User Scheduling and Power Allocation for Precoded Multi-Beam High Throughput Satellite Systems With Individual Quality of Service Constraints

in IEEE Transactions on Vehicular Technology (2022)

Performance Evaluation of Forward Link Packet Scheduling in Satellite Communication Systems with Carrier Aggregation

Scientific Conference (2022)

The rapidly growing demand for increased data rates and spectrum scarcity in satellite communication systems require new paradigms to effectively utilize radio resources. Of many candidate techniques ... [more ▼]

The rapidly growing demand for increased data rates and spectrum scarcity in satellite communication systems require new paradigms to effectively utilize radio resources. Of many candidate techniques, carrier aggregation (CA) is a promising solution that combines multiple carriers across the available spectrum to achieve a substantial increase in peak data rate and improve user experience. The concept of CA was introduced in 3GPP standards for the terrestrial communication systems and has been successfully deployed and commercialized worldwide. Recently, satellite communication community has investigated the requirements for adopting CA technique to satellite infrastructures. In this setting, aggregating multiple heterogeneous satellite links to boost a single-user peak throughput requires an efficient data packet scheduler at the gateway in order to avoid the out-of-order packet issues and the subsequent queuing delays at the receiver side. Thereby, several research efforts have been devoted to circumvent this challenge through developing packet schedulers that are aiming at delivering data packets without perturbing their original transmission order. In this paper, the performance of the developed schedulers is evaluated using end-to-end system simulations to investigate the impact of different network metrics. The obtained results demonstrate the design tradeoffs and summarize the pros and cons of the schedulers. [less ▲]

User Scheduling and Power Allocation for Precoded Multi-Beam High Throughput Satellite Systems With Individual Quality of Service Constraints

in IEEE Transactions on Vehicular Technology (Early Access) (2022)

For extensive coverage areas, multi-beam high throughput satellite (HTS) communication is a promising technology that plays a crucial role in delivering broadband services to many users with diverse ... [more ▼]

For extensive coverage areas, multi-beam high throughput satellite (HTS) communication is a promising technology that plays a crucial role in delivering broadband services to many users with diverse Quality of Service (QoS) requirements. This paper focuses on multi-beam HTS systems where all beams reuse the same spectrum. In particular, we propose a novel user scheduling and power allocation design capable of providing guarantees in terms of the individual QoS requirements while maximizing the system throughput under a limited power budget. Precoding is employed in the forward link to mitigate mutual interference among the users in multiple-access scenarios over different coherence time intervals. The combinatorial optimization structure from user scheduling requires an extremely high cost to obtain the global optimum even when a reduced number of users fit into a time slot. Therefore, we propose a heuristic algorithm yielding a good trade-off between performance and computational complexity, applicable to a static operation framework of geostationary (GEO) satellite networks. Although the power allocation optimization is signomial programming, non-convex on a standard form, the solution can be lower bounded by the global optimum of a geometric program with a hidden convex structure. A local solution to the joint user scheduling and power allocation problem is consequently obtained by a successive optimization approach. Numerical results demonstrate the effectiveness of our algorithms on GEO satellite networks by providing better QoS satisfaction combined with outstanding overall system throughput. [less ▲]

Energy Efficient Sparse Precoding Design for Satellite Communication System

Scientific Conference (2022)

Through precoding, the spectral efficiency of the system can be improved; thus, more users can benefit from 5G and beyond broadband services. However, complete precoding (using all precoding coefficients ... [more ▼]

Through precoding, the spectral efficiency of the system can be improved; thus, more users can benefit from 5G and beyond broadband services. However, complete precoding (using all precoding coefficients) may not be possible in practice due to the high signal processing complexity involved in calculating a large number of precoding coefficients and combining them with symbols for transmission. In this paper, we propose an energy-efficient sparse precoding design, where only a few precoding coefficients are used with lower power consumption depending on the demand. In this context, we formulate an optimization problem that minimizes the number of in-use precoding coefficients and the system power consumption while matching the per beam demand. This problem is nonconvex. Hence, we apply Lagrangian relaxation and successive convex approximation to convexify it. The proposed solution outperforms the benchmark scheme in power consumption and demand satisfaction with the additional advantage of sparse precoding design. [less ▲]

