An IRS-Enabled Phase Cooperative Framework for Sum Rate Maximization in B5G Networks

Intelligent reflecting surfaces (IRSs) improves beyond fifth generation (B5G) systems performance in power- and cost-efficient ways. However, maintaining the performance of multiple IRSs-enabled networks without constraining available resources is challenging. In this paper, we propose a novel IRS-assisted phase cooperative framework to maximize the sum rate of the secondary phase cooperative system (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {SPC}_{\mathcal {S}ys}$</tex-math></inline-formula>) located in close proximity of the primary phase cooperative system (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {PPC}_{\mathcal {S}ys}$</tex-math></inline-formula>). We exploit transmit beamforming (BF) at base stations (BSs) and phase shift optimization at the IRS with effective phase cooperation between BSs. The maximization problem turns out to be NP-hard, so an alternating optimization is solved for the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {PPC}_{\mathcal {S}ys}$</tex-math></inline-formula> using an exhaustive search method, i.e., the branch-reduce-and-bound (BRB) algorithm, to obtain the optimal solution for active beamformers, and phase optimization is performed using the semidefinite relaxation (SDR) approach. Further, an active BF is carried out at the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {SPC}_{\mathcal {S}ys}$</tex-math></inline-formula> transmitter by utilizing optimal phase shifts of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {PPC}_{\mathcal {S}ys}$</tex-math></inline-formula>. For the proposed framework, the performance of the BRB algorithm is compared with sub-optimal heuristic BF approaches, including transmit minimum-mean-square-error, zero-forcing BF, and maximum-ratio-transmission. The results support the benefits of deploying IRS in wireless networks to improve sum rate performance of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {SPC}_{\mathcal {S}ys}$</tex-math></inline-formula> through effective phase cooperation. The proposed framework significantly reduces the hardware cost of the system without constraining the resources of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {PPC}_{\mathcal {S}ys}$</tex-math></inline-formula>.

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Publication Details

Journal
IEEE Transactions on Network Science and Engineering
Published
2024-11-06
DOI
https://doi.org/10.1109/tnse.2024.3486733
Citations
7
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
1.46
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article

An IRS-Enabled Phase Cooperative Framework for Sum Rate Maximization in B5G Networks

J.M. Cioffi, Ghulam Abbas, Ziaul Haq Abbas, Ahmad Kamal Hassan et al.
7 citations
IEEE Transactions on Network Science and Engineering
Advanced MIMO Systems Optimization
1.46
article

An IRS-Enabled Phase Cooperative Framework for Sum Rate Maximization in B5G Networks

J.M. Cioffi, Ghulam Abbas, Ziaul Haq Abbas, Ahmad Kamal Hassan, Haleema Sadia
article en
7 citations

Abstract

Intelligent reflecting surfaces (IRSs) improves beyond fifth generation (B5G) systems performance in power- and cost-efficient ways. However, maintaining the performance of multiple IRSs-enabled networks without constraining available resources is challenging. In this paper, we propose a novel IRS-assisted phase cooperative framework to maximize the sum rate of the secondary phase cooperative system (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {SPC}_{\mathcal {S}ys}$</tex-math></inline-formula>) located in close proximity of the primary phase cooperative system (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {PPC}_{\mathcal {S}ys}$</tex-math></inline-formula>). We exploit transmit beamforming (BF) at base stations (BSs) and phase shift optimization at the IRS with effective phase cooperation between BSs. The maximization problem turns out to be NP-hard, so an alternating optimization is solved for the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {PPC}_{\mathcal {S}ys}$</tex-math></inline-formula> using an exhaustive search method, i.e., the branch-reduce-and-bound (BRB) algorithm, to obtain the optimal solution for active beamformers, and phase optimization is performed using the semidefinite relaxation (SDR) approach. Further, an active BF is carried out at the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {SPC}_{\mathcal {S}ys}$</tex-math></inline-formula> transmitter by utilizing optimal phase shifts of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {PPC}_{\mathcal {S}ys}$</tex-math></inline-formula>. For the proposed framework, the performance of the BRB algorithm is compared with sub-optimal heuristic BF approaches, including transmit minimum-mean-square-error, zero-forcing BF, and maximum-ratio-transmission. The results support the benefits of deploying IRS in wireless networks to improve sum rate performance of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {SPC}_{\mathcal {S}ys}$</tex-math></inline-formula> through effective phase cooperation. The proposed framework significantly reduces the hardware cost of the system without constraining the resources of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {PPC}_{\mathcal {S}ys}$</tex-math></inline-formula>.

IEEE Transactions on Network Science and EngineeringVol. 12(1)
Government of Khyber Pakhtunkhwa (PK), Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (PK), Stanford University (US)
Openalex Percentile: Top 17%
Advanced MIMO Systems Optimization
1.46
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