Users Selection and Resource Allocation in Intelligent Reflecting Surfaces Assisted Cellular Networks

This paper proposes an architecture based on Intelligent Reflecting Surfaces (IRSs) to improve the performance of future cellular networks. Specifically, we investigate the use of IRSs in combination with statistical Channel State Information (CSI) to enhance the coverage of Base Stations (BSs) in Multiple-Input Single-Output (MISO) systems. Furthermore, we exploit IRSs to reduce the complexity of the proposed architecture, and therefore the total cost, by reducing the number of required antennas at the transmitters (i.e., BSs). At first, we consider a Rayleigh fading channel between the transmitter and the receiver, and we assume the existence of a Line of Sight (LoS) between the BS and the IRS, as well as between the IRS and the destination. In the second part, we investigate the case of a Single-User Multiple-Input Single-Output (SU-MISO) system, where we study the benefits of IRSs in terms of coverage of the BS; then, we formulate a problem for a Multi-User Multiple-Input Single-Output (MU-MISO) system where the IRS is considered as a block of resources that can assist a certain number of users. The problem of managing the IRS resources is formulated as a nonlinear integer problem. We solve the optimization problem using an exhaustive search and propose two low-complexity heuristic algorithms. The performance of the system is evaluated with respect to a variable number of users, the position of the IRS, the required SNR, and the size of the cell. Simulation results corroborate the proposed approach and show that the introduction of the IRS in the network architecture enhances the overall performance of the network, extends the coverage area, enhances users’ satisfaction, and improves the SNR value, while optimizing the required number of antennas at the BS.

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“…First, the IRS must be close the BS to efficiently assist the users [31]. We randomly distribute a number of users in the cell.…”

Section: Proposed Algorithmsmentioning

confidence: 99%

MISO System with Intelligent Reflecting Surface-Assisted Cellular Networks

et al. 2023

Self Cite

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“…The joint design of time allocation, cooperative beamforming, and the reflection coefficients for RIS aided cellular and wireless powered sensor networks have been considered in [ 6 ]. The RIS with its elements grouped in blocks assisting multiple users has been formulated, and two heuristics have been proposed to solve them in [ 7 ]. The user association strategy with the user mobility for RIS-aided multi-beam transmission systems have been considered in [ 8 ], and the ON/OFF selection of RIS in a massive RIS aided wireless communications has been proposed in [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…The resource allocation of RIS-aided dual connectivity has been presented in [ 10 ]. The prospective use cases of 6G includes RIS assisting wireless networks [ 1 ], NOMA [ 3 ], edge computing [ 11 ], etc., as in [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Resource Allocation and Sharing Methodologies When Reconfigurable Intelligent Surfaces Meet Multiple Base Stations

Ramamoorthi

Ohmiya

Iwabuchi

et al. 2022

Sensors

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The 6G wireless systems are expected to have higher capacity, reliability, and energy efficiency than the existing cellular systems. Millimeter-wave (mmWave) frequencies offer high capacity at the cost of high attenuation and blockage losses. Reconfigurable intelligent surface (RIS) assisted mmWave networks consist of smaller antenna elements that control the propagation channel between the base station (BS) and the user by appropriately tuning the phase and the reflection of the incident electromagnetic signal. The deployment of RIS is considered to be an energy efficient solution to improve the coverage of regions with high blocking probability. However, if every BS is associated with one or more dedicated RIS, then the density of RIS increases proportionally with the density of BSs. Hence in this work, we propose RIS sharing mechanisms where multiple BSs share one RIS. We formulate resource allocation of RIS sharing in terms of time and the RIS elements as an optimization problem, and we propose heuristics to solve both. Further, we present detailed simulation results to compare time and the element based RIS sharing methods for various scenarios with the benchmark and the RIS system without sharing. The proposed time and element based RIS sharing methods improve throughput upto 53% and 25%, respectively, compared to the RIS system without sharing in specific scenarios.

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A Survey on Resource Allocation and Energy Efficient Maximization for IRS-Aided MIMO Wireless Communication

Baskar,

Selvaprabhu,

Kumaravelu

et al. 2024

IEEE Access

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