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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 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 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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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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See detailJoint User Grouping, Scheduling, and Precoding for Multicast Energy Efficiency in Multigroup Multicast Systems
Bandi, Ashok UL; Mysore Rama Rao, Bhavani Shankar UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Wireless Communications (2020)

This paper studies the joint design of user grouping, scheduling (or admission control) and precoding to optimize energy efficiency (EE) for multigroup multicast scenarios in single-cell multiuser MISO ... [more ▼]

This paper studies the joint design of user grouping, scheduling (or admission control) and precoding to optimize energy efficiency (EE) for multigroup multicast scenarios in single-cell multiuser MISO downlink channels. Noticing that the existing definition of EE fails to account for group sizes, a new metric called multicast energy efficiency (MEE) is proposed. In this context, the joint design is considered for the maximization of MEE, EE, and scheduled users. Firstly, with the help of binary variables (associated with grouping and scheduling) the joint design problem is formulated as a mixed-Boolean fractional programming problem such that it facilitates the joint update of grouping, scheduling and precoding variables. Further, several novel optimization formulations are proposed to reveal the hidden difference of convex/ concave structure in the objective and associated constraints. Thereafter, we propose a convex-concave procedure framework based iterative algorithm for each optimization criteria where grouping, scheduling, and precoding variables are updated jointly in each iteration. Finally, we compare the performance of the three design criteria concerning three performance metrics namely MEE, EE, and scheduled users through Monte-Carlo simulations. These simulations establish the need for MEE and the improvement from the system optimization. [less ▲]

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See detailNOMA-Enabled Multi-Beam Satellite Systems: Joint Optimization to Overcome Offered-Requested Data Mismatches
Wang, Anyue UL; Lei, Lei UL; Lagunas, Eva UL et al

in IEEE Transactions on Vehicular Technology (2020)

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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 (2020), 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 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 (2020)

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 detailOversampled DFT-Modulated Biorthogonal Filter Banks: Perfect Reconstruction Designs and Multiplierless Approximations
Alves Martins, Wallace UL; Shankar, Bhavani UL; Ottersten, Björn UL

in IEEE Transactions on Circuits and Systems. II, Express Briefs (2020), 67(11), 2777-2781

We propose a novel methodology for designing oversampled discrete Fourier transform-modulated uniform filter banks. The analysis prototype is designed as a Nyquist filter, whereas the synthesis prototype ... [more ▼]

We propose a novel methodology for designing oversampled discrete Fourier transform-modulated uniform filter banks. The analysis prototype is designed as a Nyquist filter, whereas the synthesis prototype is designed to guarantee perfect reconstruction (PR) considering oversampling. The resulting optimization problem fits into the disciplined convex programming framework, as long as some convex objective function is employed, as the minimization of either the stop-band energy or the maximum deviation from a desired response. The methodology also accounts for near-PR multiplierless approximations of the prototype analysis and synthesis filters, whose coefficients are obtained in the sum-of-power-of-two (SOPOT) space. The quantized coefficients are computed using successive approximation of vectors, which is able to yield filters with a reduced number of SOPOT coefficients in a computationally efficient manner. The proposed methodology is especially appealing for supporting actual hardware deployments, such as modern digital transparent processors to be used in next-generation satellite payloads. [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 (2020)

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 detailActive Popularity Learning with Cache Hit Ratio Guarantees using a Matrix Completion Committee
Bommaraveni, Srikanth UL; Vu, Thang Xuan UL; Chatzinotas, Symeon UL et al

Scientific Conference (2020, October 08)

Edge caching is a promising technology to facethe stringent latency requirements and back-haul trafficoverloading in 5G wireless networks. However, acquiringthe contents and modeling the optimal cache ... [more ▼]

Edge caching is a promising technology to facethe stringent latency requirements and back-haul trafficoverloading in 5G wireless networks. However, acquiringthe contents and modeling the optimal cache strategy is achallenging task. In this work, we use an active learningapproach to learn the content popularities since it allowsthe system to leverage the trade-off between explorationand exploitation. Exploration refers to caching new fileswhereas exploitation use known files to cache, to achievea good cache hit ratio. In this paper, we mainly focus tolearn popularities as fast as possible while guaranteeing anoperational cache hit ratio constraint. The effectiveness ofproposed learning and caching policies are demonstratedvia simulation results as a function of variance, cache hitratio and used storage. [less ▲]

