User Scheduling and Power Allocation for the Downlink of MIMO Systems Based on Limited Feedback

Zhong, Chongxian; Yang, Liu

doi:10.1109/iwcld.2007.4379027

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…The amount of energy consumption for information and communication technology (ICT) increases dramatically with the exponential growth of service requirement [1], which directly impact on global greenhouse gas emissions. Therefore, as opposed to traditional spectral efficiency resource allocation [2][3][4][5][6], dynamic resource allocation is designed to maximize energy efficiency [7][8][9][10][11][12][13]. On the other side, MIMO technology has been proposed to substantially increase the system performance.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Resource Allocation in Uplink Multiuser Massive MIMO Systems

Hu¹,

Ji²,

Huang³

et al. 2015

International Journal of Antennas and Propagation

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Energy-efficient communications, namely, green communications, has attracted increasing attention due to energy shortage and greenhouse effect. Motivated by this, we consider the uplink energy-efficient resource allocation in multiuser massive multiple-input multiple-output (MIMO) systems. Specifically, we consider that both the number of antenna arrays at the base station (BS) and the transmit data rate at UE are adjusted adaptively to maximize the energy efficiency. Firstly, we demonstrate the existence of a unique resource allocation solution that is globally optimal by exploiting the properties of objective function. Then we develop an iterative algorithm to solve it. By transforming the originally fractional optimization problem into an equivalent subtractive form using the properties of fractional programming, we develop another efficient iterative resource allocation algorithm. Simulation results have validated the effectiveness of the proposed two algorithms and have shown that both algorithms can fast converge to a near-optimal solution in a small number of iterations.

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Section: Introductionmentioning

confidence: 99%

Energy-Efficient Resource Allocation in Uplink Multiuser Massive MIMO Systems

Hu¹,

Ji²,

Huang³

et al. 2015

International Journal of Antennas and Propagation

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“…Meanwhile, energy consumption has significant financial implications for communications service providers, and its reduction will have a direct impact on operational expenditure as well as Co2 emissions [1]. Hence, design of advanced management schemes recently has focused on maximizing energy efficiency [1]- [8] rather than maximizing throughput [9]- [10]. Additionally, MIMO technology has been a key technology for wireless systems.…”

Section: Introductionmentioning

confidence: 99%

Energy-efficiency of Very Large Multi-user MIMO systems

Ying

Xu²,

et al. 2012

2012 International Conference on Wireless Communications and Signal Processing (WCSP)

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Energy efficiency is becoming increasingly important for wireless communications as mobile devices are battery-constrained. Motivated by this, in this paper we consider uplink energy-efficient resource allocation in Very Large Multi-user MIMO systems. Specifically, both the number of antenna arrays at BS and the transmit power at the user are adjusted to maximize the energy efficiency, in which the power consumption accounts for both transmit power and circuit power. We demonstrate the existence of a unique globally optimal number of antenna arrays at BS and the transmit power and provide iterative algorithms to obtain it. Our simulation results show that the performance of the proposed algorithms is close to the optimum, while having low complexity. It is also found that the distance between the base station and the users plays an important role in increasing the energy efficiency, namely, the energy efficiency is increasing with the distance decreasing.

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