Results 61-80 of 517.
Bookmark and Share    
Full Text
Peer Reviewed
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 (2021), 20(6), 3710-3722

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 ▲]

Detailed reference viewed: 112 (28 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 95 (20 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 108 (13 UL)
Full Text
Peer Reviewed
See detailCoverage Probability and Ergodic Capacity of Intelligent Reflecting Surface-Enhanced Communication Systems
Trinh, van Chien UL; Tu, Lam Thanh; Chatzinotas, Symeon UL et al

in IEEE Communications Letters (2021), 25(1), 69-73

This paper studies the performance of a single-input single-output (SISO) system enhanced by the assistance of an intelligent reflecting surface (IRS), which is equipped with a finite number of elements ... [more ▼]

This paper studies the performance of a single-input single-output (SISO) system enhanced by the assistance of an intelligent reflecting surface (IRS), which is equipped with a finite number of elements under Rayleigh fading channels. From the instantaneous channel capacity, we compute a closed-form expression of the coverage probability as a function of statistical channel information only. A scaling law of the coverage probability and the number of phase shifts is further obtained. The ergodic capacity is derived, then a simple upper bound to simplify matters of utilizing the symbolic functions and can be applied for a long period of time. Numerical results manifest the tightness and effectiveness of our closed-form expressions compared with Monte-Carlo simulations. [less ▲]

Detailed reference viewed: 128 (20 UL)
Full Text
Peer Reviewed
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 (2021), 70(1), 900-913

Non-orthogonal multiple access (NOMA) has potentials to improve the performance of multi-beam satellite systems. The performance optimization in satellite-NOMA systems could be different from that in ... [more ▼]

Non-orthogonal multiple access (NOMA) has potentials to improve the performance of multi-beam satellite systems. The performance optimization in satellite-NOMA systems could be different from that in terrestrial-NOMA systems, e.g., considering distinctive channel models, performance metrics, power constraints, and limited flexibility in resource management. In this paper, we adopt a metric, offered capacity to requested traffic ratio (OCTR), to measure the requested-offered data rate mismatch in multi-beam satellite systems. In the considered system, NOMA is applied to mitigate intra-beam interference while precoding is implemented to reduce inter-beam interference. We jointly optimize power, decoding orders, and terminal-timeslot assignment to improve the max-min fairness of OCTR. The problem is inherently difficult due to the presence of combinatorial and non-convex aspects. We first fix the terminal-timeslot assignment, and develop an optimal fast-convergence algorithmic framework based on Perron-Frobenius theory (PF) for the remaining joint power-allocation and decoding-order optimization problem. Under this framework, we propose a heuristic algorithm for the original problem, which iteratively updates the terminal-timeslot assignment and improves the overall OCTR performance. Numerical results show that the proposed algorithm improves the max-min OCTR by 40.2% over orthogonal multiple access (OMA) in average. [less ▲]

Detailed reference viewed: 244 (42 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 75 (5 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 68 (9 UL)
Full Text
Peer Reviewed
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)

Detailed reference viewed: 108 (15 UL)
Full Text
Peer Reviewed
See detailA Low-complexity Resource Optimization Technique for High Throughput Satellite
Abdu, Tedros Salih UL; Kisseleff, Steven UL; Lagunas, Eva UL et al

Scientific Conference (2021)

The high throughput satellites with flexible payloads are expected to provide a high data rate to satisfy the increasing traffic demand. Furthermore, the reconfiguration capability of flexible payloads ... [more ▼]

The high throughput satellites with flexible payloads are expected to provide a high data rate to satisfy the increasing traffic demand. Furthermore, the reconfiguration capability of flexible payloads opens the door to more advanced system optimization techniques and a better utilization of satellite resources. Consequently, we can obtain high demand satisfaction at the user side. For this, dynamically adaptive high-performance and low-complexity optimization algorithms are needed. In this paper, we propose a novel low-complexity resource optimization technique for geostationary (GEO) High Throughput Satellites. The proposed method minimizes the transmit power and the overall satellite bandwidth while satisfying the demand per beam. This optimization problem turns out to be non-convex. Hence, we convexify the problem using Dinkelbach method and Successive Convex Approximation (SCA). The simulation result shows that the proposed scheme provides better flexibility in resource allocation and requires less computational time compared to the state-of-art benchmark schemes. [less ▲]

Detailed reference viewed: 101 (27 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 187 (87 UL)
Full Text
Peer Reviewed
See detailScheduling Design and Performance Analysis of Carrier Aggregation in Satellite Communication Systems
Al-Hraishawi, Hayder UL; Maturo, Nicola UL; Lagunas, Eva UL et al

in IEEE Transactions on Vehicular Technology (2021)

