Energy and Spectral Efficiency Tradeoff With User Association and Power Coordination in Massive MIMO Enabled HetNets

Hao, Yuanyuan; Ni, Qiang; Hai, Li; Hou, Shujuan

doi:10.1109/lcomm.2016.2597832

Cited by 37 publications

(34 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The energy efficient resource optimization for HetNets has been investigated extensively [8]- [15]. In [8], energy efficient user association is optimized to minimize the total power consumption.…”

Section: Introductionmentioning

confidence: 99%

“…In [14], the summation of users' EE is maximized with the optimization of user association. Recently, the tradeoff between EE and SE is studied in our earlier work [15], where the user association and power coordination are jointly optimized.…”

Section: Introductionmentioning

confidence: 99%

“…However, in the aforementioned studies [8]- [15], the constraint of backhaul capacity between BSs and the core network is not considered. With the employment of dense small cells and large-scale antenna arrays in macro BSs, there will be enormous data transmissions over backhaul links, while current backhaul solutions can not provide sufficient capacity [16], [17] and has become one of crucial performance constraints [18], [19].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On the Energy and Spectral Efficiency Tradeoff in Massive MIMO-Enabled HetNets With Capacity-Constrained Backhaul Links

Hao

et al. 2017

IEEE Trans. Commun.

Self Cite

View full text Add to dashboard Cite

In this paper, we propose a general framework to study the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in massive MIMO enabled HetNets while ensuring proportional rate fairness among users and taking into account the backhaul capacity constraint. We aim at jointly optimizing user association, spectrum allocation, power coordination, and the number of activated antennas, which is formulated as a multi-objective optimization problem maximizing EE and SE simultaneously. With the help of weighted Tchebycheff method, it is then transformed into a single-objective optimization problem, which is a mixed-integer non-convex problem and requires unaffordable computational complexity to find the optimum. Hence, a low-complexity effective algorithm is developed based on primal decomposition, where we solve the power coordination and number of antenna optimization problem and the user association and spectrum allocation problem separately. Both theoretical analysis and numerical results demonstrate that our proposed algorithm can fast converge within several iterations and significantly improve both the EE-SE tradeoff performance and rate fairness among users compared to other algorithms.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On the Energy and Spectral Efficiency Tradeoff in Massive MIMO-Enabled HetNets With Capacity-Constrained Backhaul Links

Hao

et al. 2017

IEEE Trans. Commun.

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, in [11] and [12], the MEC server is only located at the macro base station (MBS) and massive MIMO is not taken into account for uplink transmission. As shown in the recent studies [13]- [15], the combination of massive MIMO and HetNets can boost the system EE and SE. Nevertheless, as far as we know, the performances of MEC in massive MIMO enabled HetNets have not been evaluated in the existing literature, where the inter-cell interference should be taken into account.…”

Section: Introductionmentioning

confidence: 86%

Energy-Efficient Multi-User Mobile-Edge Computation Offloading in Massive MIMO Enabled HetNets

Hao

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

Self Cite

View full text Add to dashboard Cite

In this paper, we investigate the energy-efficient multiuser mobile-edge computing offloading problem in massive MIMO enabled HetNets, where the CPU-cycle frequency of mobile devices, uplink power control, computational task offloading ratio and uplink transmission duration are jointly optimized. The problem is formulated as minimizing the energy consumption of all mobile devices while satisfying the maximum latency requirement. Specifically, to address this non-convex problem, a low-complexity algorithm is proposed relied on alternating optimization, where we address the joint computational task offloading ratio and uplink transmission duration optimization problem and the uplink power control problem iteratively. Besides, the effectiveness and convergence of the proposed iterative algorithm are analytically studied. Numerical results demonstrate that our proposed algorithm consumes less energy compared to local computing and full uploading schemes, and the application of massive MIMO in HetNets helps to reduce energy consumption of mobile devices.

show abstract

“…Extensive research on massive MIMO has focused on, for example, spectral efficiency analysis, energy efficiency resource optimization, and trade‐off between spectral and energy efficiency . Also, some works on massive MIMO systems over general fading channels have been reported in previous studies .…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of achievable sum‐rate for downlink massive MIMO systems

Wang

2019

Int J Communication

View full text Add to dashboard Cite

Massive multiple-input and multiple-output (MIMO) has been recognized as a promising technology in the fifth-generation wireless networks. Under perfect channel state information, we derive three tractable closed-form expressions that corresponding to the lower bound, approximation, and upper bound on the achievable rate in a massive MIMO downlink system with maximum-ratio transmission precoding. Based on the proposed closed-form expressions, the power efficiency of the system is investigated as the number of transmit antennas increases. Simulation results demonstrate the tightness of our proposed closed-form expressions for the achievable sum-rate. KEYWORDSachievable sum-rate, approximation, lower bound, massive MIMO, upper bound Int J Commun Syst. 2020;33:e4232.wileyonlinelibrary.com/journal/dac

show abstract

Energy and Spectral Efficiency Tradeoff With User Association and Power Coordination in Massive MIMO Enabled HetNets

Cited by 37 publications

References 13 publications

On the Energy and Spectral Efficiency Tradeoff in Massive MIMO-Enabled HetNets With Capacity-Constrained Backhaul Links

On the Energy and Spectral Efficiency Tradeoff in Massive MIMO-Enabled HetNets With Capacity-Constrained Backhaul Links

Energy-Efficient Multi-User Mobile-Edge Computation Offloading in Massive MIMO Enabled HetNets

Performance analysis of achievable sum‐rate for downlink massive MIMO systems

Contact Info

Product

Resources

About