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See detailTHz-Empowered UAVs in 6G: Opportunities, Challenges, and Trade-Offs
Azari, Mohammad Mahdi UL; Solanki, Sourabh UL; Chatzinotas, Symeon UL et al

in IEEE Communications Magazine (in press)

Envisioned use cases of unmanned aerial vehicles (UAVs) impose new service requirements in terms of data rate, latency, and sensing accuracy, to name a few. If such requirements are satisfactorily met, it ... [more ▼]

Envisioned use cases of unmanned aerial vehicles (UAVs) impose new service requirements in terms of data rate, latency, and sensing accuracy, to name a few. If such requirements are satisfactorily met, it can create novel applications and enable highly reliable and harmonized integration of UAVs in the 6G network ecosystem. Towards this, terahertz (THz) bands are perceived as a prospective technological enabler for various improved functionalities such as ultra-high throughput and enhanced sensing capabilities. This paper focuses on THz-empowered UAVs with the following capabilities: communication, sensing, localization, imaging, and control. We review the potential opportunities and use cases of THz-empowered UAVs, corresponding novel design challenges, and resulting trade-offs. Furthermore, we overview recent advances in UAV deployments regulations, THz standardization, and health aspects related to THz bands. Finally, we take UAV to UAV (U2U) communication as a case-study to provide numerical insights into the impact of various system design parameters and environment factors. [less ▲]

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See detailIntelligent Blockchain-based Edge Computing via Deep Reinforcement Learning: Solutions and Challenges
Nguyen, Dinh C; Nguyen, van Dinh UL; Ding, Ming et al

in IEEE Network (in press)

The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in wireless Internet-of-Things networks, by enabling task offloading with security enhancement ... [more ▼]

The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in wireless Internet-of-Things networks, by enabling task offloading with security enhancement based on blockchain mining. Yet the existing approaches for these enabling technologies are isolated, providing only tailored solutions for specific services and scenarios. To fill this gap, we propose a novel cooperative task offloading and blockchain mining (TOBM) scheme for a blockchain-based MEC system, where each edge device not only handles computation tasks but also deals with block mining for improving system utility. To address the latency issues caused by the blockchain operation in MEC, we develop a new Proof-of-Reputation consensus mechanism based on a lightweight block verification strategy. To accommodate the highly dynamic environment and high-dimensional system state space, we apply a novel distributed deep reinforcement learning-based approach by using a multi-agent deep deterministic policy gradient algorithm. Experimental results demonstrate the superior performance of the proposed TOBM scheme in terms of enhanced system reward, improved offloading utility with lower blockchain mining latency, and better system utility, compared to the existing cooperative and non-cooperative schemes. The paper concludes with key technical challenges and possible directions for future blockchain-based MEC research. [less ▲]

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See detailAmbient Backscatter Assisted Co-Existence in Aerial-IRS Wireless Networks
Solanki, Sourabh UL; Gautam, Sumit; Sharma, Shree Krishna et al

in IEEE Open Journal of the Communications Society (in press)

Ambient backscatter communication (AmBC) is an emerging technology that has the potential to offer spectral- and energy-efficient solutions for the next generation wireless communications networks ... [more ▼]

Ambient backscatter communication (AmBC) is an emerging technology that has the potential to offer spectral- and energy-efficient solutions for the next generation wireless communications networks, especially for the Internet of Things (IoT). Intelligent reflecting surfaces (IRSs) are also perceived to be an integral part of the beyond 5G systems to complement the traditional relaying scheme. To this end, this paper proposes a novel system design that enables the co-existence of a backscattering secondary system with the legacy primary system. This co-existence is primarily driven by leveraging the AmBC technique in IRS-assisted unmanned aerial vehicle (UAV) networks. More specifically, an aerial-IRS mounted on a UAV is considered to be employed for cooperatively relaying the transmitted signal from a terrestrial primary source node to a user equipment on the ground. Meanwhile, capitalizing on the AmBC technology, a backscatter capable terrestrial secondary node transmits its information to a terrestrial secondary receiver by modulating and backscattering the ambient relayed radio frequency signals from the UAV-IRS. We comprehensively analyze the performance of the proposed design framework with co-existing systems by deriving the outage probability and ergodic spectral efficiency expressions. Moreover, we also investigate the asymptotic behaviour of outage performance in high transmit power regimes for both primary and secondary systems. Importantly, we analyze the performance of the primary system by considering two different scenarios i.e., optimal phase shifts design and random phase shifting at IRS. Finally, based on the analytical performance assessment, we present numerical results to provide various useful insights and also provide simulation results to corroborate the derived theoretical results. [less ▲]

