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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 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 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 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 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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See detailSymbiotic Radio based Spectrum Sharing in Cooperative UAV-IRS Wireless Networks
Solanki, Sourabh UL; Gautam, Sumit; Singh, Vibhum UL et al

Scientific Conference (2022)

Ambient backscatter communication (AmBC) technology can potentially offer spectral- and energy-efficient solutions for future wireless systems. This paper proposes a novel design to facilitate the ... [more ▼]

Ambient backscatter communication (AmBC) technology can potentially offer spectral- and energy-efficient solutions for future wireless systems. This paper proposes a novel design to facilitate the spectrum sharing between a secondary system and a primary system based on the AmBC technique in intelligent reflective surface (IRS)-assisted unmanned aerial vehicle (UAV) networks. In particular, an IRS-aided UAV cooperatively relays the transmission from a terrestrial primary source node to a user equipment on the ground. On the other hand, leveraging on the AmBC technology, a terrestrial secondary node transmits its information to a terrestrial secondary receiver by modulating and backscattering the ambient relayed radio frequency (RF) signals from the UAV-IRS. The performance of such a system setup is analyzed by deriving the expressions of outage probability and ergodic spectral efficiency. Finally, we present the numerical results to provide useful insights into the system design and also validate the derived theoretical results using Monte Carlo simulations. [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 detailDual-DNN Assisted Optimization for Efficient Resource Scheduling in NOMA-Enabled Satellite Systems
Wang, Anyue UL; Lei, Lei UL; Lagunas, Eva UL et al

Scientific Conference (2021, December 08)

In this paper, we apply non-orthogonal multiple access (NOMA) in satellite systems to assist data transmission for services with latency constraints. We investigate a problem to minimize the transmission ... [more ▼]

In this paper, we apply non-orthogonal multiple access (NOMA) in satellite systems to assist data transmission for services with latency constraints. We investigate a problem to minimize the transmission time by jointly optimizing power allocation and terminal-timeslot assignment for accomplishing a transmission task in NOMA-enabled satellite systems. The problem appears non-linear/non-convex with integer variables and can be equivalently reformulated in the format of mixed-integer convex programming (MICP). Conventional iterative methods may apply but at the expenses of high computational complexity in approaching the optimum or near-optimum. We propose a combined learning and optimization scheme to tackle the problem, where the primal MICP is decomposed into two learning-suited classification tasks and a power allocation problem. In the proposed scheme, the first learning task is to predict the integer variables while the second task is to guarantee the feasibility of the solutions. Numerical results show that the proposed algorithm outperforms benchmarks in terms of average computational time, transmission time performance, and feasibility guarantee. [less ▲]

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See detailLearning-Based Multiplexing of Grant-Based and Grant-Free Heterogeneous Services with Short Packets
Tran, Duc Dung UL; Sharma, Shree Krishna; Chatzinotas, Symeon UL et al

in Proceedings of 2021 IEEE Global Communications Conference (GLOBECOM) (2021, December)

In this paper, we investigate the multiplexing of grant-based (GB) and grant-free (GF) device transmissions in an uplink heterogeneous network (HetNet), namely GB-GF HetNet, where the devices transmit ... [more ▼]

In this paper, we investigate the multiplexing of grant-based (GB) and grant-free (GF) device transmissions in an uplink heterogeneous network (HetNet), namely GB-GF HetNet, where the devices transmit their information using low-rate short data packets. Specifically, GB devices are granted unique time-slots for their transmissions. In contrast, GF devices can randomly select time-slots to transmit their messages utilizing the GF non-orthogonal multiple access (NOMA), which has emerged as a promising enabler for massive access and reducing access latency. However, random access (RA) in the GF NOMA can cause collisions and severe interference, leading to system performance degradation. To overcome this issue, we propose a multiple access (MA) protocol based on reinforcement learning for effective RA slots allocation. The proposed learning method aims to guarantee that the GF devices do not cause any collisions to the GB devices and the number of GF devices choosing the same time-slot does not exceed a predetermined threshold to reduce the interference. In addition, based on the results of the RA slots allocation using the proposed method, we derive the approximate closed-form expressions of the average decoding error probability (ADEP) for all devices to characterize the system performance. Our results presented in terms of access efficiency (AE), collision probability (CP), and overall ADEP (OADEP), show that our proposed method can ensure a smooth operation of the GB and GF devices within the same network while significantly minimizing the collision and interference among the device transmissions in the GB-GF HetNet. [less ▲]

