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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., Comment: The Asilomar Conference on Signals, Systems, and Computers 2024

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., Comment: Paper submitted to Journal of Communication and Information Systems (JCIS)

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., Comment: Paper submitted to IEEE Systems Journal

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., Comment: Paper accepted for publication in the conference proceedings of "19th International Symposium on Wireless Communication Systems" (ISWCS)

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.

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., Comment: 7 pages, 4 figures, 2 tables, magazine article

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., Comment: Submitted to IEEE Access

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.

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.

In fifth generation (5G) wireless cellular networks, millimeter wave spectrum opens room for several potential improvements in throughput, reliability, latency, among other aspects. However, it also brings challenges, such as a higher influence of blockage which may significantly limit the coverage. In this context, network-controlled repeaters (NCRs) are network nodes with low complexity that represent a technique to overcome coverage problems. In this paper, we introduce the NCR concept and study its performance gains and deployment options. Particularly, presenting the main specifications of NCR as agreed in 3rd generation partnership project (3GPP) Rel-18, we analyze different NCR deployments in an urban scenario and compare its performance with alternative deployments. As demonstrated, with a proper network planning and beamforming design, NCR is an attractive solution to cover blind spots the base stations (BSs) may have., Comment: Submmited to IEEE Communications Standards Magazine

Millimeter wave (mmWave) and sub-THz communications, foreseen for sixth generation (6G), suffer from high propagation losses which affect the network coverage. To address this point, smart entities such as network-controlled repeaters (NCRs) have been considered as cost-efficient solutions for coverage extension. NCRs, which have been standardized in 3rd generation partnership project Release 18, are radio frequency repeaters with beamforming capability controlled by the network through side control information. Another challenge raised by the adoption of high frequency bands is the use of large bandwidths. Here, a common configuration is to divide a large frequency band into multiple smaller subbands. In this context, we consider a scenario with NCRs where signaling related to measurements used for radio resource management is transmitted in one subband centered at frequency $f_c$ and data transmission is performed at a different frequency $f_c + \Delta f$ based on the measurements taken at $f_c$. Here, a challenge is that the array radiation pattern can be frequency dependent and, therefore, lead to beam misalignment, called beam squinting. We characterize beam squinting in the context of subband operation and propose a solution where the beam patterns to be employed at a given subband can be adjusted/compensated to mitigate beam squinting. Our results show that, without compensation, the perceived signal to interference-plus-noise ratio (SINR) and so the throughput can be substantially decreased due to beam squinting. However, with our proposed compensation method, the system is able to support NCR subband signaling operation with similar performance as if signaling and data were transmitted at the same frequency., Comment: Submitted to IEEE Transactions on Vehicular Technology

This paper considers the problem of downlink localization and user equipments (UEs) tracking with an adaptive procedure for a range of distances. We provide the base station (BS) with two signaling schemes and the UEs with two localization algorithms, assuming far-field (FF) and near-field (NF) conditions, respectively. The proposed schemes employ different beam-sweep patterns, where their compatibility depends on the UE range. Consequently, the FF-NF distinction transcends the traditional definition. Our proposed NF scheme requires beam-focusing on specific spots and more transmissions are required to sweep the area. Instead, the FF scheme assumes distant UEs, and fewer beams are sufficient. We derive a low-complexity algorithm that exploits the FF channel model and highlight its practical benefits and the limitations. Also, we propose an iterative adaptive procedure, where the signaling scheme is depends on the expected accuracy-complexity trade-off. Multiple iterations introduce a tracking application, where the formed trajectory dictates the validity of our assumptions. Moreover, the range from the BS, where the FF signaling scheme can be successfully employed, is investigated. We show that the conventional Fraunhofer distance is not sufficient for adaptive localization and tracking algorithms in the mixed NF and FF environment., Comment: arXiv admin note: text overlap with arXiv:2402.02473