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See detailAsymptotic Analysis of Max-Min Weighted SINR for IRS-Assisted MISO Systems with Hardware Impairments
Papazafeiropoulo, Anastasios; Pan, Cunhua; Elbir, Ahmet et al

in IEEE Wireless Communications Letters (in press)

We focus on the realistic maximization of the up-link minimum-signal-to-interference-plus-noise ratio (SINR) of a general multiple-input-single-output (MISO) system assisted by an intelligent reflecting ... [more ▼]

We focus on the realistic maximization of the up-link minimum-signal-to-interference-plus-noise ratio (SINR) of a general multiple-input-single-output (MISO) system assisted by an intelligent reflecting surface (IRS) in the large system limit accounting for HIs. In particular, we introduce the HIs at both the IRS (IRS-HIs) and the transceiver HIs (AT-HIs), usually neglected despite their inevitable impact. Specifically, the deterministic equivalent analysis enables the derivation of the asymptotic weighted maximum-minimum SINR with HIs by jointly optimizing the HIs-aware receiver, the transmit power, and the reflect beamforming matrix (RBM). Notably, we obtain the optimal power allocation and reflect beamforming matrix with low overhead instead of their frequent necessary computation in conventional MIMO systems based on the instantaneous channel information. Monte Carlo simulations verify the analytical results which show the insightful interplay among the key parameters and the degradation of the performance due to HIs. [less ▲]

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See detailFedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud System
Nguyen, van Dinh UL; Chatzinotas, Symeon UL; Ottersten, Björn UL et al

in IEEE Transactions on Wireless Communications (in press)

Federated learning (FL) is capable of performing large distributed machine learning tasks across multiple edge users by periodically aggregating trained local parameters. To address key challenges of ... [more ▼]

Federated learning (FL) is capable of performing large distributed machine learning tasks across multiple edge users by periodically aggregating trained local parameters. To address key challenges of enabling FL over a wireless fogcloud system (e.g., non-i.i.d. data, users’ heterogeneity), we first propose an efficient FL algorithm based on Federated Averaging (called FedFog) to perform the local aggregation of gradient parameters at fog servers and global training update at the cloud. Next, we employ FedFog in wireless fog-cloud systems by investigating a novel network-aware FL optimization problem that strikes the balance between the global loss and completion time. An iterative algorithm is then developed to obtain a precise measurement of the system performance, which helps design an efficient stopping criteria to output an appropriate number of global rounds. To mitigate the straggler effect, we propose a flexible user aggregation strategy that trains fast users first to obtain a certain level of accuracy before allowing slow users to join the global training updates. Extensive numerical results using several real-world FL tasks are provided to verify the theoretical convergence of FedFog. We also show that the proposed co-design of FL and communication is essential to substantially improve resource utilization while achieving comparable accuracy of the learning model. [less ▲]

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See detailTerminal-Aware Multi-Connectivity Scheduler for Uplink Multi-Layer Non-Terrestrial Networks
Dazhi, Michael UL; Al-Hraishawi, Hayder UL; Mysore Rama Rao, Bhavani Shankar UL et al

Scientific Conference (2022, December)

This paper introduces the concept of multi-connectivity (MC) to the multi-orbit non-terrestrial networks (NTNs), where user terminals can be served by more than one satellite to achieve higher peak ... [more ▼]

