On the Distribution of the Sum of Double-Nakagami-$m$ Random Vectors and Application in Randomly Reconfigurable Surfaces

Tegos, Sotiris A.; Tyrovolas, Dimitrios; Diamantoulakis, Panagiotis D.; Karagiannidis, George K.

doi:10.1109/tvt.2022.3164846

Cited by 62 publications

(27 citation statements)

References 26 publications

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“…We also investigate the approximation of the interference power from an interfering TX with an assisting RIS, I 1,k . In order to illustrate the performance gain brought by RIS reflect beamforming, we assume the coordinates of the interfering TX and its corresponding RIS are also (0, 20) and (3,20), respectively. Furthermore, as indicated in Remark 3, the shape parameter of the Nakagami-m distribution will not affect the interference distribution due to the lack of reflect beamforming.…”

Section: B Analysis Of Approximate Distributionsmentioning

confidence: 99%

“…All the above works considered the Rayleigh fading channel model. To further investigating the general channel environment, the Nakagami-m fading model was applied in [19], [20]. For example, the authors in [19] derived the outage probability of a RIS aided network without phase errors over Nakagami-m channels in an integral form by using the Gil-Pelaez theorem.…”

Section: Introductionmentioning

confidence: 99%

“…For example, the authors in [19] derived the outage probability of a RIS aided network without phase errors over Nakagami-m channels in an integral form by using the Gil-Pelaez theorem. Under the random phase-shifting scheme where the phase errors are uniformly distributed over (0, 2π), the authors in [20] derived the outage probability in closed form by assuming Nakagami-m fading channels. Recently, the effects of channel correlations were investigated in [21] and [22], where the outage probability of a RIS-assisted wireless network over correlated channels with random and coherent phase-shifting schemes were derived.…”

Section: Introductionmentioning

confidence: 99%

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Performance Analysis of RIS-Assisted Large-Scale Wireless Networks Using Stochastic Geometry

Wang¹,

Chen²,

Badiu³

et al. 2022

Preprint

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In this paper, we investigate the performance of a reconfigurable intelligent surface (RIS) assisted large-scale network by characterizing the coverage probability and the average achievable rate using stochastic geometry. Considering the spatial correlation between transmitters (TXs) and RISs, their locations are jointly modelled by a Gauss-Poisson process (GPP). Two association strategies, i.e., nearest association and fixed association, are both discussed. For the RIS-aided transmission, the signal power distribution with a direct link is approximated by a gamma random variable using a moment matching method, and the Laplace transform of the aggregate interference power is derived in closed form. Based on these expressions, we analyze the channel hardening effect in the RIS-assisted transmission, the coverage probability, and the average achievable rate of the typical user. We derive the coverage probability expressions for the fixed association strategy and the nearest association strategy in an interference-limited scenario in closed form. Numerical results are provided to validate the analysis and illustrate the effectiveness of RIS-assisted transmission with passive beamforming in improving the system performance. Furthermore, it is also unveiled that the system performance is independent of the density of TXs with the nearest association strategy in the interference-limited scenario.

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Section: B Analysis Of Approximate Distributionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Performance Analysis of RIS-Assisted Large-Scale Wireless Networks Using Stochastic Geometry

Wang¹,

Chen²,

Badiu³

et al. 2022

Preprint

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“…It is noted that this indicative example is also used for the evaluation of cascaded RIS networks in Section IV. It should be highlighted that even if a small amount of power impinges upon a RIS that does not participate in the selected route or is not configured properly, the impinging power will be randomly reflected across the space due to the random configuration of the RISs, thus, the GN can be served only via the selected RIS-route [6].…”

Section: System Modelmentioning

confidence: 99%

“…In more detail, RISs are thin programmable surfaces consisting of reflecting elements, whereby tuning their phase profile, the desired reflection coefficient is constructed leading to the realization of different electromagnetic functions (i.e., beamforming, diffusion etc.). Therefore, to enhance the wireless network's coverage, a RIS can be appropriately configured in order to act as a passive beamformer and steer its impinging signal towards the desired direction [5], [6]. Thus, by deploying multiple RISs across the propagation environment, it can be converted from an uncontrollable entity to an optimizable parameter, able to provide wireless connectivity seamlessly [7].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Cascaded Reconfigurable Intelligent Surface Networks

Tyrovolas¹,

Tegos²,

Panidou³

et al. 2022

Preprint

Self Cite

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Reconfigurable intelligent surfaces (RIS) have been presented as a solution to realize the concept of smart radio environments, wherein uninterrupted coverage and extremely high quality of service can be ensured. In this paper, assuming that multiple RIS are deployed in the propagation environment, the performance of a cascaded RIS network affected by imperfect phase estimation is evaluated. Specifically, we derive closed-form expressions for the outage probability, the ergodic capacity and the average symbol error probability that can be utilized to evaluate the coverage of the proposed network, as well as the average capacity and the data transmission accuracy. Finally, we validate the derived expressions through simulations and show that by choosing the number of the participating RIS correctly, a cascaded RIS network can outperform a single RIS-aided system and extend the network's coverage efficiently.

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On the performance of multiple‐IRS aided wireless networks over Nakagami‐m fading channels

Hindustani,

Dixit,

Sharma

2024

Int J Communication

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SummaryMultiple intelligent reflecting surfaces (IRS) in a wireless system are considered to enhance performance, efficiency, and flexibility in wireless networks. In this paper, we analyze outage probability (OP) for multiple IRS panels‐assisted wireless systems over Nakagami‐ fading channels. We focus on selecting the best IRS panel to maintain the quality of service and enhance the user experience. We derive two closed‐form OP expressions using the central limit theorem and Laguerre series expansion. Additionally, we develop a novel asymptotic OP expression and obtain a novel diversity order. The diversity order of the considered system model depends on the minimum fading parameter ( ) between the transmitter‐IRS panel and IRS panel‐receiver links and the number of IRS panels. We thoroughly investigate the impact of system parameters and validate our analytical results with simulations. Our findings emphasize that diversity order depends on the minimum fading parameter ( ) between the transmitter‐IRS panel and IRS panel‐receiver links, the number of IRS elements in each panel, and the number of IRS panels.

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On the Distribution of the Sum of Double-Nakagami-$m$ Random Vectors and Application in Randomly Reconfigurable Surfaces

Cited by 62 publications

References 26 publications

Performance Analysis of RIS-Assisted Large-Scale Wireless Networks Using Stochastic Geometry

Performance Analysis of RIS-Assisted Large-Scale Wireless Networks Using Stochastic Geometry

Performance Analysis of Cascaded Reconfigurable Intelligent Surface Networks

On the performance of multiple‐IRS aided wireless networks over Nakagami‐m fading channels

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