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See detailShort-Packet Communications for MIMO NOMA Systems over Nakagami-m Fading: BLER and Minimum Blocklength Analysis
Tran, Duc Dung UL; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Vehicular Technology (in press)

Recently, ultra-reliable and low-latency communications (URLLC) using short-packets has been proposed to fulfill the stringent requirements regarding reliability and latency of emerging applications in 5G ... [more ▼]

Recently, ultra-reliable and low-latency communications (URLLC) using short-packets has been proposed to fulfill the stringent requirements regarding reliability and latency of emerging applications in 5G and beyond networks. In addition, multiple-input multiple-output non-orthogonal multiple access (MIMO NOMA) is a potential candidate to improve the spectral efficiency, reliability, latency, and connectivity of wireless systems. In this paper, we investigate short-packet communications (SPC) in a multiuser downlink MIMO NOMA system over Nakagami-m fading, and propose two antenna-user selection methods considering two clusters of users having different priority levels. In contrast to the widely-used long data-packet assumption, the SPC analysis requires the redesign of the communication protocols and novel performance metrics. Given this context, we analyze the SPC performance of MIMO NOMA systems using the average block error rate (BLER) and minimum blocklength, instead of the conventional metrics such as ergodic capacity and outage capacity. More specifically, to characterize the system performance regarding SPC, asymptotic (in the high signal-to-noise ratio regime) and approximate closed-form expressions of the average BLER at the users are derived. Based on the asymptotic behavior of the average BLER, an analysis of the diversity order, minimum blocklength, and optimal power allocation is carried out. The achieved results show that MIMO NOMA can serve multiple users simultaneously using a smaller blocklength compared with MIMO OMA, thus demonstrating the benefits of MIMO NOMA for SPC in minimizing the transmission latency. Furthermore, our results indicate that the proposed methods not only improve the BLER performance, but also guarantee full diversity gains for the respective users. [less ▲]

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See detailMachine Learning-Enabled Joint Antenna Selection and Precoding Design: From Offline Complexity to Online Performance
Vu, Thang Xuan UL; Chatzinotas, Symeon UL; Nguyen, van Dinh UL et al

in IEEE Transactions on Wireless Communications (in press)

We investigate the performance of multi-user multiple-antenna downlink systems in which a base station (BS) serves multiple users via a shared wireless medium. In order to fully exploit the spatial ... [more ▼]

We investigate the performance of multi-user multiple-antenna downlink systems in which a base station (BS) serves multiple users via a shared wireless medium. In order to fully exploit the spatial diversity while minimizing the passive energy consumed by radio frequency (RF) components, the BS is equipped with M RF chains and N antennas, where M < N. Upon receiving pilot sequences to obtain the channel state information (CSI), the BS determines the best subset of M antennas for serving the users. We propose a joint antenna selection and precoding design (JASPD) algorithm to maximize the system sum rate subject to a transmit power constraint and quality of service (QoS) requirements. The JASPD overcomes the non-convexity of the formulated problem via a doubly iterative algorithm, in which an inner loop successively optimizes the precoding vectors, followed by an outer loop that tries all valid antenna subsets. Although approaching the (near) global optimality, the JASPD suffers from a combinatorial complexity, which may limit its application in real-time network operations. To overcome this limitation, we propose a learning-based antenna selection and precoding design algorithm (L-ASPA), which employs a deep neural network (DNN) to establish underlaying relations between the key system parameters and the selected antennas. The proposed L-ASPD is robust against the number of users and their locations, BS's transmit power, as well as the small-scale channel fading. With a well-trained learning model, it is shown that the L-ASPD significantly outperforms baseline schemes based on the block diagonalization and a learning-assisted solution for broadcasting systems and achieves higher effective sum rate than that of the JASPA under limited processing time. In addition, we observed that the proposed L-ASPD can reduce the computation complexity by 95% while retaining more than 95% of the optimal performance. [less ▲]