This paper introduces the concept of multi-connectivity (MC) to the multi-orbit non-terrestrial networks (NTNs), where user terminals can be served by more than one satellite to achieve higher peak throughput. MC is a technique initially introduced by the 3rd Generation Partnership Project (3GPP) for terrestrial communications in 4G and 5G, it has shown much gain in the terrestrial domain and this paper explores areas where this concept can benefit the satellite domain. MC can increase throughput, but this entails increased power consumption at user terminal for uplink transmissions. The energy efficiency of uplink communications can be improved by designing efficient scheduling schemes, and to this end, we developed a terminal aware multi-connectivity scheduling algorithm. This proposed algorithm uses the available radio resources and propagation information to intelligently define a dynamic resource allocation pattern, that optimally routes traffic so as to maximize uplink data rate while minimizing the energy consumption at the UT. The algorithm operates with the terminal differentiating multi-layer NTN resource scheduling architecture, which has a softwarized dispatcher at the network layer that classifies and differentiates the packets based on terminal type. The performance of the proposed algorithm was compared with round robin and joint carrier schedulers in terms of uplink data rate and energy efficiency. We also provide architectural design of implementable schedulers for multi-orbital satellite networks that can operate with different classes of terminals. [less ▲]

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See detailPower Allocation for Space-Terrestrial Cooperation Systems with Statistical CSI
Chien, Trinh-Van; Lagunas, Eva UL; Hoang, Tiep M. et al

in IEEE Global Communications Conference (IEEE Globecom), Rio de Janeiro, Brazil, Dec. 2022 (2022, December)

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See detailCoexistence of eMBB and URLLC in Open Radio Access Networks: A Distributed Learning Framework
Al-Senwi, Madyan Abdullah Othman UL; Lagunas, Eva UL; Chatzinotas, Symeon UL

in IEEE Global Communications Conference (IEEE Globecom), Rio de Janeiro, Brazil, Dec. 2022 (2022, December)

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See detailTowards the Application of Neuromorphic Computing to Satellite Communications
Ortiz Gomez, Flor de Guadalupe UL; Lagunas, Eva UL; Alves Martins, Wallace UL et al

in Towards the Application of Neuromorphic Computing to Satellite Communications (2022, October)

Artificial intelligence (AI) has recently received significant attention as a key enabler for future 5G-and-beyond terrestrial wireless networks. The applications of AI to satellite communications is also ... [more ▼]

Artificial intelligence (AI) has recently received significant attention as a key enabler for future 5G-and-beyond terrestrial wireless networks. The applications of AI to satellite communications is also gaining momentum to realize a more autonomous operation with reduced requirements in terms of human intervention. The adoption of AI for satellite communications will set new requirements on computing processors, which will need to support large workloads as efficiently as possible under harsh environmental conditions. In this context, neuromorphic processing (NP) is emerging as a bio-inspired solution to address pattern recognition tasks involving multiple, possibly unstructured, temporal signals and/or requiring continual learning. The key merits of the technology are energy efficiency and capacity for on-device adaptation. In this paper, we highlight potential use cases and applications of NP to satellite communications. We also explore major technical challenges for the implementation of space-based NP focusing on the available NP chipsets. [less ▲]

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See detailNon-Coherent Massive MIMO Integration in Satellite Communication
Monzon Baeza, Victor UL; Ha, Vu Nguyen UL; Querol, Jorge UL et al

Scientific Conference (2022, October)

Massive Multiple Input-Multiple Output (mMIMO) technique has been considered an efficient standard to improve the transmission rate significantly for the following wireless communication systems, such as ... [more ▼]

Massive Multiple Input-Multiple Output (mMIMO) technique has been considered an efficient standard to improve the transmission rate significantly for the following wireless communication systems, such as 5G and beyond. However, implementing this technology has been facing a critical issue of acquiring much channel state information. Primarily, this problem becomes more criticising in the integrated satellite and terrestrial networks (3GPP-Release 15) due to the countable high transmission delay. To deal with this challenging problem, the mMIMO-empowered non-coherent technique can be a promising solution. To our best knowledge, this paper is the first work considering employing the non-coherent mMIMO in satellite communication systems. This work aims to analyse the challenges and opportunities emerging with this integration. Moreover, we identified the issues in this conjunction. The preliminary results presented in this work show that the performance measured in bit error rate (BER) and the number of antennas are not far from that required for terrestrial links. Furthermore, thanks to mMIMO in conjunction with the non-coherent approach, we can work in a low signal-to-noise ratio (SNR) regime, which is an excellent advantage for satellite links. [less ▲]