Carrier Aggregation is one of the vital approaches to achieve several orders of magnitude increase in peak data rates. While carrier aggregation benefits have been extensively studied in cellular networks ... [more ▼]

Carrier Aggregation is one of the vital approaches to achieve several orders of magnitude increase in peak data rates. While carrier aggregation benefits have been extensively studied in cellular networks, its application to satellite systems has not been thoroughly explored yet. Carrier aggregation can offer an enhanced and more consistent quality of service for users throughout the satellite coverage via combining multiple carriers, utilizing the unused capacity at other carriers, and enabling effective interference management. Furthermore, carrier aggregation can be a prominent solution to address the issue of the spatially heterogeneous satellite traffic demand. This paper investigates introducing carrier aggregation to satellite systems from a link layer perspective. Deployment of carrier aggregation in satellite systems with the combination of multiple carriers that have different characteristics requires effective scheduling schemes for reliable communications. To this end, a novel load balancing scheduling algorithm has been proposed to distribute data packets across the aggregated carriers based on channel capacities and to utilize spectrum efficiently. Moreover, in order to ensure that the received data packets are delivered without perturbing the original transmission order, a perceptive scheduling algorithm has been developed that takes into consideration channel properties along with the instantaneous available resources at the aggregated carriers. The proposed modifications have been carefully designed to make carrier aggregation transparent above the medium access control (MAC) layer. Additionally, the complexity analysis of the proposed algorithms has been conducted in terms of the computational loads. Simulation results are provided to validate our analysis, demonstrate the design tradeoffs, and to highlight the potentials of carrier aggregation applied to satellite communication systems. [less ▲]

Detailed reference viewed: 126 (13 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 35 (3 UL)
Full Text
Peer Reviewed
See detailPower and Bandwidth Minimization for Demand-Aware GEO Satellite Systems
Abdu, Tedros Salih UL; Kisseleff, Steven UL; Lagunas, Eva UL et al

Scientific Conference (2021)

Smart radio resource allocation combined with the recent advances of digital payloads will allow to control the transmit power and bandwidth of the satellites depending on the demand and the channel ... [more ▼]

Smart radio resource allocation combined with the recent advances of digital payloads will allow to control the transmit power and bandwidth of the satellites depending on the demand and the channel conditions of users. The system flexibility is important not only to handle divergent demand requirements but also to efficiently utilize the limited and expensive satellite resources. In this paper, we propose a demand-aware smart radio resource allocation technique, where the transmit power and the bandwidth of the GEO satellite are minimized while satisfying the user demand. The formulated optimization problem is non-convex mixed-integer nonlinear program which is difficult to solve. Hence, we apply a quadratic transform to solve the problem iteratively. The numerical results showed that the proposed scheme outperforms the benchmark schemes in terms of bandwidth utilization while accurately providing capacity-ondemand. [less ▲]

Detailed reference viewed: 46 (6 UL)
Full Text
Peer Reviewed
See detailEfficient Preamble Detection and Time-of-Arrival Estimation for Single-Tone Frequency Hopping Random Access in NB-IoT
Chougrani, Houcine UL; Kisseleff, Steven UL; Chatzinotas, Symeon UL

in IEEE Internet of Things Journal (2021), 8(9), 7437-7449

The narrowband internet of things (NB-IoT) standard is a new cellular wireless technology, which has been introduced by the 3rd Generation Partnership Project (3GPP) with the goal to connect massive low ... [more ▼]

The narrowband internet of things (NB-IoT) standard is a new cellular wireless technology, which has been introduced by the 3rd Generation Partnership Project (3GPP) with the goal to connect massive low-cost, low-complexity and long-life IoT devices with extended coverage. In order to improve power efficiency, 3GPP proposed a new Random Access (RA) waveform for NB-IoT based on a single-tone frequencyhopping scheme. RA handles the first connection between user equipments (UEs) and the base station (BS). Through this, UEs can be identified and synchronized with the BS. In this context, receiver methods for the detection of the new waveform should satisfy the requirements on the successful user detection as well as the timing synchronization accuracy. This is not a trivial task, especially in the presence of radio impairments like carrier frequency offset (CFO) which constitutes one of the main radio impairments besides the noise. In order to tackle this problem, we propose a new receiver method for NB-IoT Physical Random Access Channel (NPRACH). The method is designed to eliminate perfectly the CFO without any additional computational complexity and supports all NPRACH preamble formats. The associated performance has been evaluated under 3GPP conditions. We observe a very high performance compared both to 3GPP requirements and to the existing state-of-the-art methods in terms of detection accuracy and complexity. [less ▲]

