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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 detailData-driven Precoded MIMO Detection Robust to Channel Estimation Errors
Mayouche, Abderrahmane UL; Alves Martins, Wallace UL; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2021)

We study the problem of symbol detection in downlink coded multiple-input multiple-output (MIMO) systems with precoding and without the explicit knowledge of the channel-state information (CSI) at the ... [more ▼]

We study the problem of symbol detection in downlink coded multiple-input multiple-output (MIMO) systems with precoding and without the explicit knowledge of the channel-state information (CSI) at the receiver. In this context, we investigate the impact of imperfect CSI at the transmitter (CSIT) on the detection performance. We first model the CSIT degradation based on channel estimation errors to investigate its impact on the detection performance at the receiver. To mitigate the effect of CSIT deterioration at the latter, we propose learning based techniques for hard and soft detection that use downlink precoded pilot symbols as training data. We note that these pilots are originally intended for signal-to-interference-plus-noise ratio (SINR) estimation. We validate the approach by proposing a lightweight implementation that is suitable for online training using several state-of-the-art classifiers. We compare the bit error rate (BER) and the runtime complexity of the proposed approaches where we achieve superior detection performance in harsh channel conditions while maintaining low computational requirements. Specifically, numerical results show that severe CSIT degradation impedes the correct detection when a conventional detector is used. However, the proposed learning-based detectors can achieve good detection performance even under severe CSIT deterioration, and can yield 4-8 dB power gain for BER values lower than 10-4 when compared to the classic linear minimum mean square error (MMSE) detector. [less ▲]

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See detailDynamic Bandwidth Allocation and Precoding Design for Highly-Loaded Multiuser MISO in Beyond 5G Networks
Vu, Thang Xuan UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Transactions on Wireless Communications (2021)

Multiuser techniques play a central role in the fifth-generation (5G) and beyond 5G (B5G) wireless networks that exploit spatial diversity to serve multiple users simultaneously in the same frequency ... [more ▼]

Multiuser techniques play a central role in the fifth-generation (5G) and beyond 5G (B5G) wireless networks that exploit spatial diversity to serve multiple users simultaneously in the same frequency resource. It is well known that a multi-antenna base station (BS) can efficiently serve a number of users not exceeding the number of antennas at the BS via precoding design. However, when there are more users than the number of antennas at the BS, conventional precoding design methods perform poorly because inter-user interference cannot be efficiently eliminated. In this paper, we investigate the performance of a highly-loaded multiuser system in which a BS simultaneously serves a number of users that is larger than the number of antennas. We propose a dynamic bandwidth allocation and precoding design framework and apply it to two important problems in multiuser systems: i) User fairness maximization and ii) Transmit power minimization, both subject to predefined quality of service (QoS) requirements. The premise of the proposed framework is to dynamically assign orthogonal frequency channels to different user groups and carefully design the precoding vectors within every user group. Since the formulated problems are non-convex, we propose two iterative algorithms based on successive convex approximations (SCA), whose convergence is theoretically guaranteed. Furthermore, we propose a low-complexity user grouping policy based on the singular value decomposition (SVD) to further improve the system performance. Finally, we demonstrate via numerical results that the proposed framework significantly outperforms existing designs in the literature. [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 detailDoA Estimation Using Low-Resolution Multi-BitSparse Array Measurements
Sedighi, Saeid UL; Mysore Rama Rao, Bhavani Shankar UL; Soltanalian, Mojtaba et al

in IEEE Signal Processing Letters (2021)

This letter studies the problem of Direction of Arrival (DoA) estimation from low-resolution few-bit quantized data collected by Sparse Linear Array (SLA). In such cases, contrary to the one-bit ... [more ▼]

This letter studies the problem of Direction of Arrival (DoA) estimation from low-resolution few-bit quantized data collected by Sparse Linear Array (SLA). In such cases, contrary to the one-bit quantization case, the well known arcsine law cannot be employed to estimate the covaraince matrix of unquantized array data. Instead, we develop a novel optimization-based framework for retrieving the covaraince matrix of unquantized array data from low-resolution few-bit measurements. The MUSIC algorithm is then applied to an augmented version of the recovered covariance matrix to find the source DoAs. The simulation results show that increasing the sampling resolution to $2$ or $4$ bits per samples could significantly increase the DoA estimation performance compared to the one-bit sampling regime while the power consumption and implementation costs is still much lower in comparison to the high-resolution sampling implementations. [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 detailOn the Asymptotic Performance of One-Bit Co-Array-Based Music
Sedighi, Saeid UL; Mysore Rama Rao, Bhavani Shankar UL; Soltanalian, Mojtaba et al

in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2021)

