Performance Analysis of Wireless Mesh Backhauling Using Intelligent Reflecting Surfaces

Al‐Jarrah, Mohammad; Alsusa, Emad; Al-Dweik, Arafat; Alouini, Mohamed‐Slim

doi:10.1109/twc.2021.3052370

Cited by 37 publications

(23 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since ( 14) can be used as a direct substitute for [21,Eq. 3], the proposed GKL approximations are also useful for the applications considered in [22]- [25] (and many others that cite [21]) and improve the accuracy of the analysis thereof.…”

Section: Overview Of Applicationsmentioning

confidence: 99%

Generalized Karagiannidis–Lioumpas Approximations and Bounds to the Gaussian Q-Function With Optimized Coefficients

Tanash

Riihonen

2022

IEEE Commun. Lett.

View full text Add to dashboard Cite

We develop extremely tight novel approximations, lower bounds and upper bounds for the Gaussian Q-function and offer multiple alternatives for the coefficient sets thereof, which are optimized in terms of the four most relevant criteria: minimax absolute/relative error and total absolute/relative error. To minimize error maximum, we modify the classic Remez algorithm to comply with the challenging nonlinearity that pertains to the proposed expression for approximations and bounds. On the other hand, we minimize the total error numerically using the quasi-Newton algorithm. The proposed approximations and bounds are so well matching to the actual Q-function that they can be regarded as virtually exact in many applications since absolute and relative errors of 10 −9 and 10 −5 , respectively, are reached with only ten terms. The significant advance in accuracy is shown by numerical comparisons with key reference cases.

show abstract

Section: Overview Of Applicationsmentioning

confidence: 99%

Generalized Karagiannidis–Lioumpas Approximations and Bounds to the Gaussian Q-Function With Optimized Coefficients

Tanash

Riihonen

2022

IEEE Commun. Lett.

View full text Add to dashboard Cite

show abstract

“…In addition, we assume that the TX and RX antennas are pointing towards the center of illuminated RIS region. Furthermore, we note that even in such fixed-topology scenarios the RISs need to be occasionally reconfigured such as in the case of backhaul links in a mesh architecture [14].…”

Section: A System Modelmentioning

confidence: 99%

Autonomous Reconfigurable Intelligent Surfaces Through Wireless Energy Harvesting

Ntontin¹,

Boulogeorgos²,

Björnson³

et al. 2021

Preprint

View full text Add to dashboard Cite

In this paper, we examine the potential for a reconfigurable intelligent surface (RIS) to be powered by energy harvested from information signals. This feature might be key to reap the benefits of RIS technology's lower power consumption compared to active relays. We first identify the main RIS powerconsuming components and then propose an energy harvesting and power consumption model. Furthermore, we formulate and solve the problem of the optimal RIS placement together with the amplitude and phase response adjustment of its elements in order to maximize the signal-to-noise ratio (SNR) while harvesting sufficient energy for its operation. Finally, numerical results validate the autonomous operation potential and reveal the range of power consumption values that enables it.

show abstract

“…The used sets of κ are, κ 3 with 4 reflectors have κ = 20, while κ for the remaining reflectors is uniformly distributed over [0, 1]. On the other hand, κ 4 = [20,20,20,20,20,9,8,7,6,5,4,3,2,1,0]. Both Fig.…”

Section: Performance Evaluationmentioning

confidence: 99%

Optimum Elements Selection in IRS-Assisted UAV Communications with Phase Errors

Jangsher¹,

Al-Dweik²,

Al‐Jarrah³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

<div>This letter considers minimizing the bit error rate (BER) of unmanned aerial vehicle (UAV) communications assisted by intelligent reflecting surfaces (IRSs). By noting that increasing the number of IRS elements in the presence of phase errors does not necessarily improve the BER, it is crucial to use only the elements that contribute to reducing the BER. Consequently, we propose an efficient algorithm to activate only the elements that improve the BER. The proposed algorithm has lower complexity and comparable BER to the optimum selection process, which is an NP-hard problem. The accuracy of the estimated phase is evaluated by deriving the probability distribution function (PDF) of the least-square (LS) channel estimator, and showing that the PDF can be closely approximated by the von Mises distribution at high signal-to-noise ratios (SNRs). The obtained analytical and simulation results show that using all the available reflectors can significantly deteriorate the BER, and thus, elements’ selection is necessary. In particular scenarios, using about 26% of the reflectors provides more than 10 fold BER reduction.</div>

show abstract

Performance Analysis of Wireless Mesh Backhauling Using Intelligent Reflecting Surfaces

Cited by 37 publications

References 67 publications

Generalized Karagiannidis–Lioumpas Approximations and Bounds to the Gaussian Q-Function With Optimized Coefficients

Generalized Karagiannidis–Lioumpas Approximations and Bounds to the Gaussian Q-Function With Optimized Coefficients

Autonomous Reconfigurable Intelligent Surfaces Through Wireless Energy Harvesting

Optimum Elements Selection in IRS-Assisted UAV Communications with Phase Errors

Contact Info

Product

Resources

About