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Behrooz Makki

Publications and source records attributed to Behrooz Makki.

At least 19 recordsLinked to original sources

Deconstructing the Composite Channel for Beyond Diagonal RIS: Channel Estimation and Beamforming Design

As beyond-diagonal reconfigurable intelligent surfaces (BD-RISs) gain increasing attention in high-frequency wireless communications, accurate and scalable channel-estimation methods become essential. This paper develops a parametric channel-estimation and beamforming framework that deconstructs the composite BD-RIS channel into its generating directional factors, revealing the tensor structure induced jointly by propagation geometry and beyond-diagonal scattering. We propose two tensor-based estimators: Fourth-Order Tucker Channel Estimation (FORTE), which models the partially structured channel as a fourth-order Tucker tensor, and Fourth-Order PARAFAC Channel Estimation (FORPE), which captures the fully structured channel through a fourth-order PARAFAC model. By exploiting partial and full channel geometry, the proposed methods achieve higher estimation accuracy than Least Squares and Block Tucker Kronecker Factorization benchmarks. In particular, FORTE outperforms FORPE due to its more compact representation, attaining an NMSE of about 10^{-4} at 5 dB SNR. In contrast, FORPE provides essentially unique estimates of the composite-channel factor matrices, whereas FORTE identifies their subspaces. The proposed deconstruction also provides a structured representation useful for sensing-oriented parameter extraction and tensor-structured system optimization. Finally, the Tensor Optimization Framework for Beamforming, Combining, and Scattering (TenFormer) achieves spectral efficiency comparable to the benchmark design while significantly reducing computational complexity through parallel tensor-structured optimization.

eess.SP

Low-Complexity Tensor-Based Monostatic Sensing for IRS-Assisted Communication Systems

This paper proposes a tensor-based parameter estimation algorithm for sensing in an intelligent reflecting surface-assisted system. We present a higher-order singular value decomposition-based solution that exploits the tensor structure of the received echo signal to jointly estimate the target's delay, Doppler, and angular information. Our tensor-based solution can estimate the parameters individually at low complexity, benefiting from parallel computation. Complexity analysis is carried out in comparison with a baseline scheme that does not exploit the intrinsic multilinear structure of the sensed signal. Simulation results show that our proposed tensor-based method can achieve the same performance as the reference method while drastically reducing the computational complexity.

eess.SP

PARAFAC-Based Time-Varying Channel Estimation for IRS-Aided Communications

This paper proposes a tensor-based parametric channel estimation technique for IRS-assisted communication systems with time-varying channel parameters. We exploit the multidimensional structure of the received signal by developing a $3$rd-order PARAFAC tensor model that is solved by employing the iteratively ALS algorithm. Our simulation results show that the proposed approach provides enhanced performance in terms of NMSE of the concatenated channel compared to the competing solutions by capitalizing on the intrinsic tensor structure of the received signal without increasing the computational complexity of the channel estimation.

eess.SP

Decoupled Delay-Doppler and Angle Estimation in BD-RIS Sensing via Nested Tucker Decomposition

We study single-target localization in a group-connected beyond-diagonal reconfigurable intelligent surface (BD-RIS)-assisted monostatic network with K element groups. We propose a Nested Tensor Factorization and Estimation (NTFE) algorithm that models the received signal as a 3rd-order nested Tucker tensor, decoupling the delay-Doppler and angle domains. The resulting two-stage procedure estimates the target-bearing tensor factors and then extracts the other physical parameters using subspace and closed-form steps. We also analyze identifiability and uniqueness conditions. Simulations show that NTFE exploits the group-connected BD-RIS structure and outperforms state-of-the-art sensing benchmarks.

eess.SP

A 100 GHz Wideband Reconfigurable Intelligent Surface Based on Orthogonal Polarization and Sub-Array Partitioning Concepts

The sub-terahertz frequency band offers extremely large bandwidth and enables ultra-high data rates for future wireless applications. However, severe propagation loss and blockage significantly limit coverage at these frequencies. Reconfigurable intelligent surfaces can dynamically shape EM wave propagation and provide a promising solution for coverage enhancement. Realizing such surfaces using standard printed circuit board technology is attractive due to its low cost and scalability, but it remains challenging around 100 GHz because of fabrication limits, limited switch availability, large switch size compared with the unit cell, switch parasitic effects, and high control complexity. In this work, we demonstrate a wideband PCB-based reconfigurable intelligent surface operating around 100 GHz. The design combines an orthogonal-polarization slot-coupled patch structure with subarray partitioning to mitigate switch-induced parasitic effects, reduce the required number of RF switches, and simplify the control architecture. The reconfigurability is achieved using AlGaAs SP3T bare-die switches integrated through optimized bond-wire interconnections. For proof of concept, a six-subarray structure with 4 by 4 elements per subarray is designed for different beamforming angles, and a 12 by 8 prototype is fabricated and experimentally characterized. The measured results show a gain enhancement of about 10 dB from 86 to 100 GHz and about 5 dB from 100 to 106 GHz, while maintaining a low power consumption of 0.165 W. These results validate the feasibility of practical wideband PCB-based reconfigurable intelligent surfaces for sub-terahertz wireless systems.