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See detailRadio Regulation Compliance of NGSO Constellations’ Interference towards GSO Ground Stations
Jalali, Mahdis UL; Ortiz Gomez, Flor de Guadalupe UL; Lagunas, Eva UL et al

in IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 12–15 September 2022, Virtual Conference (2022, September)

The commercial low earth orbiting (LEO) satellite constellations have shown unprecedented growth. Accordingly, the risk of generating harmful interference to the geostationary orbit (GSO) satellite ... [more ▼]

The commercial low earth orbiting (LEO) satellite constellations have shown unprecedented growth. Accordingly, the risk of generating harmful interference to the geostationary orbit (GSO) satellite services increases with the number of satel- lites in such mega-constellations. As the GSO arc encompasses the primary and existing satellite assets providing essential fixed and broadcasting satellite services, the interference avoidance for this area is of the utmost importance. In particular, non- geostationary orbit (NGSO) operators should comply with the regulations set up both by their national regulators and by the International Telecommunications Union (ITU) to minimize the impact of emissions on existing GSO and non-GSO systems. In this paper, we first provide an overview of the most recent radio regulations that dictate the NGSO-GSO spectral co-existence. Next, we analyze the NGSO-GSO radio frequency interference for the downlink scenario, following the so-called time-simulation methodology introduced by ITU. The probability distribution of aggregated power flux-density for NGSO co-channel interference is evaluated and assessed, adopting different degrees of exclusion angle strategy for interference avoidance. We conclude the paper by discussing the resulting implications for the continuity of operation and service provision and we provide remarks for future work [less ▲]

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See detailJoint Beam Placement and Load Balancing Optimization for Non-Geostationary Satellite Systems
Bui, Van-Phuc; Chien, Trinh-Van; Lagunas, Eva UL et al

in IEEE International Mediterranean Conference on Communications and Networking (IEEE MediCom), Athens, Greece, Sept. 2022 (2022, September)

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See detailLearning to Optimize: Balancing Two Conflict Metrics in MB-HTS Networks
Bui, Van-Phuc; Chien, Trinh-Van; Lagunas, Eva UL et al

in Advanced Satellite Multimedia Conference / Signal Processing for Space Communications Workshop (ASMS), Gratz, Viena, Sept. 2022 (2022, September)

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See detailAn Overview of Channel Models for NGSO Satellites
Monzon Baeza, Victor UL; Lagunas, Eva UL; Al-Hraishawi, Hayder UL et al

Scientific Conference (2022, September)

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See detailMatching Traffic Demand in GEO Multibeam Satellites: The Joint Use of Dynamic Beamforming and Precoding Under Practical Constraints
Chaker, Haythem UL; Chougrani, Houcine UL; Alves Martins, Wallace UL et al

in IEEE Transactions on Broadcasting (2022)

To adjust for the non-uniform spatiotemporal nature of traffic patterns, next-generation high throughput satellite (HTS) systems can benefit from recent technological advancements in the space-segment in ... [more ▼]