Co-array-based Direction of Arrival (DoA) estimation using Sparse Linear Arrays (SLAs) has recently gained considerable attention in array processing thanks to its capability of providing enhanced degrees ... [more ▼]

Co-array-based Direction of Arrival (DoA) estimation using Sparse Linear Arrays (SLAs) has recently gained considerable attention in array processing thanks to its capability of providing enhanced degrees of freedom for DoAs that can be resolved. Additionally, deployment of one-bit Analog-to-Digital Converters (ADCs) has become an important topic in array processing, as it offers both a low-cost and a low-complexity implementation. Although the problem of DoA estimation form one-bit SLA measurements has been studied in some prior works, its analytical performance has not yet been investigated and characterized. In this paper, to provide valuable insights into the performance of DoA estimation from one-bit SLA measurements, we derive an asymptotic closed-form expression for the performance of One-Bit Co-Array-Based MUSIC (OBCAB-MUSIC). Further, numerical simulations are provided to validate the asymptotic closed-form expression for the performance of OBCAB-MUSIC and to show an interesting use case of it in evaluating the resolution of OBCAB-MUSIC. [less ▲]

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See detailAnalog Beamforming with Antenna Selection for Large-Scale Antenna Arrays
Arora, Aakash UL; Tsinos, Christos; Mysore Rama Rao, Bhavani Shankar UL et al

in Proc. 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (2021)

In large-scale antenna array (LSAA) wireless communication systems employing analog beamforming architectures, the placement or selection of a subset of antennas can significantly reduce the power ... [more ▼]

In large-scale antenna array (LSAA) wireless communication systems employing analog beamforming architectures, the placement or selection of a subset of antennas can significantly reduce the power consumption and hardware complexity. In this work, we propose a joint design of analog beamforming with antenna selection (AS) or antenna placement (AP) for an analog beamforming system. We approach this problem from a beampattern matching perspective and formulate a sparse unit-modulus least-squares (SULS) problem, which is a nonconvex problem due to the unit-modulus and the sparsity constraints. To that end, we propose an efficient and scalable algorithm based on the majorization-minimization (MM) framework for solving the SULS problem. We show that the sequence of iterates generated by the algorithm converges to a stationary point of the problem. Numerical results demonstrate that the proposed joint design of analog beamforming with AS outperforms conventional array architectures with fixed inter-antenna element spacing. [less ▲]

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See detailSatellite Broadband Capacity-on-Demand: Dynamic Beam Illumination with Selective Precoding
Chen, Lin UL; Lagunas, Eva UL; Chatzinotas, Symeon UL et al

in European Signal Processing Conference (EUSIPCO), Dublin, Ireland, Aug. 2021 (2021)

Efficient satellite resource utilization is one of the key challenges in next generation high-throughput satellite communication system. In this context, dynamic coverage scheduling based on traffic ... [more ▼]

Efficient satellite resource utilization is one of the key challenges in next generation high-throughput satellite communication system. In this context, dynamic coverage scheduling based on traffic demand has emerged as a promising solution, focusing system capacity into geographical areas where it is needed. Conventional Beam Hopping (BH) satellite system exploit the time-domain flexibility, which provides all available spectrum to a selected set of beams as long as they are not adjacent to each other. However, large geographical areas involving more than one adjacent beam may require full access to the available spectrum during particular instances of time. In this paper, we address this problem by proposing a dynamic beam illumination scheme combined with selective precoding, where only sub-sets of beams that are subject to strong inter-beam interference are precoded. With selective precoding, complexity at the groundsegment is reduced and only considered when needed. Supporting results based on numerical simulations show that the proposed scheme outperforms the relevant benchmarks in terms of demand matching performance. [less ▲]

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See detailUser Scheduling for Precoded Satellite Systems With Individual Quality of Service Constraints
Trinh, van Chien UL; Lagunas, Eva UL; Tung, Ta Hai et al

in Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Virtual Conference, Sept. 2021 (2021)

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See detailEfficient Algorithms for Constant-Modulus Analog Beamforming
Arora, Aakash UL; Tsinos, Christos; Mysore Rama Rao, Bhavani Shankar UL et al

in IEEE Transactions on Signal Processing (2021)

The use of a large-scale antenna array (LSAA) has become an important characteristic of multi-antenna communication systems to achieve beamforming gains. For example, in millimeter wave (mmWave) systems ... [more ▼]