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See detailEnergy Efficiency Optimization Technique for SWIPT-enabled Multi-Group Multicasting Systems with Heterogeneous Users
Gautam, Sumit UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in The international Conference on Acoustics, Speech, & Signal Processing (ICASSP) (2021, June)

We consider a multi-group (MG) multicasting (MC) system wherein a multi-antenna transmitter serves heterogeneous users capable of either information decoding (ID) or energy harvesting (EH), or both. In ... [more ▼]

We consider a multi-group (MG) multicasting (MC) system wherein a multi-antenna transmitter serves heterogeneous users capable of either information decoding (ID) or energy harvesting (EH), or both. In this context, we investigate a precoder design framework to explicitly serve the ID and EH users categorized within certain MC and EH groups. Specifically, the ID users are categorized within multiple MC groups while the EH users are a part of single (last) group. We formulate a problem to optimize the energy efficiency in the considered scenario under a quality-of-service (QoS) constraint. An algorithm based on Dinkelback method, slack-variable replacement, and second-order conic programming (SOCP)/semi-definite relaxation (SDR) is proposed to obtain a suitable solution for the above-mentioned fractional-objective dependent non-convex problem. Simulation results illustrate the benefits of proposed algorithm under several operating conditions and parameter values, while drawing a comparison between the two proposed methods. [less ▲]

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See detailChannel Modeling and Analysis of Reconfigurable Intelligent Surfaces Assisted Vehicular Networks
Kong, Long UL; He, Jiguang; Ai, Yun et al

Scientific Conference (2021, June)

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See detailA design strategy for phase synchronization in Precoding-enabled DVB-S2X user terminals
Martinez Marrero, Liz UL; Merlano Duncan, Juan Carlos UL; Querol, Jorge UL et al

Scientific Conference (2021, June)

This paper address the design of a phase tracking block for the DVB-S2X user terminals in a satellite precoding system. The spectral characteristics of the phase noise introduced by the oscillator, the ... [more ▼]

This paper address the design of a phase tracking block for the DVB-S2X user terminals in a satellite precoding system. The spectral characteristics of the phase noise introduced by the oscillator, the channel, and the thermal noise at the receiver are taken into account. Using the expected phase noise mask, the optimal parameters for a second-order PLL intended to track channel variations from the pilots are calculated. To validate the results a Simulink model was implemented considering the characteristics of the hardware prototype. The performance of the design was evaluated in terms of the accuracy and stability for the frame structure of superframe Format 2, as described in Annex E of DVB-S2X. [less ▲]

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See detailModeling and Optimization of RF-Energy Harvesting-assisted Quantum Battery System
Gautam, Sumit UL; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL et al

in Proceedings of 2021 IEEE 93rd Vehicular Technology Conference: VTC2021-Spring (2021, April)

The quest for finding a small-sized energy supply to run the small-scale wireless gadgets, with almost an infinite lifetime, has intrigued humankind since past several decades. In this context, the ... [more ▼]

The quest for finding a small-sized energy supply to run the small-scale wireless gadgets, with almost an infinite lifetime, has intrigued humankind since past several decades. In this context, the concept of Quantum batteries has come into limelight more recently to serve the purpose. However, the main issue revolving around the closed-system design of Quantum batteries is to ensure a loss-less environment, which is extremely difficult to realize in practice. In this paper, we present the modeling and optimization aspects of a Radio-Frequency (RF) Energy Harvesting (EH) assisted Quantum battery, wherein several EH modules (in the form of micro- or nano- sized integrated circuits (ICs)) help each of the involved Quantum sources achieve the so-called quasi-stable state. Specifically, a micro-controller manages the overall harvested energy from the RF-EH ICs and a photon emitting device, such that the emitted photons are absorbed by the electrons in the Quantum sources. In order to precisely model and optimize the considered framework, we formulate a transmit power minimization problem for an RF-based wireless system to optimize the number of RF-EH ICs under the given EH constraints at the Quantum battery-enabled wireless device. We obtain an analytical solution to the above-mentioned problem using a rational approach, while additionally seeking another solution obtained via a non-linear program solver. The effectiveness of the proposed technique is reported in the form of numerical results by taking a range of system parameters into account. [less ▲]