To adjust for the non-uniform spatiotemporal nature of traffic patterns, next-generation high throughput satellite (HTS) systems can benefit from recent technological advancements in the space-segment in order to dynamically design traffic-adaptive beam layout plans (ABLPs). In this work, we propose a framework for dynamic beamforming (DBF) optimization and adaptation in dynamic environments. Given realistic traffic patterns and a limited power budget, we propose a feasible DBF operation for a geostationary multibeam HTS network. The goal is to minimize the mismatch between the traffic demand and the offered capacity under practical constraints. These constraints are dictated by the traffic-aware design requirements, the on-board antenna system limitations, and the signaling considerations in the K-band. Noting that the ABLP is agnostic about the inherent inter-beam interference (IBI), we construct an interference simulation environment using irregularly shaped beams for a large-scale multibeam HTS system. To cope with IBI, the combination of on-board DBF and on-ground precoding is considered. For precoded and non-precoded HTS configurations, the proposed design shows better traffic-matching capabilities in comparison to a regular beam layout plan. Lastly, we provide trade-off analyses between system-level key performance indicators for different realistic non-uniform traffic patterns. [less ▲]

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See detailRobust Congestion Control for Demand-Based Optimization in Precoded Multi-Beam High Throughput Satellite Communications
Bui, Van-Phuc; Chien, Trinh-Van; Lagunas, Eva UL et al

in IEEE Transactions on Communications (2022)

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See detailEnergy Efficiency Optimization for Backscatter Enhanced NOMA Cooperative V2X Communications under Imperfect CSI
Khan, Wali Ullah UL; Jamshed, Muhammad Ali; Lagunas, Eva UL et al

in IEEE Transactions on Intelligent Transportation Systems (2022)

Automotive-Industry 5.0 will use beyond fifth-generation (B5G) technologies to provide robust, computationally intelligent, and energy-efficient data sharing among various onboard sensors, vehicles, and ... [more ▼]

Automotive-Industry 5.0 will use beyond fifth-generation (B5G) technologies to provide robust, computationally intelligent, and energy-efficient data sharing among various onboard sensors, vehicles, and other devices. Recently, ambient backscatter communications (AmBC) have gained significant interest in the research community for providing battery-free communications. AmBC can modulate useful data and reflect it towards near devices using the energy and frequency of existing RF signals. However, obtaining channel state information (CSI) for AmBC systems would be very challenging due to no pilot sequences and limited power. As one of the latest members of multiple access technology, non-orthogonal multiple access (NOMA) has emerged as a promising solution for connecting large-scale devices over the same spectral resources in B5G wireless networks. Under imperfect CSI, this paper provides a new optimization framework for energy-efficient transmission in AmBC enhanced NOMA cooperative vehicle-to-everything (V2X) networks. We simultaneously minimize the total transmit power of the V2X network by optimizing the power allocation at BS and reflection coefficient at backscatter sensors while guaranteeing the individual quality of services. The problem of total power minimization is formulated as non-convex optimization and coupled on multiple variables, making it complex and challenging. Therefore, we first decouple the original problem into two sub-problems and convert the nonlinear rate constraints into linear constraints. Then, we adopt the iterative sub-gradient method to obtain an efficient solution. For comparison, we also present a conventional NOMA cooperative V2X network without AmBC. Simulation results show the benefits of our proposed AmBC enhanced NOMA cooperative V2X network in terms of total achievable energy efficiency. [less ▲]

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See detailBackscatter-Aided NOMA V2X Communication under Channel Estimation Errors
Khan, Wali Ullah UL; Jamshed, Muhammad Ali; Mahmood, Asad UL et al

Scientific Conference (2022, June 20)

Backscatter communications (BC) has emerged as a promising technology for providing low-powered transmissions in nextG (i.e., beyond 5G) wireless networks. The fundamental idea of BC is the possibility of ... [more ▼]