This letter studies the problem of jointly detecting active user equipments (UEs) and estimating their location in the near field, wherein the base station (BS) is unaware of the number of active (or inactive) UEs and their positions. The system is equipped with multiple reconfigurable intelligent surfaces (RISs) that aid the process of inspecting the coverage area of the BS with adequate localization resolution providing a low-complexity solution for detection and location estimation. To address this problem, we propose to utilize the additional degrees of freedom due to the additional inspection points provided by the RISs. Specifically, we propose an iterative detection procedure, where multiple inspections are jointly considered, allowing the BS to assign known pilots to previously detected UEs and thereby to provide a structured channel access. Also, the problem of multiple access interference is explored and identified as a limiting performance factor for the activity detection. The results show that, with a proper implementation of the RISs, our proposed scheme can detect/localize the UEs with high accuracy, augmenting benchmark UE detection schemes to a spatially aware detection.

This paper considers the problem of downlink localization of user equipment devices (UEs) that are either in the near-field (NF) or in the far-field (FF) of the array of the serving base station (BS). We propose a dual signaling scheme, which can be implemented at the BS, for localizing such UEs. The first scheme assumes FF, while the other assumes NF conditions. Both schemes comprise a beam-sweeping technique, employed by the BS, and a localization algorithm, employed by the UEs. The FF-based scheme enables beam-steering with a low signaling overhead, which is utilized for the proposed localization algorithm, while the NF-based scheme operates with a higher complexity. Specifically, our proposed localization scheme takes advantage of the relaxed structure of the FF, which yields low computational complexity, but is not suitable for operating in the NF. Since the compatibility and the performance of the FF- based scheme depends on the BS-to-UE distance, we study the limitations of FF-based procedure, explore the trade-off in terms of performance and resource requirements for the two schemes, and propose a triggering condition for operating the component schemes of the dual scheme. Also, we study the performance of an iterative localization algorithm that takes into account the accuracy-complexity trade-off and adapts to the actual position of the UE. We find that the conventional Fraunhofer distance is not sufficient for adapting localization algorithms in the mixed NF and FF environment., Comment: 5 pages, conference

Moving towards $6^{\text{th}}$ generation (6G), backhaul networks require significant improvements to support new use-cases with restricted joint capacity and availability requirements. In this paper, we investigate the potentials and challenges of joint sub-teraHertz (sub-THz) and free space optical (FSO), in short sub-THz-FSO, multi-hop networks as a candidate technology for future backhaul communications. As we show, with a proper deployment, sub-THz-FSO networks have the potential to provide high-rate reliable backhauling, while there are multiple practical challenges to be address before they can be used in large-scale.

Increased capacity in the access network poses capacity challenges on the transport network due to the aggregated traffic. However, there are spatial and time correlation in the user data demands that could potentially be utilized. To that end, we investigate a wireless transport network architecture that integrates beamforming and coded-caching strategies. Especially, our proposed design entails a server with multiple antennas that broadcasts content to cache nodes responsible for serving users. Traditional caching methods face the limitation of relying on the individual memory with additional overhead. Hence, we develop an efficient genetic algorithm-based scheme for beam optimization in the coded-caching system. By exploiting the advantages of beamforming and coded-caching, the architecture achieves gains in terms of multicast opportunities, interference mitigation, and reduced peak backhaul traffic. A comparative analysis of this joint design with traditional, un-coded caching schemes is also conducted to assess the benefits of the proposed approach. Additionally, we examine the impact of various buffering and decoding methods on the performance of the coded-caching scheme. Our findings suggest that proper beamforming is useful in enhancing the effectiveness of the coded-caching technique, resulting in significant reduction in peak backhaul traffic., Comment: Submitted to IEEE Future Networks World Forum, 2023

This work investigates interference mitigation techniques in multi-user multiple input multiple output (MU-MIMO) Intelligent Reflecting Surface (IRS)-aided networks, focusing on the base station end. Two methods of precoder design based on block diagonalization are proposed. The first method does not consider the interference caused by the IRS, seeking to mitigate only the multi-user interference. The second method mitigates both the IRS-caused interference and the multi-user interference. A comparison between both methods within an no-IRS MU-MIMO network with strong direct links is provided. The results show that, although in some circumstances IRS interference can be neglected, treating it can improve system capacity and provide higher spectral efficiency, Comment: 5 pages, 4 figures, submitted to XLI BRAZILIAN SYMPOSIUM ON TELECOMMUNICATIONS AND SIGNAL PROCESSING - SBrT 2023

