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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 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 detailSystem Modelling and Design Aspects of Next Generation High Throughput Satellites
Sharma, Shree Krishna UL; Querol, Jorge UL; Maturo, Nicola UL et al

in IEEE Communications Letters (2021), 69

As compared to terrestrial systems, the design of Satellite Communication (SatCom) systems require a different approach due to differences in terms of wave propagation, operating frequency, antenna ... [more ▼]

As compared to terrestrial systems, the design of Satellite Communication (SatCom) systems require a different approach due to differences in terms of wave propagation, operating frequency, antenna structures, interfering sources, limitations of onboard processing, power limitations and transceiver impairments. In this regard, this letter aims to identify and discuss important modeling and design aspects of the next generation High Throughput Satellite (HTS) systems. First, communication models of HTSs including the ones for multibeam and multicarrier satellites, multiple antenna techniques, and for SatCom payloads and antennas are highlighted and discussed. Subsequently, various design aspects of SatCom transceivers including impairments related to the transceiver, payload and channel, and traffic-based coverage adaptation are presented. Finally, some open topics for the design of next generation HTSs are identified and discussed. [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 detailPrecoding-Aided Bandwidth Optimization for High Throughput Satellite Systems
Abdu, Tedros Salih UL; Lei, Lei UL; Kisseleff, Steven UL et al

Scientific Conference (2021)

Linear precoding boosts the spectral efficiency of the satellite system by mitigating the interference signal. Typically, all users are precoded and share the same bandwidth regardless of the user demand ... [more ▼]

Linear precoding boosts the spectral efficiency of the satellite system by mitigating the interference signal. Typically, all users are precoded and share the same bandwidth regardless of the user demand. This bandwidth utilization is not efficient since the user demand permanently varies. Hence, demand-aware bandwidth allocation with linear precoding is promising. In this paper, we exploited the synergy of linear precoding and flexible bandwidth allocation for geostationary (GEO) high throughput satellite systems. We formulate an optimization problem with the goal to satisfy the demand by taking into account that multiple precoded user groups can share the different bandwidth chunks. Hence, optimal beam groups are selected with minimum bandwidth requirement to match the per beam demand. The simulation results show that the proposed method of combining bandwidth allocation and linear precoding has better bandwidth efficiency and demand satisfaction than benchmark schemes. [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 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 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 detailInterference Mitigation Methods for Coexistence of Radar and Communication
Kumar, Sumit UL; Mishra, Vijay Kumar; Mysore Rama Rao, Bhavani Shankar UL et al

in 15th European Conference on Antennas and Propagation (EuCAP) (2021)

We consider a communications-centric spectrum sharing scenario where the communications link has a minimum service constraint in throughput and the radar maximizes its receive signal-to-interference-plus ... [more ▼]

We consider a communications-centric spectrum sharing scenario where the communications link has a minimum service constraint in throughput and the radar maximizes its receive signal-to-interference-plus-noise ratio (SINR). Prior works on joint power, allocation indicate that, under a communication-centric scenario, radar transmit power is gradually reduced as the throughput demand for communications link increases. Such an approach results in severe degradation of radar SINR, especially when the communications link suffers an outage. We propose methods based on successive-interference-cancellation to improve the radar SINR. This comprises both coexistence and coordination approaches. Numerical experiments show significant improvement in radar SINR when communications throughput demand rises and eventually goes into the outage. [less ▲]

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See detailGeneralized Multiplexed Waveform Design Framework for Cost-Optimized MIMO Radar
Hammes, C.; R., B. S. M.; Ottersten, Björn UL

in IEEE Transactions on Signal Processing (2021), 69

Cost-optimization through the minimization of hardware and processing costs with minimal loss in performance is an interesting design paradigm in evolving and emerging Multiple-Input-Multiple-Output (MIMO ... [more ▼]