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See detailHybrid Analog-Digital Precoding for mmWave Coexisting in 5G-Satellite Integrated Network
Peng, D.; Li, Y.; Chatzinotas, Symeon UL et al

in 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications, title=Hybrid Analog-Digital Precoding for mmWave Coexisting in 5G-Satellite Integrated Network (2020, October 08)

Integrating massive multiple-input multiple-output (MIMO) into satellite network is regarded as an effective strategy to improve the spectral efficiency as well as the coverage of satellite communication ... [more ▼]

Integrating massive multiple-input multiple-output (MIMO) into satellite network is regarded as an effective strategy to improve the spectral efficiency as well as the coverage of satellite communication. However, the inevitable intra-system and inter-system interference deteriorate the total performance of system. In this paper, we consider precoding in the 5G Satellite Integrated Network (5GSIN) with the deployment of Massive MIMO and propagation of shared millimeter-wave (mmWave) link. Taking the requirements of both frequency efficiency and energy assumption into account, a hybrid analog and digital pre-coding scheme in the specific scenario of 5GSIN is proposed. We model sum rate maximization problem for both of satellite and terrestrial system that incorporates maximum power constrains and minimum achievable rate requirements and formulate to a convex power allocation problem with Minimum Mean Square Error (MMSE) norm and Logarithmic Linearization method. In order to balance between performance and complexity, we propose an analog and digital separated hybrid precoding algorithm to mitigate intra-system interference. Moreover, an iterative power allocation with interference mitigation algorithm is also devised to mitigate interference from satellite to terrestrial link so that power allocation can be executed by generalized iterative algorithm. Simulation results show that our proposed hybrid precoding algorithm in 5GSIN can improve the overall spectral efficiency with a small amount of iterations. [less ▲]

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See detailResource Allocation for UAV Relay-Assisted IoT Communication Networks
Tran Dinh, Hieu UL; Nguyen, van Dinh UL; Gautam, Sumit UL et al

Scientific Conference (2020, October 06)

This work studies unmanned aerial vehicle (UAV) relay-assisted Internet of Things (IoT) communication networks in which a UAV is deployed as an aerial base station (BS) to collect time-constrained data ... [more ▼]

This work studies unmanned aerial vehicle (UAV) relay-assisted Internet of Things (IoT) communication networks in which a UAV is deployed as an aerial base station (BS) to collect time-constrained data from IoT devices and transfer information to a ground gateway (GW). In this context, we jointly optimize the allocated bandwidth, transmission power, as well as the UAV trajectory to maximize the total system throughput while satisfying the user’s latency requirement and the UAV’s limited storage capacity. The formulated problem is strongly nonconvex which is very challenging to solve optimally. Towards an appealing solution, we first introduce new variables to convert the original problem into a computationally tractable form, and then develop an iterative algorithm for its solution by leveraging the inner approximation method. Numerical results are given to show [less ▲]

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See detailRadio Resource Management Techniques for Multibeam Satellite Systems
Kisseleff, Steven UL; Lagunas, Eva UL; Abdu, Tedros Salih UL et al

in IEEE Communications Letters (2020)

Next–generation of satellite communication (SatCom) networks are expected to support extremely high data rates for a seamless integration into future large satellite-terrestrial networks. In view of the ... [more ▼]

Next–generation of satellite communication (SatCom) networks are expected to support extremely high data rates for a seamless integration into future large satellite-terrestrial networks. In view of the coming spectral limitations, the main challenge is to reduce the cost (satellite launch and operation) per bit, which can be achieved by enhancing the spectral efficiencies. In addition, the capability to quickly and flexibly assign radio resources according to the traffic demand distribution has become a must for future multibeam broadband satellite systems. This article presents the radio resource management problems encountered in the design of future broadband SatComs and provides a comprehensive overview of the available techniques to address such challenges. Firstly, we focus on the demand matching formulation of the power and bandwidth assignment. Secondly, we present the scheduling design in practical multibeam satellite systems. Finally, a number of future challenges and the respective open research topics are described. [less ▲]

Detailed reference viewed: 196 (63 UL)