References of "Chatzinotas, Symeon 50001234"
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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 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 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 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 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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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 detailUnsupervised Learning for User Scheduling in Multibeam Precoded GEO Satellite Systems
Ortiz Gomez, Flor de Guadalupe UL; Lagunas, Eva UL; Chatzinotas, Symeon UL

Scientific Conference (2022, June 09)

Future generation SatCom multibeam architectures will extensively exploit full-frequency reuse schemes together with interference management techniques, such as precoding, to dramatically increase ... [more ▼]

Future generation SatCom multibeam architectures will extensively exploit full-frequency reuse schemes together with interference management techniques, such as precoding, to dramatically increase spectral efficiency performance. Precoding is very sensitive to user scheduling, suggesting a joint precoding and user scheduling design to achieve optimal performance. However, the joint design requires solving a highly complex optimization problem which is unreasonable for practical systems. Even for suboptimal disjoint scheduling designs, the complexity is still significant. To achieve a good compromise between performance and complexity, we investigate the applicability of Machine Learning (ML) for the aforementioned problem. We propose three clustering algorithms based on Unsupervised Learning (UL) that facilitate the user scheduling decisions while maximizing the system performance in terms of throughput. Numerical simulations compare the three proposed algorithms (K-means, Hierarchical clustering, and Self-Organization) with the conventional geographic scheduling and identify the main trade-offs. [less ▲]

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See detailJoint Optimization of Beam-Hopping Design and NOMA-Assisted Transmission for Flexible Satellite Systems
Wang, Anyue UL; Lei, Lei; Lagunas, Eva UL et al

in IEEE Transactions on Wireless Communications (2022)

Next-generation satellite systems require more flexibility in resource management such that available radio resources can be dynamically allocated to meet time-varying and non-uniform traffic demands ... [more ▼]

Next-generation satellite systems require more flexibility in resource management such that available radio resources can be dynamically allocated to meet time-varying and non-uniform traffic demands. Considering potential benefits of beam hopping (BH) and non-orthogonal multiple access (NOMA), we exploit the time-domain flexibility in multi-beam satellite systems by optimizing BH design, and enhance the power-domain flexibility via NOMA. In this paper, we investigate the synergy and mutual influence of beam hopping and NOMA. We jointly optimize power allocation, beam scheduling, and terminal-timeslot assignment to minimize the gap between requested traffic demand and offered capacity. In the solution development, we formally prove the NP-hardness of the optimization problem. Next, we develop a bounding scheme to tightly gauge the global optimum and propose a suboptimal algorithm to enable efficient resource assignment. Numerical results demonstrate the benefits of combining NOMA and BH, and validate the superiority of the proposed BH-NOMA schemes over benchmarks. [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 detailMaximizing the Number of Served Users in a Smart City using Reconfigurable Intelligent Surfaces
Zivuku, Progress UL; Kisseleff, Steven UL; Nguyen, van Dinh UL et al

in Proceedings of IEEE Wireless Communications and Networking Conference (WCNC) (2022, April 10)

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See detailD-ViNE: Dynamic Virtual Network Embedding in Non-Terrestrial Networks
Maity, Ilora UL; Vu, Thang Xuan UL; Chatzinotas, Symeon UL et al

Scientific Conference (2022, April 10)

In this paper, we address the virtual network embedding (VNE) problem in non-terrestrial networks (NTNs) enabling dynamic changes in the virtual network function (VNF) deployment to maximize the service ... [more ▼]

In this paper, we address the virtual network embedding (VNE) problem in non-terrestrial networks (NTNs) enabling dynamic changes in the virtual network function (VNF) deployment to maximize the service acceptance rate and service revenue. NTNs such as satellite networks involve highly dynamic topology and limited resources in terms of rate and power. VNE in NTNs is a challenge because a static strategy under-performs when new service requests arrive or the network topology changes unexpectedly due to failures or other events. Existing solutions do not consider the power constraint of satellites and rate limitation of inter-satellite links (ISLs) which are essential parameters for dynamic adjustment of existing VNE strategy in NTNs. In this work, we propose a dynamic VNE algorithm that selects a suitable VNE strategy for new and existing services considering the time-varying network topology. The proposed scheme, D-ViNE, increases the service acceptance ratio by 8.51% compared to the benchmark scheme TS-MAPSCH. [less ▲]