eess.SP

Multi-Target Estimation via Tensor Decomposition for Beyond Diagonal RIS-Aided Bistatic Sensing

We investigate the performance of beyond-diagonal reconfigurable intelligent surfaces (BD-RIS) for bistatic MIMO multi-target sensing using a two-stage tensor Doppler-delay-angle estimation (TenDAE). The first stage solves a Kronecker sum approximation (KSA) with a rank equal to the number of targets. The second stage employs a nested tensor factorization estimation (NTFE) that exploits the inherent multidimensional structure via two tensor decompositions that are solved in parallel. The first employs a PARAFAC decomposition to extract the targets' angles, and the second uses a nested PARAFAC decomposition to find the targets' delay and Doppler parameters. This two-stage approach decouples acquisition of the angles and delays/Dopplers using either alternating least squares or a higher-order singular value decomposition, followed by a high-resolution subspace technique, such as ESPRIT. We further compare the performance of a BD-RIS with a classical diagonal RIS. For the latter, we solve a Khatri-Rao sum approximation problem rather than the KSA due to the specific structure of the received signal. Notably, our NTFE framework remains blind to the underlying RIS architecture while simultaneously estimating all targets with minimal sensing resources. Additionally, we show that employing a nested-PARAFAC decomposition enables the decoupling of the delay-Doppler and angle domains. We also derive the Cram\'er-Rao lower bound to further assess the performance of the TenDAE framework. Finally, we numerically evaluate the solutions presented in this paper and demonstrate their efficiency in terms of RMSE compared with state-of-the-art approaches.

eess.SP

A Screen-printed, Silver-nanowire-based Optically Transparent Wideband Reconfigurable Intelligent Surface for 5G mmWave Applications

The reconfigurable intelligent surface (RIS) can help establish secondary line-of-sight links for 5G mmWave and beyond applications to cater for the large path loss and blockage in millimeter-wave direct links. It is desirable that the RISs are optically transparent so that they can be placed on building windows, etc. However, traditional transparent designs with indium tin oxide films have challenges of high loss and low transparency, while metallic meshes suffer from a large feature size for millimeter wave designs. In this letter, we propose an optically transparent RIS using screen-printed silver nanowires (AgNW) and PIN diodes. The AgNW ink has more than 80% optical transparency and a decent conductivity of $5\times10^{6}$ S/m. The RIS array size is 9x20, and each column serially connects 9 unit cells. The RIS can work from 23.5 GHz to 29.5 GHz with 30{\deg} angular stability. The measurement results of the RIS show up to 15 dB gain enhancement within 30{\deg} angle range, while maintaining high optical transparency and large bandwidth.

physics.optics

Reconfigurable Intelligent Surfaces-Assisted Integrated Access and Backhaul

In this paper, we study the impact of reconfigurable intelligent surfaces (RISs) on the coverage extension of integrated access and backhaul (IAB) networks. Particularly, using a finite stochastic geometry model, with random distributions of user equipments (UEs) in a finite region, and planned hierachical architecture for IAB, we study the service coverage probability defined as the probability of the event that the UEs' minimum rate requirements are satisfied. We present comparisons between different cases including IAB-only, IAB assisted with RIS for backhaul as well as IAB assisted by network controlled repeaters (NCRs). Our investigations focus on wide-area IAB assisted with RIS through the lens of different design architectures and deployments, revealing both conflicts and synergies for minimizing the effect of tree foliage over seasonal changes. Our simulation results reveal both opportunities and challenges towards the implementation of RIS in IAB.

cs.IT

Mobility Management in Integrated Sensing and Communications Networks

The performance of the integrated sensing and communication (ISAC) networks is considerably affected by the mobility of the transceiver nodes, user equipment devices (UEs) and the passive objects that are sensed. For instance, the sensing efficiency is considerably affected by the presence or absence of a line-of-sight connection between the sensing transceivers and the object; a condition that may change quickly due to mobility. Moreover, the mobility of the UEs and objects may result in dynamically varying communication-to-sensing and sensing-to communication interference, deteriorating the network performance. In such cases, there may be a need to handover the sensing process to neighbor nodes. In this article, we develop the concept of mobility management in ISAC networks. Here, depending on the mobility of objects and/or the transceiver nodes, the data traffic, the sensing or communication coverage area of the transceivers, and the network interference, the transmission and/or the reception of the sensing signals may be handed over to neighbor nodes. Also, the ISAC configuration and modality - that is, using monostatic or bistatic sensing - are updated accordingly, such that the sensed objects can be continuously sensed with low overhead. We show that mobility management reduces the sensing interruption and boosts the communication and sensing efficiency of ISAC networks.