This paper proposes a tensor-based parametric modeling and estimation framework in multiple-input multiple-output (MIMO) systems assisted by intelligent reflecting surfaces (IRSs). We present two algorithms that exploit the tensor structure of the received pilot signal to estimate the concatenated channel. The first one is an iterative solution based on the alternating least squares algorithm. In contrast, the second method provides closed-form estimates of the involved parameters using the high order single value decomposition. Our numerical results show that our proposed tensor-based methods provide improved performance compared to competing state-of-the-art channel estimation schemes, thanks to the exploitation of the algebraic tensor structure of the combined channel without additional computational complexity., Comment: arXiv admin note: text overlap with arXiv:2305.10499

Heterogeneous networks have been studied as one of the enablers of network densification. These studies have been intensified to overcome some drawbacks related to propagation in millimeter waves (mmWaves), such as severe path and penetration losses. One of the promising heterogeneous nodes is network-controlled repeater (NCR). It was proposed by the 3rd generation partnership project (3GPP) in Release 18 as a candidate solution to enhance network coverage. In this context, this work performs a system level evaluation to analyze the performance improvement that an NCR can cause in its serving cell as well as its interference impact on neighbor cells. Particularly, the results show a considerable improvement on the performance of user equipments (UEs) served by the NCR, while neighbor UEs that receive the NCR signal as interference are negatively impacted, but not enough to suffer from outage., Comment: Submitted to XLI Brazilian Symposium on Telecommunications and Signal Processing (SBrT)

In this letter, we consider an intelligent reflecting surface (IRS)-assisted multiple input multiple output (MIMO) communication and we optimize the joint active and passive beamforming by exploiting the geometrical structure of the propagation channels. Due to the inherent Kronecker product structure of the channel matrix, the global beamforming optimization problem is split into lower dimensional horizontal and vertical sub-problems. Based on this factorization property, we propose two closed-form methods for passive and active beamforming designs, at the IRS, the base station, and user equipment, respectively. The first solution is a singular value decomposition (SVD)-based algorithm independently applied on the factorized channels, while the second method resorts to a third-order rank-one tensor approximation along each domain. Simulation results show that exploiting the channel Kronecker structures yields a significant improvement in terms of computational complexity at the expense of negligible spectral efficiency (SE) loss. We also show that under imperfect channel estimation, the tensor-based solution shows better SE than the benchmark and proposed SVD-based solutions., Comment: 5 pages, 3 figures, submited to wireless communication letters (under review)

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.

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 Cram\'er-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.

Despite the growing interest in reconfigurable intelligent surfaces (RISs) for millimeter-wave (mm-wave) bands, and the considerable theoretical work reported by the communication community, there is a limited number of published works demonstrating practical implementations and experimental results. To the authors' knowledge, no published literature has reported experimental results for RISs covering the n257 and n258 mm-wave bands. In this work, we propose a novel wideband RIS design that covers the entire mm-wave 5G n257 and n258 bands. In simulations, the unit cell can maintain a phase difference of 180{\deg} +- 20{\deg} and a reflection magnitude greater than -2.8 dB within 22.7 to 30.5 GHz (29.3% bandwidth) using one-bit PIN switches. The proposed unit cell design with four circular cutouts and long vias could realize wideband performance by exciting two adjacent high-order resonances (2.5f and 3.5f). The periodic unit cells can maintain an angular stability of 30{\deg}. Based on the proposed unit cell, a 20 by 20 RIS array is designed and fabricated with a size of 7.1{\lambda} by 7.1{\lambda}. The measurement results demonstrate that the proposed RIS could maintain a 3 dB peak gain variation bandwidth among various array configurations within 22.5 to 29.5 GHz (26.9%) and with a beam scanning capability of 50{\deg}, making this design a good candidate for 5G mm-wave applications.

