mathcal {M}\) can be seen as a continuous variable.
 
2
The probability measure has the same meaning with the distribution function but is more broadly used in the area of probability theory. In the following, we will adopt probability measure, rather than distribution function, for random variables.
 
3
Recalling that Gn is the upper bound of ||gn||, thus \(G_n=\sqrt {{\sum }_{m = 1}^M \left ((\hat {g}_{n,m}^{(S + 1)}\right )^2}\). Assuming that \(\hat {g}_{n,m}^{(S + 1)}\) is equal for \(m\in \mathcal {M}\), then it is natural to write \(\hat {g}_{n,m}^{(S + 1)}=G_n/\sqrt {M}\).
 
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Metadata
Title
Data-Driven Power Allocation for Medium Access Control in LTE-U Coexisting with Wi-Fi
Authors
Rongfei Fan
Song Jin
Qi Gu
Gongpu Wang
Publication date
18-12-2018
Publisher
Springer US
Published in
Mobile Networks and Applications / Issue 5/2019
Print ISSN: 1383-469X
Electronic ISSN: 1572-8153
DOI
https://doi.org/10.1007/s11036-018-1182-0

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