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See detailMachine Learning for Radio Resource Management in Multibeam GEO Satellite Systems
Ortiz Gomez, Flor de Guadalupe UL; Lei, Lei UL; Lagunas, Eva UL et al

in Electronics (2022), 11(7), 992

Satellite communications (SatComs) systems are facing a massive increase in traffic demand. However, this increase is not uniform across the service area due to the uneven distribution of users and ... [more ▼]

Satellite communications (SatComs) systems are facing a massive increase in traffic demand. However, this increase is not uniform across the service area due to the uneven distribution of users and changes in traffic demand diurnal. This problem is addressed by using flexible payload architectures, which allow payload resources to be flexibly allocated to meet the traffic demand of each beam. While optimization-based radio resource management (RRM) has shown significant performance gains, its intense computational complexity limits its practical implementation in real systems. In this paper, we discuss the architecture, implementation and applications of Machine Learning (ML) for resource management in multibeam GEO satellite systems. We mainly focus on two systems, one with power, bandwidth, and/or beamwidth flexibility, and the second with time flexibility, i.e., beam hopping. We analyze and compare different ML techniques that have been proposed for these architectures, emphasizing the use of Supervised Learning (SL) and Reinforcement Learning (RL). To this end, we define whether training should be conducted online or offline based on the characteristics and requirements of each proposed ML technique and discuss the most appropriate system architecture and the advantages and disadvantages of each approach. [less ▲]

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See detailEnergy Harvesting from Jamming Attacks in Multi-User Massive MIMO Networks
Al-Hraishawi, Hayder UL; Abdullah, Osamah; Chatzinotas, Symeon UL et al

in IEEE Transactions on Green Communications and Networking (2022)

5G communication systems enable new functions and major performance improvements but at the cost of tougher energy requirements on mobile devices. One of the effective ways to address this issue along ... [more ▼]

5G communication systems enable new functions and major performance improvements but at the cost of tougher energy requirements on mobile devices. One of the effective ways to address this issue along with alleviating the environmental effects associated with the inevitable large increase in energy usage is the energy-neutral systems, which operate with the energy harvested from radio-frequency (RF) transmissions. In this direction, this paper investigates the notion of harvesting the ambient RF signals from an unusual source. Specifically, the performance of an RF energy harvesting scheme for multi-user massive multiple-input multiple-output (MIMO) is investigated in the presence of multiple active jammers. The key idea is to exploit the jamming transmissions as an energy source to be harvested at the legitimate users. To this end, the achievable uplink sum rate expressions are derived in closed-form for two different antenna configurations. Two optimal time-switching schemes are also proposed based on maximum sum rate and user-fairness criteria. Besides, the essential trade-off between the harvested energy and achievable sum rate are quantified in closed-form. Our analysis reveals that the massive MIMO systems can exploit the surrounding RF signals of the jamming attacks for boosting the amount of harvested energy at the served users. Finally, numerical results illustrate the effectiveness of the derived closed-form expressions through simulations. [less ▲]

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See detailPerformance Evaluation of Forward Link Packet Scheduling in Satellite Communication Systems with Carrier Aggregation
Al-Hraishawi, Hayder UL; Lagunas, Eva UL; Kumar, Sumit UL et al

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 ▲]

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See detailUplink Capacity Optimization for High Throughput Satellites using SDN and Multi-Orbital Dual Connectivity
Dazhi, Michael UL; Al-Hraishawi, Hayder UL; Mysore Rama Rao, Bhavani Shankar UL et al

Scientific Conference (2022)

Dual Connectivity is a key approach to achieving optimization of throughput and latency in heterogeneous networks. Originally a technique introduced by the 3rd Generation Partnership Project (3GPP) for ... [more ▼]

Dual Connectivity is a key approach to achieving optimization of throughput and latency in heterogeneous networks. Originally a technique introduced by the 3rd Generation Partnership Project (3GPP) for terrestrial communications, it is not been widely explored in satellite systems. In this paper, Dual Connectivity is implemented in a multi-orbital satellite network, where a network model is developed by employing the diversity gains from Dual Connectivity and Carrier Aggregation for the enhancement of satellite uplink capacity. An introduction of software defined network controller is performed at the network layer coupled with a carefully designed hybrid resource allocation algorithm which is implemented strategically. The algorithm performs optimum dynamic flow control and traffic steering by considering the availability of resources and the channel propagation information of the orbital links to arrive at a resource allocation pattern suitable in enhancing uplink system performance. Simulation results are shown to evaluate the achievable gains in throughput and latency; in addition we provide useful insight in the design of multi-orbital satellite networks with implementable scheduler design. [less ▲]

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