Cost-optimization through the minimization of hardware and processing costs with minimal loss in performance is an interesting design paradigm in evolving and emerging Multiple-Input-Multiple-Output (MIMO) radar systems. This optimization is a challenging task due to the increasing Radio Frequency (RF) hardware complexity as well as the signal design algorithm complexity in applications requiring high angular resolution. Towards addressing these, the paper proposes a low-complexity signal design framework, which incorporates a generalized time multiplex scheme for reducing the RF hardware complexity with a subsequent discrete phase modulation. The scheme further aims at achieving simultaneous transmit beamforming and maximum virtual MIMO aperture to enable better target detection and discrimination performance. Furthermore, the paper proposes a low-complexity signal design scheme for beampattern matching in the aforementioned setting. The conducted performance evaluation indicates that the listed design objectives are met. [less ▲]

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See detailOn performance characterization of cascaded multiwire-PLC/MIMO-RF communication system
Ai, Yun; Kong, Long; Cheffena, Michael et al

in 2021 29th European Signal Processing Conference (EUSIPCO) (2021)

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See detailAn Overview of Information-Theoretic Secrecy Analysis over Classical Wiretap Fading Channels
Kong; Ai, Yun; Lei, Lei et al

in EURASIP Journal on Wireless Communications and Networking (2021)

An alternative or supplementary approach named as physical layer security has been recently proposed to afford an extra security layer on top of the conventional cryptography technique. In this paper, an ... [more ▼]

An alternative or supplementary approach named as physical layer security has been recently proposed to afford an extra security layer on top of the conventional cryptography technique. In this paper, an overview of secrecy performance investigations over the classic Alice-Bob-Eve wiretap fading channels is conducted. On the basis of the classic wiretap channel model, we have comprehensively listed and thereafter compared the existing works on physical layer secrecy analysis considering the small-scale, large-scale, composite, and cascaded fading channel models. Exact secrecy metrics expressions, including secrecy outage probability (SOP), the probability of non-zero secrecy capacity (PNZ), and average secrecy capacity (ASC), and secrecy bounds, including the lower bound of SOP and ergodic secrecy capacity, are presented. In order to encompass the aforementioned four kinds of fading channel models with a more generic and flexible distribution, the mixture gamma (MG), mixture of Gaussian (MoG), and Fox’s H- function distributions are three useful candidates to largely include the above-mentioned four kinds of fading channel models. It is shown that all they are flexible and general when assisting the secrecy analysis to obtain closed-form expressions. Their advantages and limitations are also highlighted. Conclusively, these three approaches are proven to provide a unified secrecy analysis framework and can cover all types of independent wiretap fading channel models. Apart from those, revisiting the existing secrecy enhancement techniques based on our system configuration, the on-off transmission scheme, artificial noise (AN) & artificial fast fading (AFF), jamming approach, antenna selection, and security region are presented. [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 (2021), 14

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 detailUplink Power Control in Massive MIMO with Double Scattering Channels
Trinh, van Chien UL; Ngo, Quoc Hien; Chatzinotas, Symeon UL et al

in IEEE Transactions on Wireless Communications (2021)

Massive multiple-input multiple-output (MIMO) is a key technology for improving the spectral and energy efficiency in 5G-and-beyond wireless networks. For a tractable analysis, most of the previous works ... [more ▼]

Massive multiple-input multiple-output (MIMO) is a key technology for improving the spectral and energy efficiency in 5G-and-beyond wireless networks. For a tractable analysis, most of the previous works on Massive MIMO have been focused on the system performance with complex Gaussian channel impulse responses under rich-scattering environments. In contrast, this paper investigates the uplink ergodic spectral efficiency (SE) of each user under the double scattering channel model. We derive a closed-form expression of the uplink ergodic SE by exploiting the maximum ratio (MR) combining technique based on imperfect channel state information. We further study the asymptotic SE behaviors as a function of the number of antennas at each base station (BS) and the number of scatterers available at each radio channel. We then formulate and solve a total energy optimization problem for the uplink data transmission that aims at simultaneously satisfying the required SEs from all the users with limited data power resource. Notably, our proposed algorithms can cope with the congestion issue appearing when at least one user is served by lower SE than requested. Numerical results illustrate the effectiveness of the closed-form ergodic SE over Monte-Carlo simulations. Besides, the system can still provide the required SEs to many users even under congestion. [less ▲]

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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 detailTransfer Learning and Meta Learning Based Fast Downlink Beamforming Adaptation
Yuan, Yi; Zheng, G.; Wong, K.-K. et al

in IEEE Transactions on Wireless Communications (2021)