This paper proposes tensor-based channel estimation for reconfigurable intelligent surface (RIS)-assisted communication networks. We exploit the inherent geometrical structure of the Terahertz propagation channel, including the antenna array geometries at the base station, the RIS, and the user equipment to design a tensor-based channel estimator, referred to as the higher-dimensional rank-one approximations (HDR) method. By exploiting the geometrical structure of the combined base station-RIS-user equipment channel, the proposed HDR estimator recasts parametric channel estimation as a single sixth-order rank-one tensor approximation problem, which can be efficiently solved using higher-order singular value decomposition to deliver parallel estimates of each channel component vector. Numerical results show that the proposed method provides significantly more accurate parameter estimates than competing state-of-the-art tensor-based RIS channel estimation, Khatri-Rao factorization, and least squares methods. For higher-rank channels, the HDR method shows similar spectral efficiency compared to its competitors while having similar computational complexity to the classical least squares estimator.

In this work, we consider multi-hop and mesh hybrid teraHertz/free-space optics (THz/FSO)-based backhaul networks for high data-rate communications. The results are presented for the cases with both out-band integrated access and backhaul (IAB) and non-IAB based communication setups. We consider different deployments of the THz and FSO networks and consider both switching and combining methods between the hybrid FSO/THz links. We study the impact of atmospheric turbulence, atmospheric attenuation, and the pointing error on the FSO communication. The THz communication suffers from small scale fading, path-loss, and the misalignment error. Finally, we evaluate the effects of atmospheric attenuation/path-loss, pointing/misalignment error, small-scale fading, atmospheric turbulence, number of antennas, number of user equipments, number of hops, and the threshold data-rates on the performance of considered systems. As we show, with different network deployments and switching/combining methods, the hybrid implementation of the THz/FSO links improves the network reliability significantly.

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{\deg} to 160{\deg} 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{\deg} incident wave to 0{\deg} reflection with a signal enhancement of at least 10 dB as compared to the array which has all unit cells in the OFF condition., Comment: 2 pages, 3 figures, submitted to 2023 IEEE International Symposium on Antennas and Propagation

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., Comment: 7 pages, 7 figures, submitted to potential IEEE publication

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., Comment: Submitted to IEEE Wireless Communications and Networking Conference (WCNC)'2023, Glasgow, Scotland, United Kingdom

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., Comment: arXiv admin note: text overlap with arXiv:2206.03557

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., Comment: Submitted to "IEEE Access"

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., Comment: arXiv admin note: text overlap with arXiv:2205.12024

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.

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.

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.

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 $\alpha-\mu$ 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.

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.

Internet-of-vehicle (IoV) is a general concept referring to, e.g., autonomous drive based vehicle-to-everything (V2X) communications or moving relays. Here, high rate and reliability demands call for advanced multi-antenna techniques and millimeter-wave (mmw) based communications. However, the sensitivity of the mmw signals to blockage may limit the system performance, especially in highways/rural areas with limited building reflectors/base station deployments and high-speed devices. To avoid the blockage, various techniques have been proposed among which reconfigurable intelligent surface (RIS) is a candidate. RIS, however, has been mainly of interest in stationary/low mobility scenarios, due to the associated channel state information acquisition and beam management overhead as well as imperfect reflection. In this article, we study the potentials and challenges of RIS-assisted dynamic blockage avoidance in IoV networks. Particularly, by designing region-based RIS pre-selection as well as blockage prediction schemes, we show that RIS-assisted communication has the potential to boost the performance of IoV networks. However, there are still issues to be solved before RIS can be practically deployed in IoV networks., Comment: Submitted to IEEE Communications Magazine

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., Comment: 6 pages, 6 figures

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.