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See detailLearning-Assisted User Clustering in Cell-Free Massive MIMO-NOMA Networks
Le, Quang Nhat; Nguyen, van Dinh UL; Dobre, Octavia A. et al

in IEEE Transactions on Vehicular Technology (2021), 70(12), 12872-12887

The superior spectral efficiency (SE) and user fairness feature of non-orthogonal multiple access (NOMA) systems are achieved by exploiting user clustering (UC) more efficiently. However, a random UC ... [more ▼]

The superior spectral efficiency (SE) and user fairness feature of non-orthogonal multiple access (NOMA) systems are achieved by exploiting user clustering (UC) more efficiently. However, a random UC certainly results in a suboptimal solution while an exhaustive search method comes at the cost of high complexity, especially for systems of medium-to-large size. To address this problem, we develop two efficient unsupervised machine learning based UC algorithms, namely k-means++ and improved k-means++, to effectively cluster users into disjoint clusters in cell-free massive multiple-input multiple-output (CFmMIMO) system. Adopting full-pilot zero-forcing at access points (APs) to comprehensively assess the system performance, we formulate the sum SE optimization problem taking into account power constraints at APs, necessary conditions for implementing successive interference cancellation, and required SE constraints at user equipments. The formulated optimization problem is highly non-convex, and thus, it is difficult to obtain the global optimal solution. Therefore, we develop a simple yet efficient iterative algorithm for its solution. In addition, the performance of collocated massive MIMO-NOMA (COmMIMO-NOMA) system is also characterized. Numerical results are provided to show the superior performance of the proposed UC algorithms compared to baseline schemes. The effectiveness of applying NOMA in CFmMIMO and COmMIMO systems is also validated. [less ▲]

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See detailAn overview of generic tools for information-theoretic secrecy performance analysis over wiretap fading channels
Kong, Long UL; Ai, Yun; Lei, Lei UL et al

in EURASIP Journal on Wireless Communications and Networking volume (2021), (1), 194

Physical layer security (PLS) has been proposed to afford an extra layer of security on top of the conventional cryptographic techniques. Unlike the conventional complexity-based cryptographic techniques ... [more ▼]

Physical layer security (PLS) has been proposed to afford an extra layer of security on top of the conventional cryptographic techniques. Unlike the conventional complexity-based cryptographic techniques at the upper layers, physical layer security exploits the characteristics of wireless channels, e.g., fading, noise, interference, etc., to enhance wireless security. It is proved that secure transmission can benefit from fading channels. Accordingly, numerous researchers have explored what fading can offer for physical layer security, especially the investigation of physical layer security over wiretap fading channels. Therefore, this paper aims at reviewing the existing and ongoing research works on this topic. More specifically, we present a classification of research works in terms of the four categories of fading models: (i) small-scale, (ii) large-scale, (iii) composite, and (iv) cascaded. To elaborate these fading models with a generic and flexible tool, three promising candidates, including the mixture gamma (MG), mixture of Gaussian (MoG), and Fox’s H-function distributions, are comprehensively examined and compared. Their advantages and limitations are further demonstrated via security performance metrics, which are designed as vivid indicators to measure how perfect secrecy is ensured. Two clusters of secrecy metrics, namely (i) secrecy outage probability (SOP), and the lower bound of SOP; and (ii) the probability of nonzero secrecy capacity (PNZ), the intercept probability, average secrecy capacity (ASC), and ergodic secrecy capacity, are displayed and, respectively, deployed in passive and active eavesdropping scenarios. Apart from those, revisiting the secrecy enhancement techniques based on Wyner’s wiretap model, the on-off transmission scheme, jamming approach, antenna selection, and security region are discussed. [less ▲]

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See detailLearning-Assisted User Clustering in Cell-Free Massive MIMO-NOMA Networks
Le; Nguyen, van Dinh UL; Dobre, Octavia A. et al

in IEEE Transactions on Vehicular Technology (2021), 70(12), 12872-12887

The superior spectral efficiency (SE) and user fairness feature of non-orthogonal multiple access (NOMA) systems are achieved by exploiting user clustering (UC) more efficiently. However, a random UC ... [more ▼]

