Energy-Efficient Power Allocation Scheme for Uplink Distributed Antenna System with D2D Communication

Wang, Guangying; Yu, Xiangbin; Teng, Tao

doi:10.1007/s11036-019-01343-2

Cited by 2 publications

(3 citation statements)

References 19 publications

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“…2, the EE performances under different PA schemes are compared. We also give the comparison of baseline scheme in previous work [18], while assuming only one D2D pair. We can find that both EE of our proposed PA schemes are increasing firstly and then stay to be a constant with the increase of P max, d , which confirms the effectiveness of both proposed schemes.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The above works are all based on the D2D communications in co-located antenna system (CAS). There are some research works about resource allocation and EE optimization in DAS and D2D communication [18][19][20][21]. In [18], the authors developed an energy-efficient PA scheme in the uplink DAS with D2D communication, which only considered individual D2D pair.…”

mentioning

confidence: 99%

“…There are some research works about resource allocation and EE optimization in DAS and D2D communication [18][19][20][21]. In [18], the authors developed an energy-efficient PA scheme in the uplink DAS with D2D communication, which only considered individual D2D pair. In [19], the authors presented a multiple criteria scheme to optimize EE in downlink DAS.…”

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confidence: 99%

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Energy Efficiency Optimization for D2D Underlay Communication in Distributed Antenna System over Composite Fading Channels

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Device-to-Device (D2D) communication is a potential technology to improve the spectral and energy efficiency (EE) of communication networks. In this paper, we study energy-efficient power allocation (PA) schemes in uplink distributed antenna system (DAS) with device-todevice underlay communication. Our goal is to maximize the total EE of all D2D pairs while guaranteeing the data rate and transmit power requirements of the cellular user and D2D links. To solve this non-convex constrained optimization problem, we propose an energy-efficient nearoptimal PA algorithm based on the concave-convex procedure and fractional programming theory. This near-optimal algorithm can achieve the EE performance close to the optimal exhaustive search. To reduce the complexity, we furthermore present an efficient sub-optimal algorithm with the antenna selection method which can obtain the closed-form power allocation expressions. Simulation results demonstrate the significant EE performance of our proposed PA schemes.

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Section: Simulation Resultsmentioning

confidence: 99%

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confidence: 99%