Wireless Network Coding With Intelligent Reflecting Surfaces

Kafizov, Amanat; Elzanaty, Ahmed; Varshney, Lav R.; Alouini, Mohamed‐Slim

doi:10.1109/lcomm.2021.3098750

Cited by 8 publications

(3 citation statements)

References 29 publications

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“…The position of the UE can be obtained from the estimated parameters, e.g., the angles and distances. 3 We consider the location of BS as the reference frame. The location of the scatterers between the BS and RIS, p S,BR = [x S,BR , y S,BR ], can be estimated as xS,BR…”

Section: Positioningmentioning

confidence: 99%

Compressive Near-Field Localization for Multipath RIS-Aided Environments

2022

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Reconfigurable intelligent surfaces (RISs) are considered among the key techniques to be adopted for sixthgeneration cellular networks (6G) to enhance not only communications but also localization performance. In this regard, we propose a novel single-anchor localization algorithm for a stateof-the-art architecture where the position of the user equipment (UE) is to be estimated at the base station (BS) with the aid of a RIS. We consider a practical model that accounts for both nearfield propagation and multipath environments. The proposed scheme relies on a compressed sensing (CS) technique tailored to address the issues associated with near-field localization and model mismatches. Also, the RIS phases are optimized to enhance the positioning performance, achieving more than one order of magnitude gain in the localization accuracy compared to RISs with non-optimized phases.

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Section: Positioningmentioning

confidence: 99%

Compressive Near-Field Localization for Multipath RIS-Aided Environments

2022

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“…The authors demonstrated that the presence of the RIS significantly enhances the performance of the PNC scheme. [24] presented a RIS enabled PNC transmission scheme for data transmission between two transmitting devices and two receiving devices facilitated by a common RIS and a relay device. In [25], closedform BER expressions for the RIS enabled SISO-PNC system have been derived.…”

Section: Introductionmentioning

confidence: 99%

Phase Shift Optimization for RIS Enabled PNC System With Multiple Antennas

İlgüy,

Özbek,

Musavian

et al. 2024

IEEE Access

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Reconfigurable intelligent surfaces (RISs) have been developed to exploit the stochastic characteristics of the propagation environment. On the other hand, the integration of wireless physical network coding (PNC) and multiple antennas yields notable enhancements in system performance. This paper presents a multi-user system, employing RIS enabled PNC alongside multiple antennas to minimize both latency and error probability. Our aim is to establish reliable communication between the user pairs, which communicate through a base station (BS) via RIS. Therefore, the reflecting coefficients including both phases and amplitudes of the RISs are optimized by using the alternating direction method of multipliers (ADMM) algorithm for both single and multiple RIS cases. Extensive results are presented to compare the proposed algorithm with random phase shift, network coding (NC) and the search algorithm to illustrate the superiority of the proposed method.

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“…Several studies have been conducted on solving the challenges of beamforming and phase shift design in an RISaided multi-user MIMO scenario with different objectives [4]- [14] such as maximization of the sum rate [4], [5], spectral efficiency [6] and energy efficiency [7], [8] or minimization Fig. 1: The system model of the transmission power [9], max-min SINR problem [10], [11], and the exposure to electromagnetic fields [12], [13].…”

Section: Introductionmentioning

confidence: 99%

MU-Massive MIMO With Multiple RISs: SINR Maximization and Asymptotic Analysis

Aghashahi

Zeinalpour-Yazdi

Tadaion

et al. 2023

IEEE Wireless Commun. Lett.

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In this letter, we investigate the signal-tointerference-plus-noise-ratio (SINR) maximization problem in a multi-user massive multiple-input-multiple-output (massive MIMO) system enabled with multiple reconfigurable intelligent surfaces (RISs). We examine two zero-forcing (ZF) beamforming approaches for interference management namely BS-UE-ZF and BS-RIS-ZF that enforce the interference to zero at the users (UEs) and the RISs, respectively. Then, for each case, we resolve the SINR maximization problem to find the optimal phase shifts of the elements of the RISs. Also, we evaluate the asymptotic expressions for the optimal phase shifts and the maximum SINRs when the number of the base station (BS) antennas tends to infinity. We show that if the channels of the RIS elements are independent and the number of the BS antennas tends to infinity, random phase shifts achieve the maximum SINR using the BS-UE-ZF beamforming approach. The simulation results illustrate that by employing the BS-RIS-ZF beamforming approach, the asymptotic expressions of the phase shifts and maximum SINRs achieve the rate obtained by the optimal phase shifts even for a small number of the BS antennas.

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Wireless Network Coding With Intelligent Reflecting Surfaces

Cited by 8 publications

References 29 publications

Compressive Near-Field Localization for Multipath RIS-Aided Environments

Compressive Near-Field Localization for Multipath RIS-Aided Environments

Phase Shift Optimization for RIS Enabled PNC System With Multiple Antennas

MU-Massive MIMO With Multiple RISs: SINR Maximization and Asymptotic Analysis

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