arXiv subjects

Behrooz Makki

Publications and source records attributed to Behrooz Makki.

At least 55 records · Page 3Linked to original sources

arXiv2023

Tensor-Based Channel Estimation and Data-Aided Tracking in IRS-Assisted MIMO Systems

This letter proposes a model for symbol detection in the uplink of IRS-assisted networks in the presence of channel aging. During the first stage, we model the received pilot signal as a tensor, which serves as a basis for both estimating the channel and configuring the IRS. In the second stage, the proposed tensor approach tracks the aging process to detect and estimate the transmitted data symbols. Our evaluations show that our proposed channel and symbol estimation schemes improve the performance of IRS-assisted systems in terms of the achieved bit error rate and mean squared error of the received data, compared to state of the art schemes.

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arXiv2023

Two-Dimensional Channel Parameter Estimation for IRS-Assisted Networks

This paper proposes a pilot decoupling-based two-dimensional channel parameter estimation method for intelligent reflecting surface (IRS)-assisted networks. We exploit the combined effect of Terahertz sparse propagation and the geometrical structure of arrays deployed at the base station, the IRS, and the user equipment to develop a low-complexity channel parameter estimation method. By means of a new pilot design along the horizontal and vertical domains, the overall channel parameter estimation problem is decoupled into different domains. Furthermore, with this decoupling, it is possible to simultaneously sense/estimate the channel parameters and to communicate with the sensed node. Specifically, we derive two estimators by decoupling the global problem into sub-problems and exploiting the built-in tensor structure of the sensing/estimation problem by means of multiple rank-one approximations. The Cramér-Rao lower bound is derived to assess the performance of the proposed estimators. We show that the two proposed methods yield accurate parameter estimates and outperform state-of-the-art methods in terms of complexity. The tradeoffs between performance and complexity offered by the proposed methods are discussed and numerically assessed.

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arXiv2023

A Via-less Fully Screen-Printed Reconfigurable Intelligent Surface for 5G Millimeter Wave Communication

In this paper, we propose a via-less fully screen-printed reconfigurable intelligent surface which can establish a second line-of-sight communication from 23.5GHz to 29.5GHz. By serially connecting the H shaped resonator along the H field of the incident wave, we minimize the effect of the biasing lines and make a via-less design, which reduces the fabrication difficulty and cost. The unit-cell simulation of the array with screen-printed VO2 switches shows a 215° to 160° phase shift difference between the ON and OFF states within bandwidth. During the field testing of the ideal arrays, we verify that the array can redirect the 45° incident wave to 0° reflection with a signal enhancement of at least 10 dB as compared to the array which has all unit cells in the OFF condition.

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arXiv2022

A Comparison between Network-Controlled Repeaters and Reconfigurable Intelligent Surfaces

Network-controlled repeater (NCR) has been recently considered as a study-item in 3GPP Release 18, and the discussions are continuing in a work-item. In this paper, we introduce the concept of NCRs, as a possible low-complexity device to support for network densification and compare the performance of the NCRs with those achieved by reconfigurable intelligent surfaces (RISs). The results are presented for the cases with different beamforming methods and hardware impairment models of the RIS. Moreover, we introduce the objectives of the 3GPP Release 18 NCR work-item and study the effect of different parameters on the performance of NCR-assisted networks. As we show, with a proper deployment, the presence of NCRs/RISs can improve the network performance considerably.

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arXiv2022

Hybrid FSO/THz-based Backhaul Network for mmWave Terrestrial Communication

In this work, a hybrid free-space optics (FSO)/ teraHertz (THz) based backhaul network is considered to provide high-data rate reliable communication to the terrestrial mobile users (MUs) operating at millimeter wave (mmWave) bands. The FSO link is affected by the atmospheric turbulence and pointing error impairments which are characterized with Gamma-Gamma and Rayleigh fading, respectively. At the FSO receiver, both the intensity modulated direct detection and heterodyne detection techniques are considered. The multi-antenna THz link suffers from both high path-loss and misalignment error. The THz channel is characterized with $α-μ$ distribution and misalignment error is characterized with Rayleigh fading. To minimize the effect of back-and-forth switching, soft switching method is introduced at the access point (AP) to select the signal coming through the hybrid FSO/THz link, and a comparison with hard switching method is presented. Selective decode-and-forward relaying is considered at the AP which is forwarding the successfully decoded backhaul signals to the terrestrial MUs. In this context, we derive closed-form expressions of the individual link's outage probability, end-to-end (E2E) outage probability, asymptotic outage probability, ergodic capacity, and average bit-error-rate of various modulation schemes. Finally, we study the effect of different parameters such as atmospheric turbulence, pointing/misalignment errors, link distance, atmospheric attenuation/path-loss, fading parameters of the THz and access links, and number of antennas on the network performance. Our results indicate that, with a proper switching method, the joint implementation of FSO/THz links, improves the rate/reliability of the backhaul links with limited switching overhead.

