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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

in IEEE Global Communications Conference (Globecom), Rio de Janeiro 4 - 8 December 2022 (in press)

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 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 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 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 detailAdaptive Beam Pattern Selection and Resource Allocation for NOMA-Based LEO Satellite Systems
Wang, Anyue UL; Lei, Lei; Hu, Xin et al

Scientific Conference (2022, December 04)

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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 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 detailOn the Performance of Cache-Free/Cache-Aided STBC-NOMA in Cognitive Hybrid Satellite-Terrestrial Networks
Singh, Vibhum UL; Solanki, Sourabh UL; Eappen, Geoffrey UL et al

in IEEE Wireless Communications Letters (2022), (Early Access), 1-1

Future wireless networks pose several challenges such as high spectral efficiency, wide coverage massive connectivity, low receiver complexity, etc. To this end, this letter investigates an overlay based ... [more ▼]

Future wireless networks pose several challenges such as high spectral efficiency, wide coverage massive connectivity, low receiver complexity, etc. To this end, this letter investigates an overlay based cognitive hybrid satellite-terrestrial network (CHSTN) combining non-orthogonal multiple access (NOMA) and conventional Alamouti space-time block coding (STBC) techniques. Herein, a decode-and-forward based secondary terrestrial network cooperates with a primary satellite network for dynamic spectrum access. Further, for reliable content delivery and low latency requirements, wireless caching is employed, whereby the secondary network can store the most popular contents of the primary network. Considering the relevant heterogeneous fading channel models and the NOMA-based imperfect successive interference cancellation, we examine the performance of CHSTN for the cache-free (CF) STBC-NOMA and the cache-aided (CA) STBC-NOMA schemes. We assess the outage probability expressions for primary and secondary networks and further, highlight the corresponding achievable diversity orders. Indicatively, the proposed CF/CA STBC-NOMA schemes for CHSTN perform significantly better than the benchmark standalone NOMA and OMA schemes. [less ▲]

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See detailTask-Oriented Data Compression for Multi-Agent Communications Over Bit-Budgeted Channels
Mostaani, Arsham UL; Vu, Thang Xuan UL; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2022)

Various applications for inter-machine communications are on the rise. Whether it is for autonomous driving vehicles or the internet of everything, machines are more connected than ever to improve their ... [more ▼]

Various applications for inter-machine communications are on the rise. Whether it is for autonomous driving vehicles or the internet of everything, machines are more connected than ever to improve their performance in fulfilling a given task. While in traditional communications the goal has often been to reconstruct the underlying message, under the emerging task-oriented paradigm, the goal of communication is to enable the receiving end to make more informed decisions or more precise estimates/computations. Motivated by these recent developments, in this paper, we perform an indirect design of the communications in a multi-agent system (MAS) in which agents cooperate to maximize the averaged sum of discounted one-stage rewards of a collaborative task. Due to the bit-budgeted communications between the agents, each agent should efficiently represent its local observation and communicate an abstracted version of the observations to improve the collaborative task performance. We first show that this problem can be approximated as a form of data-quantization problem which we call task-oriented data compression (TODC). We then introduce the state-aggregation for information compression algorithm (SAIC) to solve the formulated TODC problem. It is shown that SAIC is able to achieve near-optimal performance in terms of the achieved sum of discounted rewards. The proposed algorithm is applied to a geometric consensus problem and its performance is compared with several benchmarks. Numerical experiments confirm the promise of this indirect design approach for task-oriented multi-agent communications. [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 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 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 detailSatellite Beam Densification for High-Demand Areas
Jubba Honnaiah, Puneeth UL; Lagunas, Eva UL; Chatzinotas, Symeon UL et al

in 2022 11th Advanced Satellite Multimedia Systems Conference and the 17th Signal Processing for Space Communications Workshop (ASMS/SPSC) (2022, September)

Conventional multi-beam pattern design in Geostationary (GEO) satellite communication systems consists of a regular grid of non-reconfigurable beams, where the beams overlap is typically assumed at the ... [more ▼]

Conventional multi-beam pattern design in Geostationary (GEO) satellite communication systems consists of a regular grid of non-reconfigurable beams, where the beams overlap is typically assumed at the point where the beam edge reaches a 3-dB loss in the antenna pattern (with respect to the beam center). For certain high demand areas, this 3dB loss has a significant impact. To overcome this issue, in this paper we evaluate the potential gain of beam densification, i.e. considering an increased number of beams (keeping the same beam size and shape) to cover hot-spot areas, with the aim to push the beam overlap and increase the beam gain. In particular, we compare two beam patterns (kindly provided by ESA): One with regular beam grid, and one with densification in a particular hot-spot area. We provide a comparison in terms of per-beam average SINR and capacity, as well as an overall system analysis considering the whole densified region. [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 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 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 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 detailInbound Carrier Plan Optimization for Adaptive VSAT Networks
Lacoste, Clément UL; Alves Martins, Wallace UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Aerospace and Electronic Systems (2022)

The past decades witnessed the application of adaptive modulation and coding (ACM) in satellite links. However, ACM technologies come at the cost of higher complexity when designing the network’s carrier ... [more ▼]

The past decades witnessed the application of adaptive modulation and coding (ACM) in satellite links. However, ACM technologies come at the cost of higher complexity when designing the network’s carrier plan and user terminals. Accounting for those issues is even more important when the satellite link uses frequencies in Ka band and above, where the attenuation caused by tropospheric phenomena is a major concern. In this paper, we propose a solution for the inbound, i.e. return link, carrier plan sizing of very small aperture terminal (VSAT) networks. As tropospheric attenuation is a key factor, we present a mathematical problem formulation based on spatially correlated attenuation time series generators. Our proposed sizing scheme is formulated as a mixed integer linear programming (MILP) optimization problem. The numerical results for a test scenario in Europe show a 10 to 50% bandwidth improvement over traditional sizing methods for outage probabilities lower than 1%. [less ▲]

Detailed reference viewed: 103 (6 UL)