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See detailRESOURCE MANAGEMENT TECHNIQUES FOR FLEXIBLE BROADBAND SATELLITE COMMUNICATION SYSTEMS
Abdu, Tedros Salih UL

Doctoral thesis (2022)

The application of Satellite Communications (SatCom) has recently evolved from providing simple Direct-To-Home television (DTHTV) to enable a range of broadband internet services. Typically, it offers ... [more ▼]

The application of Satellite Communications (SatCom) has recently evolved from providing simple Direct-To-Home television (DTHTV) to enable a range of broadband internet services. Typically, it offers services to the broadcast industry, the aircraft industry, the maritime sector, government agencies, and end-users. Furthermore, SatCom has a significant role in the era of 5G and beyond in terms of integrating satellite networks with terrestrial networks, offering backhaul services, and providing coverage for the Internet of Things (IoT) applications. Moreover, thanks to the satellite's wide coverage area, it can provide services to remote areas where terrestrial networks are inaccessible or expensive to connect. Due to the wide range of satellite applications outlined above, the demand for satellite service from user terminals is rapidly increasing. Conventionally, satellites use multi-beam technology with uniform resource allocation to provide service to users/beams. In this case, the satellite's resources, such as power and bandwidth, are evenly distributed among the beams. However, this resource allocation method is inefficient since it does not consider the heterogeneous demands of each beam, which may result in a beam with a low demand receiving too many resources while a beam with a high demand receiving few resources. Consequently, we may not satisfy some beam demands. Additionally, satellite resources are limited due to spectrum regulations and onboard batteries constraint, which require proper utilization. Therefore, the next generation of satellites must address the above main challenges of conventional satellites. For this, in this thesis, novel advanced resource management techniques are proposed to manage satellite resources efficiently while accommodating heterogeneous beam demands. In the above context, the second and third chapters of the thesis explore on-demand resource allocation methods with no precoding technique. These methods aim to closely match the beam traffic demand by using the minimum transmit power and utilized bandwidth while having tolerable interference among the beams. However, an advanced interference mitigation technique is required in a high interference scenario. Thus, in the fourth chapter of the thesis, we propose a combination of resource allocation and interference management strategies to mitigate interference and meet high-demand requirements with less power and bandwidth consumption. In this context, the performance of the resource management method for systems with full precoding, that is, all beams are precoded; without precoding, that is, no precoding is applied to any beams; and with partial precoding, that is, some beams are precoded, is investigated and compared. Thanks to emerging technologies, the next generation of satellite communication systems will deploy onboard digital payloads; thus, advanced resource management techniques can be implemented. In this case, the digital payload can be configured to change the bandwidth, carrier frequency, and transmit power of the system in response to heterogeneous traffic demands. Typically, onboard digital payloads consist of payload processors, each operating with specific power and bandwidth to process each beam signal. There are, however, only a limited number of processors, thus requiring proper management. Furthermore, the processors consume more energy to process the signals, resulting in high power consumption. Therefore, payload management will be crucial for future satellite generation. In this context, the fifth chapter of the thesis proposes a demand-aware onboard payload processor management method, which switches on the processors according to the beam demand. In this case, for low demand, fewer processors are in-use, while more processors become necessary as demand increases. Demand-aware resource allocation techniques may require optimization of large variables. Consequently, this may increase the computational time complexity of the system. Thus, the sixth chapter of the thesis explores the methods of combining demand-aware resource allocation and deep learning (DL) to reduce the computational complexity of the system. In this case, a demand-aware algorithm enables bandwidth and power allocation, while DL can speed up computation. Finally, the last chapter provides the main conclusions of the thesis, as well as the future research directions. [less ▲]

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See detailDemand and Interference Aware Adaptive Resource Management for High Throughput GEO Satellite Systems
Abdu, Tedros Salih UL; Kisseleff, Steven UL; Lagunas, Eva UL et al

in IEEE Open Journal of the Communications Society (2022)

The scarce spectrum and power resources, the inter-beam interference, together with the high traffic demand, pose new major challenges for the next generation of Very High Throughput Satellite (VHTS ... [more ▼]

The scarce spectrum and power resources, the inter-beam interference, together with the high traffic demand, pose new major challenges for the next generation of Very High Throughput Satellite (VHTS) systems. Accordingly, future satellites are expected to employ advanced resource/interference management techniques to achieve high system spectrum efficiency and low power consumption while ensuring user demand satisfaction. This paper proposes a novel demand and interference aware adaptive resource management for geostationary (GEO) VHTS systems. For this, we formulate a multi-objective optimization problem to minimize the total transmit power consumption and system bandwidth usage while matching the offered capacity with the demand per beam. In this context, we consider resource management for a system with full-precoding, i.e. all beams are precoded; without precoding, i.e. no precoding is applied to any beam; and with partial precoding, i.e. only some beams are precoded. The nature of the problem is non-convex and we solve it by jointly using the Dinkelbach and Successive Convex Approximation (SCA) methods. The simulation results show that the proposed method outperforms the benchmark schemes. Specifically, we show that the proposed method requires low resource consumption, low computational time, and simultaneously achieves a high demand satisfaction. [less ▲]

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See detailEnergy Efficient Sparse Precoding Design for Satellite Communication System
Abdu, Tedros Salih UL; Kisseleff, Steven UL; Lagunas, Eva UL et al

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 ▲]

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See detailFlexible Resource Optimization for GEO Multibeam Satellite Communication System
Abdu, Tedros Salih UL; Kisseleff, Steven UL; Lagunas, Eva UL et al

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 ▲]

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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 (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 ▲]

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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 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 ▲]

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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 ▲]

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See detailCarrier and Power Assignment for Flexible Broadband GEO Satellite Communications System
Abdu, Tedros Salih UL; Lagunas, Eva UL; Kisseleff, Steven et al

in PIMRC 2020 Proceedings (2020)

Current multi-beam GEO satellite systems operate under a limited frequency reuse configuration and considering uniform power assignment across beams. The latter has been shown to be inefficient in ... [more ▼]

Current multi-beam GEO satellite systems operate under a limited frequency reuse configuration and considering uniform power assignment across beams. The latter has been shown to be inefficient in matching the geographic distribution of the traffic demand. In this context, next generation of broadband GEO satellite systems will be equipped with more flexible and reconfigurable payloads, facilitating on-demand resource allocation. In this paper, we consider both carrier and power assignment to match the requested beam demands while minimizing the total transmit power and the total utilized bandwidth. A novel optimization problem is formulated and, given its non-convex structure, we divide the problem into two tractable sub-problems. First, we estimate the number of adjacent frequency carriers required for each beam to satisfy its demand and, subsequently, we optimize the power allocation based on the previously assigned carriers. We validate the proposed method with extensive numerical results, which demonstrate its efficiency with respect to benchmark strategies. [less ▲]

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