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arXiv2022

Constrained Deployment Optimization in Integrated Access and Backhaul Networks

Integrated access and backhaul (IAB) is one of the promising techniques for 5G networks and beyond (6G), in which the same node/hardware is used to provide both backhaul and cellular services in a multi-hop fashion. Due to the sensitivity of the backhaul links with high rate/reliability demands, proper network planning is needed to make the IAB network performing appropriately and as good as possible. In this paper, we study the effect of deployment optimization on the coverage of IAB networks. We concentrate on the cases where, due to either geographical or interference management limitations, unconstrained IAB node placement is not feasible in some areas. To that end, we propose various millimeter wave (mmWave) blocking-aware constrained deployment optimization approaches. Our results indicate that, even with limitations on deployment optimization, network planning boosts the coverage of IAB networks considerably.

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arXiv2022

Channel Estimation in RIS-Assisted MIMO Systems Operating Under Imperfections

Reconfigurable intelligent surface is a potential technology component of future wireless networks due to its capability of shaping the wireless environment. The promising MIMO systems in terms of extended coverage and enhanced capacity are, however, critically dependent on the accuracy of the channel state information. However, traditional channel estimation schemes are not applicable in RIS-assisted MIMO networks, since passive RISs typically lack the signal processing capabilities that are assumed by channel estimation algorithms. This becomes most problematic when physical imperfections or electronic impairments affect the RIS due to its exposition to different environmental effects or caused by hardware limitations from the circuitry. While these real-world effects are typically ignored in the literature, in this paper we propose efficient channel estimation schemes for RIS-assisted MIMO systems taking different imperfections into account. Specifically, we propose two sets of tensor-based algorithms, based on the parallel factor analysis decomposition schemes. First, by assuming a long-term model in which the RIS imperfections, modeled as unknown phase shifts, are static within the channel coherence time we formulate an iterative alternating least squares (ALS)-based algorithm for the joint estimation of the communication channels and the unknown phase deviations. Next, we develop the short-term imperfection model, which allows both amplitude and phase RIS imperfections to be non-static with respect to the channel coherence time. We propose two iterative ALS-based and closed-form higher order singular value decomposition-based algorithms for the joint estimation of the channels and the unknown impairments. Moreover, we analyze the identifiability and computational complexity of the proposed algorithms and study the effects of various imperfections on the channel estimation quality.

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arXiv2022

Paving the Way Towards Mobile IAB: Problems, Solutions and Challenges

Deploying access and backhaul as wireless links, a.k.a. integrated access and backhaul (IAB), is envisioned as a viable approach to enable flexible and dense networks. Even further, mobile IAB (mIAB) is a candidate solution to enhance the connectivity of user equipments (UEs) moving together. In this context, different of other works from the literature, the present work overviews the basis for the deployment of mIAB by presenting: 1) the current status of IAB standardization in the fifth generation (5G) new radio (NR); 2) a new taxonomy for state-of-the-art works regarding fixed IAB and mIAB; 3) an extensive performance analysis of mIAB based on simulation results; and 4) open challenges and potential future prospects of mIAB. Specifically, the proposed taxonomy classifies IAB works according to different perspectives and categorizes mIAB works according to the type of mobility. For each type of mobility, the main studied topics are presented. Regarding the performance evaluation, we consider an urban macro scenario where mIAB nodes are deployed in buses in order to improve the passengers connection. The results show that, compared to other network architectures, the deployment of mIAB nodes remarkably improves the passengers throughput and latency in both downlink and uplink.

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arXiv2022

Reducing the Control Overhead of Intelligent Reconfigurable Surfaces Via a Tensor-Based Low-Rank Factorization Approach

Passive intelligent reconfigurable surfaces (IRS) are becoming an attractive component of cellular networks due to their ability of shaping the propagation environment and thereby improving the coverage. While passive IRS nodes incorporate a great number of phase-shifting elements and a controller entity, the phase-shifts are typically determined by the cellular base station (BS) due to its computational capability. Since the fine granularity control of the large number of phase-shifters may become prohibitive in practice, it is important to reduce the control overhead between the BS and the IRS controller. To this end, in this paper we propose a low-rank approximation of the near-optimal phase-shifts, which would incur prohibitively high communication overhead on the BS-IRS controller links. The key idea is to represent the potentially large IRS phase-shift vector using a low-rank tensor model. This is achieved by factorizing a tensorized version of the IRS phase-shift vector, where each component is modeled as the Kronecker product of a predefined number of factors of smaller sizes, which can be obtained via tensor decomposition algorithms. We show that the proposed low-rank models drastically reduce the required feedback requirements associated with the BS-IRS control links. Our simulation results indicate that the proposed method is especially attractive in scenarios with a strong line of sight component, in which case nearly the same spectral efficiency is reached as in the cases with near-optimal phase-shifts, but with a drastically reduced communication overhead.

