Impact of Transceiver Power Consumption on the Energy Efficiency of Zero-Forcing Detector in Massive MIMO Systems

Mohammed, Saif Khan

doi:10.1109/tcomm.2014.2364188

Cited by 81 publications

(79 citation statements)

References 19 publications

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“…The research results illustrated that the maximal EE is achieved at some finite number of transceiver antennas when there is a non-zero circuit power per antenna. Similarly, the studies in [41] also demonstrated that it is optimal from the perspective of EE to have a few transceiver antennas when the transceiver design is power inefficient.…”

Section: Introductionmentioning

confidence: 90%

Energy Efficient Coordinated Beamforming for Multicell System: Duality-Based Algorithm Design and Massive MIMO Transition

Huang

Yang

et al. 2015

IEEE Trans. Commun.

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Abstract-In this paper, we investigate joint beamforming and power allocation in multicell multiple-input single-output (MISO) downlink networks. Our goal is to maximize the utility function defined as the ratio between the system weighted sum rate and the total power consumption subject to the users' quality of service requirements and per-base-station (BS) power constraints. The considered problem is nonconvex and its objective is in a fractional form. To circumvent this problem, we first resort to an virtual uplink formulations of the the primal problem by introducing an auxiliary variable and applying the uplinkdownlink duality theory. By exploiting the analytic structure of the optimal beamformers in the dual uplink problem, an efficient algorithm is then developed to solve the considered problem. Furthermore, to reduce further the exchange overhead between coordinated BSs in a large-scale antenna system, an effective coordinated power allocation solution only based on statistical channel state information is reached by deriving the asymptotic optimization problem, which is used to obtain the power allocation in a long-term timescale. Numerical results validate the effectiveness of our proposed schemes and show that both the spectral efficiency and the energy efficiency can be simultaneously improved over traditional downlink coordinated schemes, especially in the middle-high transmit power region.Index Terms-Coordinated energy-efficient transmission, uplink-downlink duality, massive multiple-input-single-output system, beamforming and power allocation.

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Section: Introductionmentioning

confidence: 90%

Energy Efficient Coordinated Beamforming for Multicell System: Duality-Based Algorithm Design and Massive MIMO Transition

Huang

Yang

et al. 2015

IEEE Trans. Commun.

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“…Equation (14) is used to calculate the remaining renewable energy. The available value of renewable energy for period can be calculated by (15), which fully utilizes (8) and (9). Equations (16) and (17) denote the transmitting power constraint for period and the QoS constraint for MT .…”

Section: Problem Formulationmentioning

confidence: 99%

Sleep Mechanism of Base Station Based on Minimum Energy Cost

Han

Chen

2018

Wireless Communications and Mobile Computing

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Deploying dense network is a promising technique of fifth-generation communication to meet the challenge of soaring demand from explosive growth of mobile users. However, this technique obviously increases the power consumption, thereby indirectly causing heavy financial burden on mobile network operators and CO 2 emission, which is considered as a major threat to the environment. In consideration of energy storage device, self-discharge effect, and preventing repeated switch (PRS) mechanism, a comprehensive power management model for wireless communication system in smart grid is investigated in this study from the power consumption and economic cost aspects. Two base sleep mechanisms, namely, energy cost first (ECF) algorithm and power consumption first (PCF) algorithm, are proposed. The ECF algorithm focuses on the minimum cost of system operation by selecting the low-cost energy scheme. Meanwhile, the PCF algorithm considers the minimum power consumption first and then optimizes the cost. Compared with conventional scheme, simulation results show that the two proposed algorithms can decrease the energy cost of communication base system significantly. Setting an energy storage device can further stabilize the energy cost, while the switching frequency can be reduced to a large extent when combined with the PRS mechanism.

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“…Considering the transmit power and the circuit power in massive MIMO systems, a power consumption model has been proposed to help optimize the energy efficiency of multi-cell mobile communication systems by selecting the optimal number of active antennas [23]. When the sum spectrum efficiency was fixed, the impact of transceiver power consumption on the energy efficiency of ZF detector was investigated for the uplinks of massive MIMO systems [24]. Considering the power cost by RF generation, baseband computing, and the circuits associated with each antenna, simulation results in [25] illustrated that massive MIMO macro cells outperforms LTE macro cells in both spectrum and energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficiency Optimization of 5G Radio Frequency Chain Systems

Thompson

et al. 2016

IEEE J. Select. Areas Commun.

151

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Abstract-With the massive multi-input multi-output (MIMO)antennas technology adopted for the fifth generation (5G) wireless communication systems, a large number of radio frequency (RF) chains have to be employed for RF circuits. However, a large number of RF chains not only increase the cost of RF circuits but also consume additional energy in 5G wireless communication systems. In this paper we investigate energy and cost efficiency optimization solutions for 5G wireless communication systems with a large number of antennas and RF chains. An energy efficiency optimization problem is formulated for 5G wireless communication systems using massive MIMO antennas and millimeter wave technology. Considering the nonconcave feature of the objective function, a suboptimal iterative algorithm, i.e., the energy efficient hybrid precoding (EEHP) algorithm is developed for maximizing the energy efficiency of 5G wireless communication systems. To reduce the cost of RF circuits, the energy efficient hybrid precoding with the minimum number of RF chains (EEHP-MRFC) algorithm is also proposed. . Compared with conventional MIMO antenna technology, massive MIMO can improve more than 10 times spectrum efficiency in wireless communication systems [7]. Moreover, the beamforming gain based on the massive MIMO antenna technology helps to overcome the path loss fading in millimeter wave channels. For MIMO communication systems with traditional radio frequency (RF) chains and baseband processing, one antenna corresponds to one RF chain [8], [9]. In this case, a large number of RF chains has to be employed for massive MIMO communication systems. These RF chains not only consume a large amount of energy in wireless transmission systems but also increase the cost of wireless communication systems [10]. Therefore, it is an important problem to find energy efficient solutions for 5G wireless communication systems with a large number of antennas and RF chains.To improve the performance of multiple antenna transmission systems, hybrid precoding technology combining digital

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Impact of Transceiver Power Consumption on the Energy Efficiency of Zero-Forcing Detector in Massive MIMO Systems

Cited by 81 publications

References 19 publications

Energy Efficient Coordinated Beamforming for Multicell System: Duality-Based Algorithm Design and Massive MIMO Transition

Energy Efficient Coordinated Beamforming for Multicell System: Duality-Based Algorithm Design and Massive MIMO Transition

Sleep Mechanism of Base Station Based on Minimum Energy Cost

Energy Efficiency Optimization of 5G Radio Frequency Chain Systems

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