The use of a large-scale antenna array (LSAA) has become an important characteristic of multi-antenna communication systems to achieve beamforming gains. For example, in millimeter wave (mmWave) systems, an LSAA is employed at the transmitter/receiver end to combat severe propagation losses. In such applications, each antenna element has to be driven by a radio frequency (RF) chain for the implementation of fully-digital beamformers. This strict requirement significantly increases the hardware cost, complexity, and power consumption. Therefore, constant-modulus analog beamforming (CMAB) becomes a viable solution. In this paper, we consider the scaled analog beamforming (SAB) or CMAB architecture and design the system parameters by solving the beampattern matching problem. We consider two beampattern matching problems. In the first case, both the magnitude and phase of the beampattern are matched to the given desired beampattern whereas in the second case, only the magnitude of the beampattern is matched. Both the beampattern matching problems are cast as a variant of the constant-modulus least-squares problem. We provide efficient algorithms based on the alternating majorization-minimization (AMM) framework that combines the alternating minimization and the MM frameworks and the conventional-cyclic coordinate descent (C-CCD) framework to solve the problem in each case. We also propose algorithms based on a new modified-CCD (M-CCD) based approach. For all the developed algorithms we prove convergence to a Karush-Kuhn-Tucker (KKT) point (or a stationary point). Numerical results demonstrate that the proposed algorithms converge faster than state-of-the-art solutions. Among all the algorithms, the M-CCD-based algorithms have faster convergence when evaluated in terms of the number of iterations and the AMM-based algorithms offer lower complexity. [less ▲]

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See detailLocalization Performance of 1-Bit Passive Radars in NB-IoT Applications using Multivariate Polynomial Optimization
Sedighi, Saeid UL; Mishra, Kumar Vijay; Mysore Rama Rao, Bhavani Shankar UL et al

in IEEE Transactions on Signal Processing (2021), 69

Several Internet-of-Things (IoT) applications provide location-based services, wherein it is critical to obtain accurate position estimates by aggregating information from individual sensors. In the ... [more ▼]

Several Internet-of-Things (IoT) applications provide location-based services, wherein it is critical to obtain accurate position estimates by aggregating information from individual sensors. In the recently proposed narrowband IoT (NB-IoT) standard, which trades off bandwidth to gain wide coverage, the location estimation is compounded by the low sampling rate receivers and limited-capacity links. We address both of these NB-IoT drawbacks in the framework of passive sensing devices that receive signals from the target-of-interest. We consider the limiting case where each node receiver employs one-bit analog-to-digital-converters and propose a novel low-complexity nodal delay estimation method using constrained-weighted least squares minimization. To support the low-capacity links to the fusion center (FC), the range estimates obtained at individual sensors are then converted to one-bit data. At the FC, we propose target localization with the aggregated one-bit range vector using both optimal and sub-optimal techniques. The computationally expensive former approach is based on Lasserre's method for multivariate polynomial optimization while the latter employs our less complex iterative joint r\textit{an}ge-\textit{tar}get location \textit{es}timation (ANTARES) algorithm. Our overall one-bit framework not only complements the low NB-IoT bandwidth but also supports the design goal of inexpensive NB-IoT location sensing. Numerical experiments demonstrate feasibility of the proposed one-bit approach with a 0.6\% increase in the normalized localization error for the small set of 20-60 nodes over the full-precision case. When the number of nodes is sufficiently large (>80), the one-bit methods yield the same performance as the full precision. [less ▲]

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See detailPrecoding for Satellite Communications: Why, How and What next?
Mysore Rama Rao, Bhavani Shankar UL; Lagunas, Eva UL; Chatzinotas, Symeon UL et al

in IEEE Communications Letters (2021)

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See detailPrecoding with Received-Interference Power Control for Multibeam Satellite Communication Systems
Lagunas, Eva UL; Perez-Neira, Ana Isabel; Martinez, Marc et al

in Frontiers in Space Technologies (2021)

Zero-Forcing (ZF) and Regularized Zero-Forcing (RZF) precoding are low-complexity sub-optimal solutions widely accepted in the satellite communications community to mitigate the resulting co-channel ... [more ▼]

Zero-Forcing (ZF) and Regularized Zero-Forcing (RZF) precoding are low-complexity sub-optimal solutions widely accepted in the satellite communications community to mitigate the resulting co-channel interference caused by aggressive frequency reuse. However, both are sensitive to the conditioning of the channel matrix, which can greatly reduce the achievable gains. This paper brings the attention to the benefits of a design that allows some residual received interference power at the co-channel users. The motivation behind this approach is to relax the dependence on the matrix inversion procedure involved in conventional precoding schemes. In particular, the proposed scheme aims to be less sensitive to the user scheduling, which is one of the key limiting factors for the practical implementation of precoding. Furthermore, the proposed technique can also cope with more users than satellite beams. In fact, the proposed precoder can be tuned to control the interference towards the co-channel beams, which is a desirable feature that is not met by the existing RZF solutions. The design is formulated as a non-convex optimization and we study various algorithms in order to obtain a practical solution. Supporting results based on numerical simulations show that the proposed precoding implementations are able to outperform the conventional ZF and RZF schemes. [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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