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See detailJoint Beam-Hopping Scheduling and Power Allocation in NOMA-Assisted Satellite Systems
Wang, Anyue UL; Lei, Lei UL; Lagunas, Eva UL et al

Scientific Conference (2021, March 31)

In this paper, we investigate potential synergies of non-orthogonal multiple access (NOMA) and beam hopping (BH) for multi-beam satellite systems. The coexistence of BH and NOMA provides time-power-domain ... [more ▼]

In this paper, we investigate potential synergies of non-orthogonal multiple access (NOMA) and beam hopping (BH) for multi-beam satellite systems. The coexistence of BH and NOMA provides time-power-domain flexibilities in mitigating a practical mismatch effect between offered capacity and requested traffic per beam. We formulate the joint BH scheduling and NOMA-based power allocation problem as mixed-integer nonconvex programming. We reveal the xponential-conic structure for the original problem, and reformulate the problem to the format of mixed-integer conic programming (MICP), where the optimum can be obtained by exponential-complexity algorithms. A greedy scheme is proposed to solve the problem on a timeslot-by-timeslot basis with polynomial-time complexity. Numerical results show the effectiveness of the proposed efficient suboptimal algorithm in reducing the matching error by 62.57% in average over the OMA scheme and achieving a good trade-off between computational complexity and performance compared to the optimal solution. [less ▲]

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See detailAutomotive Squint-forward-looking SAR: High Resolution and Early Warning
Hu, Ruizhi UL; Mysore Rama Rao, Bhavani Shankar UL; Murtada, Ahmed Abdelnaser Elsayed UL et al

in IEEE Journal of Selected Topics in Signal Processing (2021)

Forward-looking automotive radars can sense long-distant targets to enable early warning, but the lateral resolution is limited. Synthetic aperture radar (SAR) techniques can achieve very high azimuth ... [more ▼]

Forward-looking automotive radars can sense long-distant targets to enable early warning, but the lateral resolution is limited. Synthetic aperture radar (SAR) techniques can achieve very high azimuth resolution but cannot resolve targets in the forward direction. As a trade-off, squint-forward-looking SAR (SFL-SAR) can perform 2D imaging on a distant area squint to the moving direction, providing both high resolution and early warning. In this paper, we analyzed and derived the constraints of automotive SFL-SAR to satisfy both the required resolution and braking distance. Simulations and imaging results verified the analysis. [less ▲]

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See detailEfficient Federated Learning Algorithm for Resource Allocation in Wireless IoT Networks
Nguyen, van Dinh UL; Sharma, Shree Krishna UL; Vu, Thang Xuan UL et al

in IEEE Internet of Things Journal (2021), 8(5), 3394-3409

Federated learning (FL) allows multiple edge computing nodes to jointly build a shared learning model without having to transfer their raw data to a centralized server, thus reducing communication ... [more ▼]

Federated learning (FL) allows multiple edge computing nodes to jointly build a shared learning model without having to transfer their raw data to a centralized server, thus reducing communication overhead. However, FL still faces a number of challenges such as non-iid distributed data and heterogeneity of user equipments (UEs). Enabling a large number of UEs to join the training process in every round raises a potential issue of the heavy global communication burden. To address these issues, we generalize the current state-of-the-art Federated Averaging (FedAvg) by adding a weight-based proximal term to the local loss function. The proposed FL algorithm runs stochastic gradient descent in parallel on a sampled subset of the total UEs with replacement during each global round. We provide a convergence upper bound characterizing the trade-off between convergence rate and global rounds, showing that a small number of active UEs per round still guarantees convergence. Next, we employ the proposed FL algorithm in wireless Internet-of-Things (IoT) networks to minimize either total energy consumption or completion time of FL, where a simple yet efficient path-following algorithm is developed for its solutions. Finally, numerical results on unbalanced datasets are provided to demonstrate the performance improvement and robustness on the convergence rate of the proposed FL algorithm over FedAvg. They also reveal that the proposed algorithm requires much less training time and energy consumption than the FL algorithm with full user participation. These observations advocate the proposed FL algorithm for a paradigm shift in bandwidth- constrained learning wireless IoT networks. [less ▲]