eess.SP

RIS-Assisted Sensing: A Nested Tensor Decomposition-Based Approach

We study a monostatic multiple-input multiple-output sensing scenario assisted by a reconfigurable intelligent surface using tensor signal modeling. We propose a method that exploits the intrinsic multidimensional structure of the received echo signal, allowing us to recast the target sensing problem as a nested tensor-based decomposition problem to jointly estimate the delay, Doppler, and angular information of the target. We derive a two-stage approach based on the alternating least squares algorithm followed by the estimation of the signal parameters via rotational invariance techniques to extract the target parameters. Simulation results show that the proposed tensor-based algorithm yields accurate estimates of the sensing parameters with low complexity.

eess.SP

Cellular Network Densification: a System-level Analysis with IAB, NCR and RIS

As the number of user equipments increases in fifth generation (5G) and beyond, it is desired to densify the cellular network with auxiliary nodes assisting the base stations. Examples of these nodes are integrated access and backhaul (IAB) nodes, network-controlled repeaters (NCRs) and reconfigurable intelligent surfaces (RISs). In this context, this work presents a system level overview of these three nodes. Moreover, this work evaluates through simulations the impact of network planning aiming at enhancing the performance of a network used to cover an outdoor sport event. We show that, in the considered scenario, in general, IAB nodes provide an improved signal to interference-plus-noise ratio and throughput, compared to NCRs and RISs. However, there are situations where NCR outperforms IAB due to higher level of interference caused by the latter. Finally, we show that the deployment of these nodes in unmanned aerial vehicles (UAVs) also achieves performance gains due to their aerial mobility. However, UAV constraints related to aerial deployment may prevent these nodes from reaching results as good as the ones achieved by their stationary deployment.

eess.SY

Load Balancing-based Topology Adaptation for Integrated Access and Backhaul Networks

Integrated access and backhaul (IAB) technology is a flexible solution for network densification. IAB nodes can also be deployed in moving nodes such as buses and trains, i.e., mobile IAB (mIAB). As mIAB nodes can move around the coverage area, the connection between mIAB nodes and their parent macro base stations (BSs), IAB donor, is sometimes required to change in order to keep an acceptable backhaul link, the so called topology adaptation (TA). The change from one IAB donor to another may strongly impact the system load distribution, possibly causing unsatisfactory backhaul service due to the lack of radio resources. Based on this, TA should consider both backhaul link quality and traffic load. In this work, we propose a load balancing algorithm based on TA for IAB networks, and compare it with an approach in which TA is triggered based on reference signal received power (RSRP) only. The results show that our proposed algorithm improves the passengers worst connections throughput in uplink (UL) and, more modestly, also in downlink (DL), without impairing the pedestrian quality of service (QoS) significantly.

cs.NI

Impact of Network Deployment on the Performance of NCR-assisted Networks

To address the need of coverage enhancement in the fifth generation (5G) of wireless cellular telecommunications, while taking into account possible bottlenecks related to deploying fiber based backhaul (e.g., required cost and time), the 3rd generation partnership project (3GPP) proposed in Release 18 the concept of network-controlled repeaters (NCRs). NCRs enhance previous radio frequency (RF) repeaters by exploring beamforming transmissions controlled by the network through side control information. In this context, this paper introduces the concept of NCR. Furthermore, we present a system level model that allows the performance evaluation of an NCR-assisted network. Finally, we evaluate the network deployment impact on the performance of NCR-assisted networks. As we show, with proper network planning, NCRs can boost the signal to interference-plus-noise ratio (SINR) of the user equipments (UEs) in a poor coverage of a macro base station. Furthermore, celledge UEs and uplink (UL) communications are the ones that benefit the most from the presence of NCRs.

cs.NI

A Fully Screen-Printed Vanadium-Dioxide Switches Based Wideband Reconfigurable Intelligent Surface for 5G Bands