Backscatter communications (BC) has emerged as a promising technology for providing low-powered transmissions in nextG (i.e., beyond 5G) wireless networks. The fundamental idea of BC is the possibility of communications among wireless devices by using the existing ambient radio frequency signals. Non-orthogonal multiple access (NOMA) has recently attracted significant attention due to its high spectral efficiency and massive connectivity. This paper proposes a new optimization framework to minimize total transmit power of BC-NOMA cooperative vehicle-to-everything networks (V2XneT) while ensuring the quality of services. More specifically, the base station (BS) transmits a superimposed signal to its associated roadside units (RSUs) in the first time slot. Then the RSUs transmit the superimposed signal to their serving vehicles in the second time slot exploiting decode and forward protocol. A backscatter device (BD) in the coverage area of RSU also receives the superimposed signal and reflect it towards vehicles by modulating own information. Thus, the objective is to simultaneously optimize the transmit power of BS and RSUs along with reflection coefficient of BDs under perfect and imperfect channel state information. The problem of energy efficiency is formulated as non-convex and coupled on multiple optimization variables which makes it very complex and hard to solve. Therefore, we first transform and decouple the original problem into two sub-problems and then employ iterative sub-gradient method to obtain an efficient solution. Simulation results demonstrate that the proposed BC-NOMA V2XneT provides high energy efficiency than the conventional NOMA V2XneT without BC. [less ▲]

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See detailArea-Power Analysis of FFT Based Digital Beamforming for GEO, MEO, and LEO Scenarios
Palisetty, Rakesh UL; Eappen, Geoffrey UL; Gonzalez Rios, Jorge Luis UL et al

Scientific Conference (2022, June 19)

Satellite communication systems can provide seamless wireless coverage directly or through complementary ground terrestrial components and are projected to be incorporated into future wireless networks ... [more ▼]

Satellite communication systems can provide seamless wireless coverage directly or through complementary ground terrestrial components and are projected to be incorporated into future wireless networks, particularly 5G and beyond networks. Increased capacity and flexibility in telecom satellite payloads based on classic radio frequency technology have traditionally translated into increased power consumption and dissipation. Much of the analog hardware in a satellite communications payload can be replaced with highly integrated digital components that are often smaller, lighter, and less expensive, as well as software reprogrammable. Digital beamforming of thousands of beams simultaneously is not practical due to the limited power available onboard satellite processors. Reduced digital beamforming power consumption would enable the deployment of a full digital payload, resulting in comprehensive user applications. Beamforming can be implemented using matrix multiplication, hybrid methodology, or a discrete Fourier transform (DFT). Implementing DFT via fast Fourier transform (FFT) reduces the power consumption, process time, hardware requirements, and chip area. Therefore, in this paper, area-power efficient FFT architectures for digital beamforming are analyzed. The area in terms of look up tables (LUTs) is estimated and compared among conventional FFT, fully unrolled FFT, and a 4-bit quantized twiddle factor (TF) FFT. Further, for the typical satellite scenarios, area, and power estimation are reported. [less ▲]

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See detailWhen RIS Meets GEO Satellite Communications: A New Sustainable Optimization Framework in 6G
Khan, Wali Ullah UL; Lagunas, Eva UL; Mahmood, Asad UL et al

Scientific Conference (2022, June 19)

Reflecting intelligent surfaces (RIS) is a low-cost and energy-efficient solution to achieve high spectral efficiency in sixth-generation (6G) networks. The basic idea of RIS is to smartly reconfigure the ... [more ▼]

Reflecting intelligent surfaces (RIS) is a low-cost and energy-efficient solution to achieve high spectral efficiency in sixth-generation (6G) networks. The basic idea of RIS is to smartly reconfigure the signal propagation by using passive reflecting elements. On the other side, the demand of high throughput geostationary (GEO) satellite communications (SatCom) is rapidly growing to deliver broadband services in inaccessible/insufficient covered areas of terrestrial networks. This paper proposes a GEO SatCom network, where a satellite transmits the signal to a ground mobile terminal using multicarrier communications. To enhance the effective gain, the signal delivery from satellite to the ground mobile terminal is also assisted by RIS which smartly shift the phase of the signal towards ground terminal. We consider that RIS is mounted on a high building and equipped with multiple re-configurable passive elements along with smart controller. We jointly optimize the power allocation and phase shift design to maximize the channel capacity of the system. The joint optimization problem is formulated as nonconvex due to coupled variables which is hard to solve through traditional convex optimization methods. Thus, we propose a new optimal algorithm which is based on Mesh Adaptive Direct Search to obtain an efficient solution. Simulation results unveil the benefits of RIS-assisted SatCom in terms of system channel capacity. [less ▲]

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