Energy-efficiency Optimization of Pilot Duration and Power Allocation for Downlink Massive MIMO FDD Systems

WANG Yi; LIN Yan; LI Chunguo; HUANG Yongming; YANG Luxi

doi:10.11999/JEIT160226

Volume 39 Issue 1

Jan. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(1): 16-23

WANG Yi, LIN Yan, LI Chunguo, HUANG Yongming, YANG Luxi. Energy-efficiency Optimization of Pilot Duration and Power Allocation for Downlink Massive MIMO FDD Systems[J]. Journal of Electronics & Information Technology, 2017, 39(1): 16-23. doi: 10.11999/JEIT160226

Citation:

WANG Yi, LIN Yan, LI Chunguo, HUANG Yongming, YANG Luxi. Energy-efficiency Optimization of Pilot Duration and Power Allocation for Downlink Massive MIMO FDD Systems[J]. Journal of Electronics & Information Technology, 2017, 39(1): 16-23. doi: 10.11999/JEIT160226

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Energy-efficiency Optimization of Pilot Duration and Power Allocation for Downlink Massive MIMO FDD Systems

doi: 10.11999/JEIT160226

Funds:

The National 863 Program of China (2015AA01A703), The National Natural Science Foundation of China (61372101, 61271018, 61671144), Research Project of Jiangsu Province (BE2015156), The Natural Science Research Project of Jiangsu Province for Colleges and Universities (16KJB510008)

Received Date: 2016-03-11
Rev Recd Date: 2016-07-28
Publish Date: 2017-01-19

Abstract

Abstract

An energy-efficient resource allocation method is provided for the downlink massive Multiple-Input Multiple-Output (MIMO) Frequency Division Duplexing (FDD) system, which jointly evaluates the channel estimation stage and data transmission stage. The optimization problem is established based on the Energy Efficiency (EE) maximization by adjusting the pilot duration, pilot power and data power under the constraint of total transmit energy and spectral efficiency requirement. Since the analytical expression of the involved objective function is intractable, a closed-form expression is deduced using deterministic equivalent approximation technology. Based on this, the original non-convex fractional optimization problem is transformed into an equivalent problem in subtractive form by the means of fraction programming. Then, a lower bound of the transformed objective function is employed, which induces a relatively easy-to-solve equivalent problem. Finally, a three-layer iterative algorithm is developed. Numerical results validate the effectiveness and relatively fast convergence speed of the proposed algorithm.
- Massive MIMO,
- Frequency Division Duplexing (FDD),
- Energy efficiency,
- Pilot duration

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References(22)

References

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