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arXiv2022

Tensor-Based Channel Estimation for RIS-Assisted Networks Operating Under Imperfections

Reconfigurable intelligent surface (RIS) is a candidate technology for future wireless networks. It enables to shape the wireless environment to reach massive connectivity and enhanced data rate. The promising gains of RIS-assisted networks are, however, strongly depends on the accuracy of the channel state information. Due to the passive nature of the RIS elements, channel estimation may become challenging. This becomes most evident when physical imperfections or electronic impairments affect the RIS due to its exposition to different environmental effects or caused by hardware limitations from the circuitry. In this paper, we propose an efficient and low-complexity tensor-based channel estimation approach in RIS-assisted networks taking different imperfections into account. By assuming a short-term model in which the RIS imperfections behavior, modeled as unknown amplitude and phase shifts deviations, is non-static with respect to the channel coherence time, we formulate a closed-form higher order singular value decomposition based algorithm for the joint estimation of the involved channels and the unknown impairments. Furthermore, the identifiability and computational complexity of the proposed algorithm are analyzed, and we study the effect of different imperfections on the channel estimation quality. Simulation results demonstrate the effectiveness of our proposed tensor-based algorithm in terms of the estimation accuracy and computational complexity compared to competing tensor-based iterative alternating solutions.

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arXiv2022

IRS Phase-Shift Feedback Overhead-Aware Model Based on Rank-One Tensor Approximation

In this paper, we propose a rank-one tensor modeling approach that yields a compact representation of the optimum IRS phase-shift vector for reducing the feedback overhead. The main idea consists of factorizing the IRS phase-shift vector as a Kronecker product of smaller vectors, namely factors. The proposed phase-shift model allows the network to trade-off between achievable data rate and feedback reduction by controling the factorization parameters. Our simulations show that the proposed phase-shift factorization drastically reduces the feedback overhead, while improving the data rate in some scenarios, compared to the state-of-the-art schemes.

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arXiv2022

Semi-Blind Joint Channel and Symbol Estimation in IRS-Assisted Multi-User MIMO Networks

Intelligent reflecting surface (IRS) is a promising technology for beyond 5th Generation of the wireless communications. In fully passive IRS-assisted systems, channel estimation is challenging and should be carried out only at the base station or at the terminals since the elements of the IRS are incapable of processing signals. In this letter, we formulate a tensor-based semi-blind receiver that solves the joint channel and symbol estimation problem in an IRS-assisted multi-user multiple-input multiple-output system. The proposed approach relies on a generalized PARATUCK tensor model of the signals reflected by the IRS, based on a two-stage closed-form semi-blind receiver using Khatri-Rao and Kronecker factorizations. Simulation results demonstrate the superior performance of the proposed semi-blind receiver, in terms of the normalized mean squared error and symbol error rate, as well as a lower computational complexity, compared to recently proposed parallel factor analysis-based receivers.

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arXiv2022

TDD frame design for interference handling in mobile IAB networks

Integrated access and backhaul (IAB) is envisioned as a possible solution to address the need for network densification in situations where fiber connection is not viable. In Release 18, 3rd generation partnership project (3GPP) will take another step on extending IAB capabilities. With mobile IAB (mIAB), IAB nodes can be deployed within vehicles, e.g., buses. As in every new technology, performance assessment and evaluation of the impact of interference is of interest for industry and academia. In this paper, we present contributions on those topics. First, we evaluate the performance of mIAB compared to fiber connected deployments. Moreover, we study the impact of interference on the performance of mIAB networks and propose a solution based on inserting silent slots on the time division duplex (TDD) frame pattern. According to our simulation results, mIAB is capable of improving performance of onboard user equipments (UEs) without harming too much the quality of service (QoS) of surrounding UEs. Furthermore, we show that the TDD frame pattern should be carefully designed to account for scenarios with different levels of interference.

