Robust resource allocation for heterogeneous wireless network: a worst‐case optimisation

Xu, Yongjun; Hu, Yuan; Li, Guoquan; Zhang, Haibo

doi:10.1049/iet-com.2017.0626

Cited by 16 publications

(10 citation statements)

References 24 publications

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“…Since the statistical distribution function of channel estimation errors are usually difficult to obtain [37], thus we model the uncertain parameters as the bounded channel uncertainty sets. Based on the spherical uncertainty formulation [38], channel uncertainties can be modeled by…”

Section: A Uncertainty Modelmentioning

confidence: 99%

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Optimal and Robust Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks

Xu¹,

Sun²,

Yang³

et al. 2020

Preprint

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Simultaneous wireless information and power transfer (SWIPT)-enabled cognitive networks (CRNs) is recognized as one of the most promising techniques to improve spectrum efficiency and prolong operation lifetime in 5G and beyond. However, existing methods focus on the centralized algorithm and the power allocation under perfect channel state information (CSI). The analytical solution and the impact of power splitting (PS) on the optimal power allocation strategy are not addressed. In addition, the influence of the PS factor on the feasible region of transit power is rarely analyzed. In this paper, we propose a joint power allocation and PS algorithm under perfect CSI and imperfect CSI, respectively, for multiuser SWIPT-enabled CRNs scenarios. The power minimization of resource allocation problem is formulated as a multivariate nonconvex optimization which is hard to obtain the closed-form solution. Hence, we propose a suboptimal algorithm to alternatively optimize the power allocation and PS coefficient under the cases of the low-harvested energy region and the high-harvested energy region, respectively. Moreover, a closed-form distributed power allocation and PS expressions are derived by the Lagrangian approach. Simulation results confirm the proposed method with good robustness and high energy efficiency.

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Section: A Uncertainty Modelmentioning

confidence: 99%

“…Based on the worst-case approach and the Cauchy-Buniakowsky-Schwarz inequality [38], the interference temperature constraint C 1 with channel uncertainties can be reformulated as Similarly, the worst-case SINR of each SU is given by…”

Section: B Transformation Of Robust Constraintmentioning

confidence: 99%

Optimal and Robust Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks

Xu¹,

Sun²,

Yang³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Since the statistical distribution function of channel estimation errors are usually difficult to obtain [36], thus we model the uncertain parameters as the bounded channel uncertainty sets. Based on the spherical uncertainty formulation [37], channel uncertainties can be modeled by…”

Section: A Uncertainty Modelmentioning

confidence: 99%

“…Based on the worst-case approach and the Cauchy-Buniakowsky-Schwarz inequality [37], the interference temperature constraint C 1 with channel uncertainties can be reformulated as…”

Section: B Transformation Of Robust Constraintmentioning

confidence: 99%

Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks With and Without Perfect CSI

Xu¹,

Sun²,

Wang³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Simultaneous wireless information and power transfer (SWIPT)-enabled cognitive networks (CRNs) is recognized as one of most promising techniques to improve spectrum efficiency and prolong operation lifetime in 5G and beyond. However, existing methods focus on the centralized algorithm and the power allocation under perfect channel state information (CSI). The analytical solution and the impact of the power splitting (PS) on the optimal power allocation strategy are not addressed. In addition, the influence of the PS factor on the feasible region of transit power is rarely analyzed. In this paper, we propose a joint power allocation and PS algorithm under perfect CSI and imperfect CSI, respectively, for multiuser SWIPT-enabled CRNs scenarios. The power minimization of resource allocation problem is formulated as a multivariate nonconvex optimization which is hard to obtain the closed-form solution. Hence, we propose a suboptimal algorithm to alternatively optimize the power allocation and PS coefficient under the cases of the low-harvested energy region and the high-harvested energy region, respectively. Moreover, a closed-form distributed power allocation and PS expressions are derived by the Lagrangian approach. Simulation results confirm the proposed method with good robustness and high energy efficiency.

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“…With the tremendous increasing requirement of multimedia data transmission and energy saving, energy efficiency (EE) has become the key issue for CR networks in recent researches [14]- [18]. In [14], energy consumption and access strategy is considered in both half-duplex and full-duplex CR network.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficiency Optimization for multiuser OFDM-based Cognitive Heterogeneous networks

2019

KSII TIIS

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Reducing the interference to the licensed mobile users and obtaining the energy efficiency are key issues in cognitive heterogeneous networks. A corresponding rate loss constraint is proposed to be used for the sensing-based spectrum sharing (SBSS) model in cognitive heterogeneous networks in this paper. Resource allocation optimization strategy is designed for the maximum energy efficiency under the proposed interference constraint together with average transmission power constraint. An efficiency algorithm is studied to maximize energy efficiency due to the nonconvex optimal problem. Furthermore, the relationship between the proposed protection criterion and the conventional interference constraint strategy under imperfect sensing condition for the SBSS model is also investigated, and we found that the conventional interference threshold can be regarded as the upper bound of the maximum rate loss that the primary user could tolerate. Simulation results have shown the effectiveness of the proposed protection criterion overcome the conventional interference power constraint.

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Robust resource allocation for heterogeneous wireless network: a worst‐case optimisation

Cited by 16 publications

References 24 publications

Optimal and Robust Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks

Optimal and Robust Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks

Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks With and Without Perfect CSI

Energy Efficiency Optimization for multiuser OFDM-based Cognitive Heterogeneous networks

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