JOINT CARRIER ALLOCATION AND PRECODING OPTIMIZATION FOR INTERFERENCE-LIMITED GEO SATELLITE

Scientific Conference (2022)

The rise of flexible payloads on satellites opens a door for controlling satellite resources according to the user demand, user location, and satellite position. In addition to resource management ... [more ▼]

The rise of flexible payloads on satellites opens a door for controlling satellite resources according to the user demand, user location, and satellite position. In addition to resource management, applying precoding on flexible payloads is essential to obtain high spectral efficiency. However, these cannot be achieved using a conventional resource allocation algorithm that does not consider the user demand. In this paper, we propose a demand-aware algorithm based on multiobjective optimization to jointly design the carrier allocation and precoding for better spectral efficiency and demand matching with proper management of the satellite resources. The optimization problem is non-convex, and we solve it using convex relaxation and successive convex approximation. Then, we evaluate the performance of the proposed algorithm through numerical results. It is shown that the proposed method outperforms the benchmark schemes in terms of resource utilization and demand satisfaction. [less ▲]

Joint Beam Hopping and Carrier Aggregation in High Throughput Multi-Beam Satellite Systems

in IEEE Access (2022)

Beam hopping (BH) and carrier aggregation (CA) are two promising technologies for the next generation satellite communication systems to achieve several orders of magnitude increase in system capacity and ... [more ▼]

Beam hopping (BH) and carrier aggregation (CA) are two promising technologies for the next generation satellite communication systems to achieve several orders of magnitude increase in system capacity and to significantly improve the spectral efficiency. While BH allows a great flexibility in adapting the offered capacity to the heterogeneous demand, CA further enhances the user quality-of-service (QoS) by allowing it to pool resources from multiple adjacent beams. In this paper, we consider a multi-beam high throughput satellite (HTS) system that employs BH in conjunction with CA to capitalize on the mutual interplay between both techniques. Particularly, an innovative joint BH-CA scheme is proposed and analyzed in this work to utilize their individual competencies. This includes designing an efficient joint time-space beam illumination pattern for BH and multi-user aggregation strategy for CA. Through this, user-carrier assignment, transponder filling-rates, beams hopping pattern, and illumination duration are all simultaneously optimized by formulating a joint optimization problem as a multi-objective mixed integer linear programming problem (MINLP). Simulation results are provided to corroborate our analysis, demonstrate the design tradeoffs, and point out the potentials of the proposed joint BH-CA concept. Advantages of our BH-CA scheme versus the conventional BH method without employing CA are investigated and presented under the same system circumstances. [less ▲]

QoE-Oriented Resource Allocation Design Coping with Time-Varying Demands in Wireless Communication Networks

in IEEE 96st Vehicular Technology Conference, London-Beijing, Sept. 2022 (2022)

Flexible Resource Optimization for GEO Multibeam Satellite Communication System

in IEEE Transactions on Wireless Communications (2021)

Conventional GEO satellite communication systems rely on a multibeam foot-print with a uniform resource allocation to provide connectivity to users. However, applying uniform resource allocation is ... [more ▼]

Conventional GEO satellite communication systems rely on a multibeam foot-print with a uniform resource allocation to provide connectivity to users. However, applying uniform resource allocation is inefficient in presence of non-uniform demand distribution. To overcome this limitation, the next generation of broadband GEO satellite systems will enable flexibility in terms of power and bandwidth assignment, enabling on-demand resource allocation. In this paper, we propose a novel satellite resource assignment design whose goal is to satisfy the beam traffic demand by making use of the minimum transmit power and utilized bandwidth. The motivation behind the proposed design is to maximize the satellite spectrum utilization by pushing the spectrum reuse to affordable limits in terms of tolerable interference. The proposed problem formulation results in a non-convex optimization structure, for which we propose an efficient tractable solution. We validate the proposed method with extensive numerical results, which demonstrate the efficiency of the proposed approach with respect to benchmark schemes. [less ▲]

Radio Resource Management Techniques for Multibeam Satellite Systems

in IEEE Communications Letters (2021), 25(8), 2448-2452

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 ▲]

Completion Time Minimization in NOMA Systems:Learning for Combinatorial Optimization

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 ▲]