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., Comment: Submitted to IEEE Communications Magazine

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., Comment: Summitted to 2021 17th International Symposium on Wireless Communication Systems (ISWCS) - Special Session - Optimal Resource Allocation for Interference Limited Wireless Networks

Coded-caching is a promising technique to reduce the peak rate requirement of backhaul links during high traffic periods. In this letter, we study the effect of adaptive transmission on the performance of coded-caching based networks. Particularly, concentrating on the reduction of backhaul peak load during the high traffic periods, we develop adaptive rate and power allocation schemes maximizing the network successful transmission probability, which is defined as the probability of the event with all cache nodes decoding their intended signals correctly. Moreover, we study the effect of different message decoding and buffering schemes on the system performance. As we show, the performance of coded-caching networks is considerably affected by rate/power allocation as well as the message decoding/buffering schemes., Comment: under review in IEEE Wireless Communications Letters

In this paper, we study the throughput utility functions in buffer-equipped monostatic backscatter communication networks with multi-antenna Readers. In the considered model, the backscatter nodes (BNs) store the data in their buffers before transmission to the Reader. We investigate three utility functions, namely, the sum, the proportional and the common throughput. We design online admission policies, corresponding to each utility function, to determine how much data can be admitted in the buffers. Moreover, we propose an online data link control policy for jointly controlling the transmit and receive beamforming vectors as well as the reflection coefficients of the BNs. The proposed policies for data admission and data link control jointly optimize the throughput utility, while stabilizing the buffers. We adopt the min-drift-plus-penalty (MDPP) method in designing the control policies. Following the MDPP method, we cast the optimal data link control and the data admission policies as solutions of two independent optimization problems which should be solved in each time slot. The optimization problem corresponding to the data link control is non-convex and does not have a trivial solution. Using Lagrangian dual and quadratic transforms, we find a closed-form iterative solution. Finally, we use the results on the achievable rates of finite blocklength codes to study the system performance in the cases with short packets. As demonstrated, the proposed policies achieve optimal utility and stabilize the data buffers in the BNs.

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., Comment: Revised manuscript in IEEE Open Journal of the Communications Society

In future wireless systems, a large number of users may access the networks via moving relays (MRs) installed on top of vehicles. One of the main challenges of MRs is rapid channel variation which may make channel estimation, and its following procedures, difficult. To address these issues, various schemes are designed, among which predictor antenna (PA) is a candidate. The PA setup refers to a system with two (sets of) antennas on top of a vehicle, where the PA(s) positioned in front of the vehicle is(are) utilized to predict the channel state information required for data transmission to the receive antennas (RAs) aligned behind the PA. In this paper, we introduce the concept and the potentials of PA systems. Moreover, summarizing the field trials for PAs and the 3GPP attempts on (moving) relays, we compare the performance of different PA and non-PA methods for vehicle communications in both urban and rural areas with the PA setup backhauled through terrestrial or satellite technology, respectively. As we show, with typical parameter settings and vehicle speeds, a single-antenna PA-assisted setup can boost the backhaul throughput of MRs, compared to state-of-the-art open-loop schemes, by up to 50%., Comment: Submitted to IEEE Communications Magazine

In this paper, we study an application of deep learning to uplink multiuser detection (MUD) for non-orthogonal multiple access (NOMA) scheme based on Welch bound equality spread multiple access (WSMA). Several non-cooperating users, each with its own preassigned NOMA signature sequence (SS), transmit over the same resource. These SSs have low correlation among them and aid in the user separation at the receiver during MUD. Several subtasks such as equalizing, combining, slicing, signal reconstruction and interference cancellation are involved in MUD. The neural network (NN) considered in this paper replaces these well-defined receiver blocks with a single black box, i.e., the NN provides a one-shot approximation for these modules. We consider two different supervised feed-forward NN implementations, namely, a deep NN and a 2D-Convolutional NN, for MUD. Performance of these two NNs is compared with the conventional receivers. Simulation results show that by proper selection of the NN parameters, it is possible for the black box approximation to provide faster and better performance, compared to conventional MUD schemes, and it achieves almost the same symbol error rate as the ultimate one obtained by the complex maximum likelihood-based detectors., Comment: Under review in IEEE Transactions on Cognitive Communications and Networking