This paper studies fast adaptive beamforming optimization for the signal-to-interference-plus-noise ratio balancing problem in a multiuser multiple-input single-output downlink system. Existing deep ... [more ▼]

This paper studies fast adaptive beamforming optimization for the signal-to-interference-plus-noise ratio balancing problem in a multiuser multiple-input single-output downlink system. Existing deep learning based approaches to predict beamforming rely on the assumption that the training and testing channels follow the same distribution which may not hold in practice. As a result, a trained model may lead to performance deterioration when the testing network environment changes. To deal with this task mismatch issue, we propose two offline adaptive algorithms based on deep transfer learning and meta-learning, which are able to achieve fast adaptation with the limited new labelled data when the testing wireless environment changes. Furthermore, we propose an online algorithm to enhance the adaptation capability of the offline meta algorithm in realistic non-stationary environments. Simulation results demonstrate that the proposed adaptive algorithms achieve much better performance than the direct deep learning algorithm without adaptation in new environments. The meta-learning algorithm outperforms the deep transfer learning algorithm and achieves near optimal performance. In addition, compared to the offline meta-learning algorithm, the proposed online meta-learning algorithm shows superior adaption performance in changing environments. [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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See detailState Aggregation for Multiagent Communication over Rate-Limited Channels
Mostaani, Arsham UL; Vu, Thang Xuan UL; Chatzinotas, Symeon UL et al

in State Aggregation for Multiagent Communication over Rate-Limited Channels (2020, December)

A collaborative task is assigned to a multiagent system (MAS) in which agents are allowed to communicate. The MAS runs over an underlying Markov decision process and its task is to maximize the averaged ... [more ▼]

A collaborative task is assigned to a multiagent system (MAS) in which agents are allowed to communicate. The MAS runs over an underlying Markov decision process and its task is to maximize the averaged sum of discounted one-stage rewards. Although knowing the global state of the environment is necessary for the optimal action selection of the MAS, agents are limited to individual observations. The inter-agent communication can tackle the issue of local observability, however, the limited rate of the inter-agent communication prevents the agent from acquiring the precise global state information. To overcome this challenge, agents need to communicate their observations in a compact way such that the MAS compromises the minimum possible sum of rewards. We show that this problem is equivalent to a form of rate-distortion problem which we call the task-based information compression. State Aggregation for Information Compression (SAIC) is introduced here to perform the task-based information compression. The SAIC is shown, conditionally, to be capable of achieving the optimal performance in terms of the attained sum of discounted rewards. The proposed algorithm is applied to a rendezvous problem and its performance is compared with two benchmarks; (i) conventional source coding algorithms and the (ii) centralized multiagent control using reinforcement learning. Numerical experiments confirm the superiority and fast convergence of the proposed SAIC. [less ▲]

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See detailConstant Envelope MIMO-OFDM Precoding for Low Complexity Large-Scale Antenna Array Systems
Domouchtsidis, Stavros UL; Tsinos, Christos UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Wireless Communications (2020)

Herein, we consider constant envelope precoding in a multiple-input multiple-output orthogonal frequency division multiplexing system (CE MIMO-OFDM) for frequency selective channels. In CE precoding the ... [more ▼]

Herein, we consider constant envelope precoding in a multiple-input multiple-output orthogonal frequency division multiplexing system (CE MIMO-OFDM) for frequency selective channels. In CE precoding the signals for each transmit antenna are designed to have constant amplitude regardless of the channel realization and the information symbols that must be conveyed to the users. This facilitates the use of power-efficient components, such as phase shifters (PS) and nonlinear power amplifiers, which are key for the feasibility of large-scale antenna array systems because of their low cost and power consumption. The CE precoding problem is firstly formulated as a least-squares problem with a unit modulus constraint and solved using an algorithm based on coordinate descent. The large number of optimization variables in the case of the MIMO-OFDM system motivates the search for a more computationally efficient solution. To tackle this, we reformulate the CE precoding design into an unconstrained nonlinear least-squares problem, which is solved efficiently using the Gauss-Newton algorithm. Simulation results underline the efficiency of the proposed solutions and show that they outperform state of the art techniques. [less ▲]

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