A (Very) Brief Survey on Optimization Methods for Wireless Communication Systems

Guimarães, Antônio Alisson Pessoa; Guerreiro, Igor M.; Sousa, Lígia Maria Carvalho; Moreira, Darlan C.; Maciel, Tarcísio F.; Cavalcante, Charles C.

doi:10.14209/sbrt.2010.111

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…Majorization theory is a topic of much interest in various areas of the mathematics and recently has been applied in problems of wireless communications systems [16]- [19]. The definition of majorization relationship allows to compare two vectors by reordering its coordinates in decreasing order.…”

Section: Majorization Theorymentioning

confidence: 99%

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An Upper-Bound on the Ergodic Capacity of Rayleigh-Fading MIMO Channels using Majorization Theory

Cavalcante¹,

Guimarães²

2012

Anais De XXX Simpósio Brasileiro De Telecomunicações

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In this paper, we investigate the ergodic capacity of multiple-input multiple-output (MIMO) wireless communication systems over spatially uncorrelated Rayleigh-fading channels, assuming that the channel state information (CSI) is unknown at the transmitter and perfectly known at the receiver. Applying some results of majorization theory, we provide an analytical closed-form upper-bound to the ergodic capacity at any signalto-noise ratio (SNR). In addition, we also derive an approximation to the ergodic capacity in high-SNR regimes. Finally, we present numerical results that confirm our theoretical analysis.

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Section: Majorization Theorymentioning

confidence: 99%

“…Applying the expectation operator E {•} in the inequality (19) and observing that the ergodic capacity presented in Eq. 9is equal to E {φ( λ (Γ) )}, we obtain an upper-bound to the ergodic capacity as shown below:…”

Section: Upper-bound On Ergodic Capacitymentioning

confidence: 99%

An Upper-Bound on the Ergodic Capacity of Rayleigh-Fading MIMO Channels using Majorization Theory

Cavalcante¹,

Guimarães²

2012

Anais De XXX Simpósio Brasileiro De Telecomunicações

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“…Hence for improving the efficiency of the wireless services, the application of mathematical optimization methods including classic optimization methods and multiobjective optimization tools plays a key role. Classic optimization methods comprise of integer, semidefinite, linear, and convex optimization, while game theory, majorization theory, and statistical approximations are different multiobjective optimization tools …”

Section: Introductionmentioning

confidence: 99%

Power optimization using optimal small cell arrangements in different deployment scenarios

Gupta

Jha

2017

Int J Communication

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For smooth transition from 4G to 5G, there is a need for optimizing the power in the wireless communication. In 5G, it is expected that the number of users will increase drastically that correspondingly increase the utilization of power in the transmitter and receiver sides. So researchers and academicians are now finding ways to optimize the power. Some optimizing methods like convex optimization are very helpful for optimized algorithm design. In this paper, a proposed mathematical approach for deployment of small cell access point is used for optimizing the power consumption in the massive multiple input and multiple output and small cell scenario. The new proposed mathematical approach will also help in deciding the optimal number of small cell access points and optimal location of these small cell access points for the particular deployment scenario like urban macro heterogeneous deployment scenario in the 3GPP LTE standard and different macro deployment scenario in the ITU-R M.2135 standard like urban macro, suburban macro, and rural macro, for optimizing the power.

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Location Games on Networks: Existence and Efficiency of Equilibria

Fournier

Scarsini

2018

Mathematics of OR

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We consider a game where a finite number of retailers choose a location, given that their potential consumers are distributed on a network. Retailers do not compete on price but only on location, therefore each consumer shops at the closest store. We show that when the number of retailers is large enough, the game admits a pure Nash equilibrium and we construct it. We then compare the equilibrium cost borne by the consumers with the cost that could be achieved if the retailers followed the dictate of a benevolent planner. We perform this comparison in term of the price of anarchy, i.e., the ratio of the worst equilibrium cost and the optimal cost, and the price of stability, i.e., the ratio of the best equilibrium cost and the optimal cost. We show that, asymptotically in the number of retailers, these ratios are bounded by two and one, respectively. MSC Subject Classification: Primary 91A43; secondary 91A06. OR/MS classification: Games/noncooperative.

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A (Very) Brief Survey on Optimization Methods for Wireless Communication Systems

Cited by 4 publications

References 6 publications

An Upper-Bound on the Ergodic Capacity of Rayleigh-Fading MIMO Channels using Majorization Theory

An Upper-Bound on the Ergodic Capacity of Rayleigh-Fading MIMO Channels using Majorization Theory

Power optimization using optimal small cell arrangements in different deployment scenarios

Location Games on Networks: Existence and Efficiency of Equilibria

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