In future wireless networks, we anticipate that a large number of devices will connect to mobile networks through moving relays installed on vehicles, in particular in public transport vehicles. To provide high-speed moving relays with accurate channel state information different methods have been proposed, among which predictor antenna (PA) is one of the promising ones. Here, the PA system refers to a setup where two sets of antennas are deployed on top of a vehicle, and the front antenna(s) can be used to predict the channel state information for the antenna(s) behind. In this paper, we study the delay-limited performance of PA systems using adaptive rate allocations. We use the fundamental results on the achievable rate of finite block-length codes to study the system throughput and error probability in the presence of short packets. Particularly, we derive closed-form expressions for the error probability, the average transmit rate as well as the optimal rate allocation, and study the effect of different parameters on the performance of PA systems. The results indicate that rate adaptation under finite block-length codewords can impro, Comment: Accepted in the 3rd International Conference on Advanced Communication Technologies and Networking (CommNet 2020)

This paper explores the road to vastly improving the broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, with peak data rates up to 1 Tbps. Several categories of enablers at the infrastructure, spectrum, and protocol/algorithmic levels are required to realize the intended broadband connectivity goals in 6G. At the infrastructure level, we consider ultra-massive MIMO technology (possibly implemented using holographic radio), intelligent reflecting surfaces, user-centric cell-free networking, integrated access and backhaul, and integrated space and terrestrial networks. At the spectrum level, the network must seamlessly utilize sub-6 GHz bands for coverage and spatial multiplexing of many devices, while higher bands will be mainly used for pushing the peak rates of point-to-point links. Finally, at the protocol/algorithmic level, the enablers include improved coding, modulation, and waveforms to achieve lower latency, higher reliability, and reduced complexity., Comment: Submitted to IEEE Access. 51 pages,31 figures. arXiv admin note: text overlap with arXiv:2004.14247

In this paper, we propose and analyze an error-constrained data transmission approach for uplink communication using non-orthogonal multiple access (NOMA). The results are presented for the cases with hybrid automatic repeat request (HARQ) protocols where, depending on the message decoding status in the previous rounds, the decoding scheme of the receiver as well as the data rates/transmission powers of the transmitters are adapted correspondingly. We perform finite block-length analysis of the proposed scheme and study the effect of the codewords length on the performance of NOMA-HARQ protocols. Particularly, considering repetition time diversity HARQ and codewords of finite length, we determine the expected error-limited achievable rate and the transmit power improvement of our proposed scheme, compared to the conventional NOMA-HARQ protocols. As we show, smart adaptation of the decoding scheme improves the spectral/energy efficiency of NOMA-HARQ protocols considerably with no additional receiver complexity., Comment: Under review in IEEE Open Journal of the Communications Society

In this paper, we introduce and study the potentials and challenges of integrated access and backhaul (IAB) as one of the promising techniques for evolving 5G networks. We study IAB networks from different perspectives. We summarize the recent Rel-16 as well as the upcoming Rel-17 3GPP discussions on IAB, and highlight the main IAB-specific agreements on different protocol layers. Also, concentrating on millimeter wave-based communications, we evaluate the performance of IAB networks in both dense and suburban areas. Using a finite stochastic geometry model, with random distributions of IAB nodes as well as user equipments (UEs) in a finite region, we study the service coverage rate defined as the probability of the event that the UEs' minimum rate requirements are satisfied. We present comparisons between IAB and hybrid IAB/fiber-backhauled networks where a part or all of the small base stations are fiber-connected. Finally, we study the robustness of IAB networks to weather and various deployment conditions and verify their effects, such as blockage, tree foliage, rain as well as antenna height/gain on the coverage rate of IAB setups, as the key differences between the fiber-connected and IAB networks. As we show, IAB is an attractive approach to enable the network densification required by 5G and beyond., Comment: Revised manuscript in IEEE Open Journal of the Communications Society