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See detailDesign Optimization for Low-Complexity FPGA Implementation of Symbol-Level Multiuser Precoding
Haqiqatnejad, Alireza UL; Krivochiza, Jevgenij UL; Merlano Duncan, Juan Carlos UL et al

in IEEE Access (2021), 9

This paper proposes and validates a low-complexity FPGA design for symbol-level precoding (SLP) in multiuser multiple-input single-output (MISO) downlink communication systems. In the optimal case, the ... [more ▼]

This paper proposes and validates a low-complexity FPGA design for symbol-level precoding (SLP) in multiuser multiple-input single-output (MISO) downlink communication systems. In the optimal case, the symbol-level precoded transmit signal is obtained as the solution to an optimization problem tailored for a given set of users’ data symbols. This symbol-by-symbol design, however, imposes excessive computational complexity on the system. To alleviate this issue, we aim to reduce the per-symbol complexity of the SLP scheme by developing an approximate yet computationally-efficient closed-form solution. The proposed solution allows us to achieve a high symbol throughput in real-time implementations. To develop the FPGA design, we express the proposed solution in an algorithmic way and translate it to hardware description language (HDL). We then optimize the processing to accelerate the performance and generate the corresponding intellectual property (IP) core. We provide the synthesis report for the generated IP core, including performance and resource utilization estimates and interface descriptions. To validate our design, we simulate an uncoded transmission over a downlink multiuser channel using the LabVIEW software, where the SLP IP core is implemented as a clock-driven logic (CDL) unit. Our simulation results show that a throughput of 100 Mega symbols per second per user can be achieved via the proposed SLP design. We further use the MATLAB software to produce numerical results for the conventional zero-forcing (ZF) and the optimal SLP techniques as benchmarks for comparison. Thereby, it is shown that the proposed FPGA implementation of SLP offers an improvement of up to 50 percent in power efficiency compared to the ZF precoding. Remarkably, it enjoys the same per-symbol complexity order as that of the ZF technique. We also evaluate the loss of the real-time SLP design, introduced by the algebraic approximations and arithmetic inaccuracies, with respect to the optimal scheme. [less ▲]

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See detailEnergy-Efficient Hybrid Symbol-Level Precoding via Phase Shifter Selection in mmWave MU-MIMO Systems
Haqiqatnejad, Alireza UL; Kayhan, Farbod UL; Ottersten, Björn UL

in Energy-Efficient Hybrid Symbol-Level Precoding via Phase Shifter Selection in mmWave MU-MIMO Systems (2021, January 25)

We address the symbol-level precoding design problem for the downlink of a multiuser millimeter wave (mmWave) multiple-input multiple-output wireless system. We consider a hybrid analog-digital ... [more ▼]

We address the symbol-level precoding design problem for the downlink of a multiuser millimeter wave (mmWave) multiple-input multiple-output wireless system. We consider a hybrid analog-digital architecture with phase shifter selection where a small-sized baseband precoder is followed by two successive networks of analog on-off switches and variable phase shifters according to a fully-connected structure. We jointly optimize the digital baseband precoder and the states of the switching network on a symbol-level basis, i.e., by exploiting both the channel state information (CSI) and the instantaneous data symbols, while the phase-shifting network is designed only based on the CSI. Our approach to this joint optimization is to minimize the Euclidean distance between the optimal fully-digital and the hybrid symbol-level precoders. It is shown via numerical results that using the proposed approach, up to 50 percent of the phase shifters can be switched off on average, allowing for reductions in the power consumption of the phase-shifting network. Adopting appropriate power consumption models for the analog precoder, our energy efficiency analysis further shows that this power reduction can substantially improve the energy efficiency of the hybrid precoding compared to the fully-digital and the state-of-the-art schemes. [less ▲]

