On Some Properties of Programming Problems in Parametric form Pertaining to Fractional Programming

Jagannathan, R.

doi:10.1287/mnsc.12.7.609

Cited by 139 publications

(65 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then, since all the constraint functions in (37) and (38) are monotonic and continuous, by virtue of Proposition 2 and employing again (35), it follows that S and S c are normal and co-normal sets in the hyper-rectangle given by:…”

Section: Global Optimality: Monotonic Fractional Programmingmentioning

confidence: 99%

Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks

Zappone

Björnson

Sanguinetti

et al. 2017

IEEE Trans. Signal Process.

237

228

View full text Add to dashboard Cite

Abstract-The characterization of the global maximum of energy efficiency (EE) problems in wireless networks is a challenging problem due to the non-convex nature of investigated problems in interference channels. The aim of this work is to develop a new and general framework to achieve globally optimal solutions. First, the hidden monotonic structure of the most common EE maximization problems is exploited jointly with fractional programming theory to obtain globally optimal solutions with exponential complexity in the number of network links. To overcome this issue, we also propose a framework to compute suboptimal power control strategies characterized by affordable complexity. This is achieved by merging fractional programming and sequential optimization. The proposed monotonic framework is used to shed light on the ultimate performance of wireless networks in terms of EE and also to benchmark the performance of the lower-complexity framework based on sequential programming. Numerical evidence is provided to show that the sequential fractional programming framework achieves global optimality in several practical communication scenarios.

show abstract

Section: Global Optimality: Monotonic Fractional Programmingmentioning

confidence: 99%

Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks

Zappone

Björnson

Sanguinetti

et al. 2017

IEEE Trans. Signal Process.

237

228

View full text Add to dashboard Cite

show abstract

“…Problem (4) is a max-min fractional program, for which a common approach is based on solving a parametric program and a two-layer iterative procedure, i.e., a Dinkelbach-type algorithm [9], [10]. As numerically shown in Sect.…”

Section: Proposed Low-complexity Beamforming Designmentioning

confidence: 99%

Achieving Energy Efficiency Fairness in Multicell MISO Downlink

et al. 2015

View full text Add to dashboard Cite

Abstract-We investigate the fairness of achievable energy efficiency in a multicell multiuser multiple-input single-output (MISO) downlink system, where a beamforming scheme is designed to maximize the minimum energy efficiency among all base stations. The resulting optimization problem is a nonconvex max-min fractional program, which is generally difficult to solve optimally. We propose an iterative beamformer design based on an inner approximation algorithm which aims at locating a Karush-Kuhn-Tucker solution to the nonconvex program. By novel transformations, we arrive at a convex problem at each iteration of the proposed algorithm, which is amendable for being approximated by a second order cone program. The numerical results demonstrate that the proposed algorithm outperforms the existing schemes in terms of the convergence rate and processing time.Index Terms-Energy efficiency, max-min fractional programming, inner approximation algorithm.

show abstract

“…Thus, the convergence of the alternating maximization of steps 3-5 in Algorithm 3 can be guaranteed with the monotonic convergence theorem [41]. In the results obtained in [15,39,40], one can see that the convergence of Algorithm 3 is also guaranteed. In particular, based on the conclusion given by [41,Prop.…”

Section: Algorithm Designmentioning

confidence: 87%

“…It is easy to see that problem (28) belongs to a classical fractional programming problem. In addition, the works in [15,39,40] have shown that it is equivalent to looking up a value of α such that the optimal objective value of the following optimization problem (29) equals to zero.…”

Section: Algorithm Designmentioning

confidence: 99%

See 1 more Smart Citation

Coordinated beamforming design for multicell systems with transceiver impairments: from perspective of spectral efficiency to energy efficiency

Huang

Zhang

et al. 2015

J Wireless Com Network

View full text Add to dashboard Cite

Physical transceiver implementations for wireless communication systems usually suffer from transmit-radio frequency (Tx-RF) and receiver-RF (Rx-RF) impairments. In this paper, we aim to design efficient coordinated beamforming for multicell multiuser multi-antenna systems by fully taking into account the residual transceiver impairments. Our design objectives include both spectral efficiency and energy efficiency. In particular, we first derive the closed-form expression of the mean square error (MSE) which includes the impact of transceiver impairments. Based on that, we propose an alternating optimization algorithm to solve the coordinated multicell beamforming problems with the goal of minimizing the worst user MSE, and the sum MSE. Then, by exploiting the relationship between the minimum mean square error (MMSE) and the achievable rate, we develop a new algorithm to address the sum rate maximization problem. This approach is further generalized to solve the more intractable energy efficiency optimization problem. We prove that all the proposed iterative algorithms guarantee to converge to a stationary point. Numerical results show that our proposed schemes achieve a better performance than conventional coordinated beamforming algorithms that were designed ignoring the transceiver impairments.

show abstract

On Some Properties of Programming Problems in Parametric form Pertaining to Fractional Programming

Cited by 139 publications

References 9 publications

Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks

Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks

Achieving Energy Efficiency Fairness in Multicell MISO Downlink

Coordinated beamforming design for multicell systems with transceiver impairments: from perspective of spectral efficiency to energy efficiency

Contact Info

Product

Resources

About