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arXiv2022

High-Rate Uninterrupted Internet-of-Vehicle Communications in Highways: Dynamic Blockage Avoidance and CSIT Acquisition

In future wireless networks, one of the use-cases of interest is Internet-of-vehicles (IoV). Here, IoV refers to two different functionalities, namely, serving the in-vehicle users and supporting the connected-vehicle functionalities, where both can be well provided by the transceivers installed on top of vehicles. Such dual functionality of on-vehicle transceivers implies strict rate and reliability requirements, for which one may need to communicate at millimeter wave (mmW) frequencies. However, IoV communication at mmW requires up-to-date channel state information (CSI) and blockage avoidance. In this article, we incorporate the recently proposed concept of predictor antennas (PAs) into a large-scale cooperative PA (LSCPA) setup where both temporal blockages and CSI out-dating are avoided via base stations (BSs)/vehicles cooperation. Summarizing the ongoing standardization progress enabling IoV communications, we present the potentials and challenges of the LSCPA setup, and compare the effect of cooperative and non-cooperative schemes on the performance of IoV links. As we show, BSs cooperation and blockage/CSI prediction can boost the performance of IoV links remarkably.

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arXiv2021

Uplink Power Control in Integrated Access and Backhaul Networks

Integrated access and backhaul (IAB) network is a novel radio access network (RAN) solution, enabling network densification for 5G and beyond. In this paper, we use power control combined with resource allocation algorithms to develop efficient IAB networks with high service coverage. Particularly, we develop a genetic algorithm-based solution for the power control of both user equipments and IAB nodes such that the network uplink service coverage probability is maximized. Finally, considering millimeter wave channel models, we study the effect of different parameters including minimum data rate requirement, coverage distance and transmit power on the network performance. As we show, a power allocation schemes with well-tuned parameters can improve the uplink performance of IAB networks considerably. Moreover, with millimeter wave communications and a proper network deployment, the effect of interference on the service coverage probability is negligible.

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arXiv2021

Velocity-aware Antenna Selection in Predictor Antenna Systems

Moving relay (MR), which is a candidate solution for supporting in-vehicle users, has been investigated in different studies. Due to the mobile nature of the MR, acquiring channel state information at the transmitter side (CSIT) is challenging because of the fast-changing environment around the vehicle. On top of an MR, one can use predictor antenna (PA), i.e., an additional antenna in front of the receive antenna (RA), to obtain CSIT, and recent works have investigated the benefits of such a set up. PA-aided CSIT acquisition normally works with the help of different content information such as the location and the velocity of the MR. In this paper, we study the effect of velocity awareness on the PA system, and develop adaptive antenna selection schemes in PA-assisted MRs. Results show that, compared to no-CSIT schemes, a velocity-aware antenna selection-based PA system can improve the end-to-end throughput by an order of magnitude.

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arXiv2021

On Topology Optimization and Routing in Integrated Access and Backhaul Networks: A Genetic Algorithm-based Approach

In this paper, we study the problem of topology optimization and routing in integrated access and backhaul (IAB) networks, as one of the promising techniques for evolving 5G networks. We study the problem from different perspectives. We develop efficient genetic algorithm-based schemes for both IAB node placement and non-IAB backhaul link distribution, and evaluate the effect of routing on bypassing temporal blockages. Here, concentrating on millimeter wave-based communications, we study the service coverage probability, defined as the probability of the event that the user equipments' (UEs) minimum rate requirements are satisfied. Moreover, we study the effect of different parameters such as the antenna gain, blockage and tree foliage on the system performance. Finally, we summarize the recent Rel-16 as well as the upcoming Rel-17 3GPP discussions on routing in IAB networks, and discuss the main challenges for enabling mesh-based IAB networks. As we show, with a proper network topology, IAB is an attractive approach to enable the network densification required by 5G and beyond.

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arXiv2021

Joint Scheduling and Throughput Maximization in Self-backhauled Millimeter Wave Cellular Networks

Integrated access and backhaul (IAB) networks have the potential to provide high data rate in both access and backhaul networks by sharing the same spectrum. Due to the dense deployment of small base stations (SBSs), IAB networks connect SBSs to the core network in a wireless manner without the deployment of high-cost optical fiber. As large spectrum is available in mmWave bands and high data rate is achieved by using directional beamforming, the access and backhaul links can be integrated in the same frequency band while satisfying quality-of-service constraints. In this work, we optimize the scheduling of access and backhaul links such that the minimum throughput of the access links is maximized based on the revised simplex method. By considering a probability based line-ofsight (LOS) and non-line-of-sight (NLOS) path loss model and the antenna array gains, we compare the achievable minimum access throughput of the IAB network with the network with only macro base stations, and study the effect of the network topology and antenna parameters on the achievable minimum throughput. Simulation results show that, for a broad range of parameter settings, the implementation of IABs improves the access minimum achievable throughput.

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