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See detailCompletion Time Minimization in NOMA Systems:Learning for Combinatorial Optimization
Wang, Anyue UL; Lei, Lei UL; Lagunas, Eva UL et al

in IEEE Networking Letters (2021)

In this letter, we study a completion-time minimization problem by jointly optimizing time slots (TSs) and power allocation for time-critical non-orthogonal multiple access (NOMA) systems. The original ... [more ▼]

In this letter, we study a completion-time minimization problem by jointly optimizing time slots (TSs) and power allocation for time-critical non-orthogonal multiple access (NOMA) systems. The original problem is non-linear/non-convex with discrete variables, leading to high computational complexity in conventional iterative methods. Towards an efficient solution, we train deep neural networks to perform fast and high-accuracy predictions to tackle the difficult combinatorial parts, i.e., determining the minimum consumed TSs and user-TS allocation. Based on the learning-based predictions, we develop a low-complexity post-process procedure to provide feasible power allocation. The numerical results demonstrate promising improvements of the proposed scheme compared to other baseline schemes in terms of computational efficiency, approximating optimum, and feasibility guarantee. [less ▲]

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See detailFeasible Point Pursuit and Successive Convex Approximation for Transmit Power Minimization in SWIPT-Multigroup Multicasting Systems
Gautam, Sumit UL; Lagunas, Eva UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Green Communications and Networking (2021)

We consider three wireless multi-group (MG) multicasting (MC) systems capable of handling heterogeneous user types viz., information decoding (ID) specific users with conventional receiver architectures ... [more ▼]

We consider three wireless multi-group (MG) multicasting (MC) systems capable of handling heterogeneous user types viz., information decoding (ID) specific users with conventional receiver architectures, energy harvesting (EH) only users with non-linear EH module, and users with joint ID and EH capabilities having separate units for the two operations, respectively. Each user is categorized under unique group(s), which can be of MC type specifically meant for ID users, and/or an energy group consisting of EH explicit users. The joint ID and EH users are a part of both EH group and single MC group. We formulate an optimization problem to minimize the total transmit power with optimal precoder designs for the three aforementioned scenarios, under certain quality-of-service constraints. The problem may be adapted to the well-known semidefinite program and solved via relaxation of rank-1 constraint. However, this process leads to performance degradation in some cases, which increases with the rank of solution obtained from the relaxed problem. Hence, we develop a novel technique motivated by the feasible-point pursuit successive convex approximation method in order to address the rank-related issue. The benefits of proposed method are illustrated under various operating conditions and parameter values, with comparison between the three above-mentioned scenarios. [less ▲]

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See detailSymbol-Level Precoding with Constellation Rotation in the Finite Block Length Regime
Kisseleff, Steven UL; Alves Martins, Wallace UL; Chatzinotas, Symeon UL et al

in IEEE Communications Letters (2021)

This paper tackles the problem of optimizing the parameters of a symbol-level precoder for downlink multiantenna multi-user systems in the finite block length regime. Symbol-level precoding (SLP) is a non ... [more ▼]

This paper tackles the problem of optimizing the parameters of a symbol-level precoder for downlink multiantenna multi-user systems in the finite block length regime. Symbol-level precoding (SLP) is a non-linear technique for multiuser wireless networks, which exploits constructive interference among co-channel links. Current SLP designs, however, implicitly assume asymptotically infinite blocks, since they do not take into account that the design rules for finite and especially short blocks might significantly differ. This paper fills this gap by introducing a novel SLP design based on discrete constellation rotations. The rotations are the added degree of freedom that can be optimized for every block to be transmitted, for instance, to save transmit power. Numerical evaluations of the proposed method indicate substantial power savings, which might be over 99% compared to the traditional SLP, at the expense of a single additional pilot symbol per block for constellation de-rotation. [less ▲]