Detailed reference viewed: 109 (28 UL)
Full Text
Peer Reviewed
See detailOptimization of the Return Link Carrier Planning for a Constant Coding and Modulation Satellite Network
Lacoste, Clément UL; Maturo, Nicola UL; Chatzinotas, Symeon UL et al

in Frontiers in Communications and Networks (2021), 2

In this paper, we propose an approach to optimize the frequency plan and associated bandwidth allocation in the return link of a broadband satellite network, by exploring several design techniques for ... [more ▼]

In this paper, we propose an approach to optimize the frequency plan and associated bandwidth allocation in the return link of a broadband satellite network, by exploring several design techniques for carrier allocation plans. Since bandwidth is a limited resource in satellite telecommunications, the minimization of bandwidth usage is a core issue that satellite communication service providers must solve, in particular for networks using a constant coding and modulation plan, which lacks the flexibility found in newer satellite communication products and can be subject to hardware constraints. This problematic led us to raise the following question: how can the long term bandwidth requirement of the network be minimized, given a set of ground terminals, of Modulations and Codings, and of discrete bandwidths. In this document we formally define the long-term carrier allocation problem and analyze current practical solutions. We subsequently investigate two other potential solutions, found to be more bandwidth-efficient: one based on heuristics and another based on integer linear programming. Finally, we look at the impact of several parameters on the performance of those three methods. Overall we observed marginal reductions in bandwidth, however significant gains were reached for networks with small return links with low committed information rate, a case in which some constant coding and modulation networks could fall. We concluded that those networks could benefit from our methods and see a significant reduction in bandwidth, and subsequently operational costs, at low implementation costs. [less ▲]

Detailed reference viewed: 45 (3 UL)
Full Text
Peer Reviewed
See detailDemand-Aware Beam Design and User Scheduling for Precoded Multibeam GEO Satellite Systems
Jubba Honnaiah, Puneeth UL; Lagunas, Eva UL; Maturo, Nicola et al

in 25th International ITG Workshop on Smart Antennas (WSA 2021) (2021)

For many years, satellite footprints have been fixed from the design phase until the last day of the satellite operational life. Flexibility in coverage by means of reconfigurable beams is becoming ... [more ▼]

For many years, satellite footprints have been fixed from the design phase until the last day of the satellite operational life. Flexibility in coverage by means of reconfigurable beams is becoming increasingly popular thanks to the recent developments in active antenna systems. On the other hand, spatial frequency reuse combined with precoding has been shown to boost the spectral efficiency while lowering the cost per bit. In this context, and motivated by the unbalanced demand requests of the satellite users, we propose a shift from the traditional system-throughput maximization design towards a demand-Aware design, where a new beam shaping technique and user scheduling are combined to satisfy the users’ demands. Supporting numerical results are provided that validate the effectiveness of the proposed beam planning and scheduling and quantify the benefits over conventional rigid techniques. [less ▲]

Detailed reference viewed: 56 (7 UL)
Full Text
Peer Reviewed
See detailClustering-based Adaptive Beam Footprint Design for 5G Urban Macro-Cell
Jubba Honnaiah, Puneeth UL; Lagunas, Eva UL; Maturo, Nicola et al

in 2021 IEEE 4th 5G World Forum (5GWF) - Track 1: 5G Technologies (2021)

In a dense 5G urban-eMBB environment, the user density and traffic loads follow a spatiotemporal variability. To meet high traffic demands, the 5G base stations exploit spatial multiplexing by means of ... [more ▼]

In a dense 5G urban-eMBB environment, the user density and traffic loads follow a spatiotemporal variability. To meet high traffic demands, the 5G base stations exploit spatial multiplexing by means of Active Antenna Systems (AAS) and beamforming. However, pedestrian and vehicular users are highly mobile, rendering non-dynamic beamforming designs totally inefficient in terms of meeting the users’ demand requests. In particular, the latter results in either overload or underutilized beams in a cell. Hence, a practical approach to meet such spatio-temporal heterogeneous demand is to consider dynamic and adaptive beam footprint design that takes into account both the actual users’ position as well as the traffic loads. In this paper, we first study and evaluate the state-of-the-art fixed cell beamforming (based on ITU-R M.2412-0) in a test environment and highlight its drawbacks. Next, we propose a adaptive macro-cell beam footprint design where the beams are dynamically shaped based on the spatial users distribution and their demand requests. Numerical simulations demonstrate the high system performance achieved by the proposed methodology. [less ▲]

Detailed reference viewed: 68 (8 UL)