Reconfigurable Intelligent Surface (RIS) is attracting more and more research interest because of its ability to reprogram the radio environment. Designing and implementing the RIS, however, is challenging because of limitations of printed circuit board (PCB) technology related to manufacturing of large sizes as well as the cost of switches. Thus, a low-cost manufacturing process suitable for large size and volume of devices, such as screen-printing is necessary. In this paper, for the first time, a fully screen-printed reconfigurable intelligent surface (RIS) with vanadium dioxide (VO2) switches for 5G and beyond communications is proposed. A VO2 ink has been prepared and batches of switches have been printed and integrated with the resonator elements. These switches are a fraction of the cost of commercial switches. Furthermore, the printing of these switches directly on metal patterns negates the need of any minute soldering of the switches. To avoid the complications of multilayer printing and realizing the RIS without vias, the resonators and the biasing lines are realized on a single layer. However, this introduces the challenge of interference between the biasing lines and the resonators, which is tackled in this work by designing the bias lines as part of the resonator. By adjusting the unit cell periodicity and the dimension of the H-shaped resonator, we achieve a 220 to 170{\deg} phase shift from 23.5 GHz to 29.5 GHz covering both n257 and n258 bands. Inside the wide bandwidth, the maximum ON reflection magnitude is 74%, and the maximum OFF magnitude is 94%. The RIS array comprises 20x20 unit cells (4.54x4.54{\lambda}^2 at 29.5 GHz). Each column of unit cells is serially connected to a current biasing circuit. To validate the array's performance, we conduct full-wave simulations as well as near-field and far-field measurements.

eess.SP

Extended Automatic Repeat Request For Integrated Sensing And Communication Networks

6G wireless networks will integrate communication, computing, localization, and sensing capabilities while meeting the needs of high reliability and trustworthiness. In this paper, we develop similar techniques as those used by communication modules of previous generations for the sensing functionality of 6G networks. Specifically, this paper introduces the concept of extended automatic repeat request (e-ARQ) for integrated sensing and communications (ISAC) networks. We focus on multi-static sensing schemes, in which the nodes receiving the reflected sensing signals provide the transmitting nodes with configurable levels of feedback about the sensing result. This technique improves the sensing quality via retransmissions using adaptive parameters. We show that our proposed e-ARQ boosts the sensing quality in terms of detection accuracy and provides a sense of adaptability for applications supported by ISAC networks.

eess.SP

RIS in Cellular Networks -- Challenges and Issues

Reconfigurable intelligent surface (RIS) has been suggested to be a key 6G feature and was suggested to be considered as a study-item in both 3GPP Releases 18 and 19. However, in both releases, it has been decided not to continue with it as a study-item, and to leave it for possible future specification. In this paper, we present the rationale for such a decision. Particularly, we demonstrate the practical issues which may affect the feasibility or usefulness of RIS in cellular networks, and present open problems to be addressed before RIS can be used in practice. Moreover, we compare the performance of RIS with network-controlled repeater, the node with the most similar characteristics to RIS and which has been standardized in 3GPP Release 18. Finally, different simulations are presented to evaluate the performance of RIS-assisted networks.

cs.NI

Integrated Communication, Localization, and Sensing in 6G D-MIMO Networks

Future generations of mobile networks call for concurrent sensing and communication functionalities in the same hardware and/or spectrum. Compared to communication, sensing services often suffer from limited coverage, due to the high path loss of the reflected signal and the increased infrastructure requirements. To provide a more uniform quality of service, distributed multiple input multiple output (D-MIMO) systems deploy a large number of distributed nodes and efficiently control them, making distributed integrated sensing and communications (ISAC) possible. In this paper, we investigate ISAC in D-MIMO through the lens of different design architectures and deployments, revealing both conflicts and synergies. In addition, simulation and demonstration results reveal both opportunities and challenges towards the implementation of ISAC in D-MIMO.

cs.IT

Uplink soft handover for LEO constellations: how strong the inter-satellite link should be

We consider a constellation of low-earth-orbit (LEO) satellites connected to a handheld device on the ground. Due to the very large orbital speed, an effective handover strategy becomes of paramount importance. In particular, we study the benefits of soft handover in the uplink from the physical-layer point of view. We give a realistic model for both the ground-to-satellite and the inter-satellite links, following the 3GPP channel model for the former. We suppose that, during handover from a serving satellite to a target satellite, one of the two satellites forwards the received signal from the ground user to the other, thus acting as a relay. We quantify through simulations the loss of hard handover, compared to soft handover. For the latter, we test both amplify-and-forward (AF) and decode-and-forward (DF) relaying techniques and verify that, at least in the simulated conditions, DF does not repay, in terms of block error rate (BLER), the increase of complexity with respect to AF. Also, we study the effect of the LEO constellation size on the network BLER. Finally, we show that, with soft handover, the impact of misalignment on the inter-satellite link is severe, especially at optical frequencies.

cs.IT