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See detailA Novel Learning-based Hard Decoding Scheme and Symbol-Level Precoding Countermeasures
Mayouche, Abderrahmane UL; Alves Martins, Wallace UL; Tsinos, Christos G. et al

in IEEE Wireless Communications and Networking Conference (WCNC), Najing 29 March to 01 April 2021 (2021)

In this work, we consider an eavesdropping scenario in wireless multi-user (MU) multiple-input single-output (MISO) systems with channel coding in the presence of a multi-antenna eavesdropper (Eve). In ... [more ▼]

In this work, we consider an eavesdropping scenario in wireless multi-user (MU) multiple-input single-output (MISO) systems with channel coding in the presence of a multi-antenna eavesdropper (Eve). In this setting, we exploit machine learning (ML) tools to design a hard decoding scheme by using precoded pilot symbols as training data. Within this, we propose an ML framework for a multi-antenna hard decoder that allows an Eve to decode the transmitted message with decent accuracy. We show that MU-MISO systems are vulnerable to such an attack when conventional block-level precoding is used. To counteract this attack, we propose a novel symbol-level precoding scheme that increases the bit-error rate at Eve by obstructing the learning process. Simulation results validate both the ML-based attack as well as the countermeasure, and show that the gain in security is achieved without affecting the performance at the intended users. [less ▲]

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See detailA Remote Carrier Synchronization Technique for Coherent Distributed Remote Sensing Systems
Merlano Duncan, Juan Carlos UL; Martinez Marrero, Liz UL; Querol, Jorge UL et al

in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2020)

Phase, frequency, and time synchronization are crucial requirements for many applications, such as multi-static remote sensing and communication systems. Moreover, the synchronization solution becomes ... [more ▼]

Phase, frequency, and time synchronization are crucial requirements for many applications, such as multi-static remote sensing and communication systems. Moreover, the synchronization solution becomes even more challenging when the nodes are orbiting or flying on airborne or spaceborne platforms. This paper compares the available technologies used for the synchronization and coordination of nodes in distributed remote sensing applications. Additionally, this paper proposes a general system model and identifies preliminary guidelines and critical elements for implementing the synchronization mechanisms exploiting the inter-satellite communication link. The distributed phase synchronization loop introduced in this work deals with the self-interference in a full-duplex point to point scenario by transmitting two carriers at each node. All carriers appear with different frequency offsets around a central frequency, called the application central-frequency or the beamforming frequency. This work includes a detailed analysis of the proposed algorithm and the required simulations to verify its performance for different phase noise, AWGN, and Doppler shift scenarios. [less ▲]

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See detailStochastic-Geometry-Based Interference Modeling in Automotive Radars Using Matérn Hard-Core Process
Mishra, K. V.; R., B. Shankar M.; Ottersten, Björn UL

in 2020 IEEE Radar Conference (RadarConf20), Stochastic-Geometry-Based Interference Modeling in Automotive Radars Using Matérn Hard-Core Process (2020, December 04)

As the use of radars in autonomous driving systems becomes more prevalent, these systems are increasingly susceptible to mutual interference. In this paper, we employ stochastic geometry to model the ... [more ▼]

As the use of radars in autonomous driving systems becomes more prevalent, these systems are increasingly susceptible to mutual interference. In this paper, we employ stochastic geometry to model the automotive radar interference in realistic traffic scenarios and then derive trade-offs between the radar design parameters and detection probability. Prior works model the locations of radars in the lane as a homogeneous Poisson point process (PPP). However, the PPP models assume all nodes to be independent, do not account for the lengths of vehicles, and ignore spatial mutual exclusion. In order to provide a more realistic interference effect, we adopt the Matérn hardcore process (MHCP) instead of PPP, in which two vehicles are not closer than an exclusion radius from one another. We show that the MHCP model leads to more practical design trade-offs for adapting the radar parameters than the conventional PPP model. [less ▲]

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