First-Order Methods for Energy-Efficient Power Control in Cell-Free Massive MIMO : Invited Paper

Tran, Le-Nam; Ngo, Hien Quoc

doi:10.1109/ieeeconf44664.2019.9048924

Cited by 21 publications

(15 citation statements)

References 8 publications

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“…where E CB k (ξ) is exhibited in (11) and S denotes the feasible set of ξ. It remarks that the objective function f (ξ) is non-differentiable with respect to ξ and the APG method cannot be directly employed to solve problem H CB [30]- [32]. Fortunately, a smoothing technique can be utilized to tackle this issue by recalling a log-sum-exp function [36]…”

Section: A Max-min He For Cb Schemementioning

confidence: 99%

“…to H CB can be determined by implementing the monotone APG method [30]- [32] outlined in Algorithm 1, provided that a sufficiently large λ is available. We detail this algorithm at the top of the next page and denote the corresponding optimal HE for the CB scheme as E CB-Opt f ξ Opt , where ξ Opt is the optimal solution to H CB .…”

Section: A Max-min He For Cb Schemementioning

confidence: 99%

“…In [29], Interdonato et al pointed out that the NCB scheme helps improve the achievable rate by reducing the beamforming gain uncertainty as compared to the CB one, but whether the NCB scheme outperforms the CB scheme in terms of HE is still unclear. Besides, we also design an accelerated projected gradient (APG)-based maxmin fairness power control policy with fast executing speed [30]- [32] to obtain the maximized identical HE and achievable rate. The contributions of this paper are outlined as follows.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Cell-Free IoT Networks With SWIPT: Performance Analysis and Power Control

Zhang

Xia

Zhao

et al. 2022

IEEE Internet Things J.

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In this paper, the performance of simultaneous wireless information and power transfer (SWIPT) in downlink (DL) Internet-of-things (IoT) networks relying on cell-free massive multiple-input multiple-output (CF-mMIMO) technology is investigated. In such a network, the access points (APs) beam radio-frequency (RF) energy toward the IoT sensors during the DL phase of wireless power transfer. Tight closed-form expressions for the DL harvested energy (HE) and achievable rate with conjugate beamforming (CB) and normalized CB (NCB) are respectively derived, which enable us to analyze the HErate trade-offs under different precoding techniques. Apart from this, to guarantee the sensor fairness with respect to the HE and achievable rate, a max-min fairness power control algorithm based on the accelerated projected gradient (APG) method is proposed. Specifically, the proposed APG-based algorithm is able to determine the optimum of the considered max-min fairness problem in closed form and is more memory-efficient than traditional convex-solver-based counterparts. These analytical results as well as the effectiveness of the proposed power control policy are verified by experimental simulations.Index Terms-Simultaneous wireless information and power transfer (SWIPT), Internet-of-things (IoT), cell-free massive multiple-input multiple-output (CF-mMIMO), max-min power control, accelerated projected gradient (APG).

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Section: A Max-min He For Cb Schemementioning

confidence: 99%

Section: A Max-min He For Cb Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cell-Free IoT Networks With SWIPT: Performance Analysis and Power Control

Zhang

Xia

Zhao

et al. 2022

IEEE Internet Things J.

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“…Centralized deep learning-based power control strategies that get closer to the optimal MMF have been proposed in [128][129][130]. Methods for downlink power control are investigated in [131,132] aiming to reduce the complexity of existing solutions based on second-order optimization. Partial distributed downlink power control schemes based on inverse leakage and successive convex approximation are proposed in [133].…”

Section: The Power Control Scheme Proposed In Paper B Is Obtained By mentioning

confidence: 99%

Cell-Free Massive MIMO : Scalability, Signal Processing and Power Control

Interdonato

2020

Linköping Studies in Science and Technology. Dissertations

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Linköping 2020 This is a Swedish Doctor of Philosophy thesis. The Doctor of Philosophy degree comprises 240 ECTS credits of postgraduate studies. Cover: Illustration of the Ericsson Radio Stripes concept, co-invented by the author of this thesis. The Radio Stripes constitute a way to implement a cell-free massive MIMO system. They aim at enabling invisible, low-cost deployment of large number of distributed access points in the vicinity of the users. This is achieved by serial integration of several transmitting and receiving components into a cable (or stripe) which also provides fronthaul communication and power supply.

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“…To this end, we propose a novel low-complexity method, called the accelerated projected gradient (APG) method, which is derived from a gradient based method for nonconvex programming in [23]. A similar method has been used in [24] to solve the EEmax problem. In particular, the proposed method can deal with the four considered utility functions in a unified framework.…”

Section: Introductionmentioning

confidence: 99%

Utility Maximization for Large-Scale Cell-Free Massive MIMO Downlink

Farooq

Ngo

Hong

et al. 2021

IEEE Trans. Commun.

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We consider utility maximization problems in the downlink cell-free massive multiple-input multiple-output (MIMO) whereby a large number of access points (APs) simultaneously serve a group of users. Four fundamental maximization objectives are of interest: (i) average spectral efficiency (SE), (ii) proportional fairness, (iii) harmonic-rate, and (iv) minimum SE of all users, subject to a sum power constraint at each AP. As considered problems are non-convex, existing solutions normally rely on successive convex approximation (SCA) and use off-the-shelf convex solvers, which implement an interior-point algorithm, to solve derived convex problems. The complexity of such methods scales quickly with the problem size. Therefore, we propose an accelerated projected gradient method to solve the considered problems. Particularly, each iteration of the proposed solution is given in a closed form and only requires the first order oracle of the objective, rather than the Hessian matrix as in known solutions, and thus is much more memory efficient. Numerical results demonstrate that our proposed solution achieves the same utility performance but with far less run-time, compared to the SCA method. Simulation results show that large-scale cell-free massive MIMO has the intrinsic user fairness, i.e. the four utility functions can deliver nearly uniformed services to all users.

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First-Order Methods for Energy-Efficient Power Control in Cell-Free Massive MIMO : Invited Paper

Cited by 21 publications

References 8 publications

Cell-Free IoT Networks With SWIPT: Performance Analysis and Power Control

Cell-Free IoT Networks With SWIPT: Performance Analysis and Power Control

Cell-Free Massive MIMO : Scalability, Signal Processing and Power Control

Utility Maximization for Large-Scale Cell-Free Massive MIMO Downlink

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