Improving Water-Filling Algorithm to Power Control Cognitive Radio System Based Upon Traffic Parameters and QoS

Hosseini, Elham; Falahati, Abolfazl

doi:10.1007/s11277-012-0778-0

Cited by 16 publications

(4 citation statements)

References 18 publications

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“…Therefore, energy management is a vital problem and must be considered in the process of precoder design. In [7], the authors design an optimal precoder towards minimising an estimation error, employing a water‐filling algorithm and in [8, 9], optimality of linear precoder exploitation on WSNs with Gaussian sensor statistics is obtained. In [10, 11], receive filtering schemes are proposed for the decentralised estimation of an unknown vector parameter with correlated sources, considering only power restrictions.…”

Section: Introductionmentioning

confidence: 99%

Precoder design for decentralised estimation over MIMO‐WSN based on stochastic models

Rostami

Falahati

2018

IET Communications

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Section: Introductionmentioning

confidence: 99%

Precoder design for decentralised estimation over MIMO‐WSN based on stochastic models

Rostami

Falahati

2018

IET Communications

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“…It thus requires the interference power to be below a prescribed threshold, known as the interference temperature constraint [5]. Motivated by this idea, a great deal of valuable scholarly work has been done on the design of optimal power control strategies for CR networks [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Power allocation in cognitive radio networks over Rayleigh-fading channels with hybrid intelligent algorithms

Lam

Wang

2017

Wireless Netw

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In this paper, we introduce a hybrid strategy containing pattern search (PS) optimization and genetic algorithm (GA) to address the problem of power allocation in cognitive radio networks. Considering the fluctuating interference thresholds in cognitive networks, an approach for promoting the coexistence between licensed users and cognitive users is designed first. Then, based on the analysis of transmission outage probability, a corresponding objective function with regard to the power allocation over Rayleigh fading channels is obtained. Due to the nonlinearity and complexity of the optimization problem, it is uneasy to figure it out directly by using traditional methods, such as common mathematical deduction or linear programming. Inspired by the concept of intelligent algorithms, we try to employ the scheme of combining PS optimization and GA method, which are both efficient intelligent algorithms to resolve this difficulty. The reason why we apply a combined algorithm is it can overcome the instability of GA and the local convergency of PS method. Thus, the hybrid intelligent method can attain a global and steady outcome. We improve the performance of power allocation strategy with an acceptable increase of computation burden. The numerical results are encouraging and show the proposed approach is worthy of consideration in finding complicated power optimization. Thus, we achieve steady and rational outcomes by ap-

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“…This problem is a nonlinear constraint optimization problem that is discussed in [5][6][7][8][9]. In [5], the analytical method based on Lagrangian technique is used to solve this problem for a multiuser communication system.…”

Section: Introductionmentioning

confidence: 99%

“…The overlay subcarriers are allocated power according to a ladder profile. PU's activity is statistically considered to control power in SU's network [6]. Since the introduced optimal power allocation in [7] has high complexity, two suboptimal algorithm that are less complexity are proposed.…”

Section: Introductionmentioning

confidence: 99%

An iterative resource allocation algorithm for multi-user OFDM-CR system with low complexity

Falahati

Hosseini

2014

7'th International Symposium on Telecommunications (IST'2014)

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a low complexity resource allocation scheme is proposed for an underlay scheme over OFDM-based multi-user cognitive radio system. The resource allocation problem in an OFDM-based CR system includes subcarrier, power and bit allocation that is a combinational optimization problem. In the proposed scheme, subcarrier and power allocation is accomplished in two separate stages. The power allocation problem under the interference channel model is a constraint optimization problem. It is notable that one of problem complexity source is coupling between the power budget and interference temperature constraints sets. In this algorithm the power budget constraint is used to determine initial point within iterative algorithm. Additionally, a margin parameter that depends on similarity of the interference channel branches is introduced. The simulation results for two statistical models, namely Rayliegh and Nakagami, show that the proposed algorithm performance is close to an optimal solution with lower complexity.Keywords-cognitive radio system, power allocation algorithm, OFDM, dynamic spectrum management.

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Improving Water-Filling Algorithm to Power Control Cognitive Radio System Based Upon Traffic Parameters and QoS

Cited by 16 publications

References 18 publications

Precoder design for decentralised estimation over MIMO‐WSN based on stochastic models

Precoder design for decentralised estimation over MIMO‐WSN based on stochastic models

Power allocation in cognitive radio networks over Rayleigh-fading channels with hybrid intelligent algorithms

An iterative resource allocation algorithm for multi-user OFDM-CR system with low complexity

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