The superior spectral efficiency (SE) and user fairness feature of non-orthogonal multiple access (NOMA) systems are achieved by exploiting user clustering (UC) more efficiently. However, a random UC certainly results in a suboptimal solution while an exhaustive search method comes at the cost of high complexity, especially for systems of medium-to-large size. To address this problem, we develop two efficient unsupervised machine learning based UC algorithms, namely k-means++ and improved k-means++, to effectively cluster users into disjoint clusters in cell-free massive multiple-input multiple-output (CFmMIMO) system. Adopting full-pilot zero-forcing at access points (APs) to comprehensively assess the system performance, we formulate the sum SE optimization problem taking into account power constraints at APs, necessary conditions for implementing successive interference cancellation, and required SE constraints at user equipments. The formulated optimization problem is highly non-convex, and thus, it is difficult to obtain the global optimal solution. Therefore, we develop a simple yet efficient iterative algorithm for its solution. In addition, the performance of collocated massive MIMO-NOMA (COmMIMO-NOMA) system is also characterized. Numerical results are provided to show the superior performance of the proposed UC algorithms compared to baseline schemes. The effectiveness of applying NOMA in CFmMIMO and COmMIMO systems is also validated. [less ▲]

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See detailProceedings of the 12th European CubeSatSymposium
Thoemel, Jan UL; Querol, Jorge UL; Bokal, Zhanna UL et al

in Proceedings of the 12th European CubeSatSymposium (2021, November 15)

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See detailDownlink Transmit Design in Massive MIMO LEO Satellite Communications
Li, Ke-Xin; You, Li; Want, Jiaheng et al

in IEEE Transactions on Communications (2021)

Low earth orbit (LEO) satellite communication systems have attracted extensive attention due to their smaller pathloss, shorter round-trip delay and lower launch cost compared with geostationary ... [more ▼]

Low earth orbit (LEO) satellite communication systems have attracted extensive attention due to their smaller pathloss, shorter round-trip delay and lower launch cost compared with geostationary counterparts. In this paper, the downlink transmit design for massive multiple-input multiple-output (MIMO) LEO satellite communications is investigated. First, we establish the massive MIMO LEO satellite channel model where the satellite and user terminals (UTs) are both equipped with the uniform planar arrays. Then, the rank of transmit covariance matrix of each UT is shown to be no larger than one to maximize ergodic sum rate, which reveals the optimality of single-stream precoding for each UT. The minorization-maximization algorithm is used to compute the precoding vectors. To reduce the computation complexity, an upper bound of ergodic sum rate is resorted to produce a simplified transmit design, where the rank of optimal transmit covariance matrix of each UT is also shown to not exceed one. To tackle the simplified precoder design, we derive the structure of precoding vectors, and formulate a Lagrange multiplier optimization (LMO) problem building on the structure. Then, a low-complexity algorithm is devised to solve the LMO, which takes much less computation effort. Simulation results verify the performance of proposed approaches. [less ▲]

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See detailSDN for Gateway Diversity Implementation in Satellite Networks
Minardi, Mario UL; Politis, Christos; Zimmer, Frank et al

in International Symposium on Networks, Computers and Communications (ISNCC), Dubai 31 Oct.-2 Nov. 2021 (2021, November)

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See detailHybrid Beamforming for Terahertz Joint Ultra-Massive MIMO Radar-Communications
Elbir, Ahmet M.; Mishra, Kumar Vjiay; Chatzinotas, Symeon UL

in IEEE Journal of Selected Topics in Signal Processing (2021), 15(6), 1468-1483

In this paper, we investigate the hybrid beamforming problem in joint radar-communications at terahertz (THz) bands. In order to address the extremely high attenuation at THz, ultra-massive multiple-input ... [more ▼]

In this paper, we investigate the hybrid beamforming problem in joint radar-communications at terahertz (THz) bands. In order to address the extremely high attenuation at THz, ultra-massive multiple-input multiple-output (UM-MIMO) antenna systems have been proposed for THz communications to compensate propagation losses. Further, we propose a new group-of-subarrays (GoSA) UM-MIMO structure to reduce the hardware cost. We formulate the GoSA beamformer design as an optimization problem to provide a trade-off between the unconstrained communications beamformers and the desired radar beamformers. Numerical experiments demonstrate that the proposed approach outperforms the conventional approaches in terms of spectral efficiency and hardware costs. [less ▲]

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See detailThroughput Enhancement in FD- and SWIPT-enabled IoT Networks over Non-Identical Rayleigh Fading Channel
Nguyen, Nhat Tan; Tran Dinh, Hieu UL; Chatzinotas, Symeon UL et al

in IEEE Internet of Things Journal (2021)

Simultaneous wireless information and power transfer (SWIPT) and full-duplex (FD) communications have emerged as prominent technologies in overcoming the limited energy resources in Internet-of-Things ... [more ▼]

Simultaneous wireless information and power transfer (SWIPT) and full-duplex (FD) communications have emerged as prominent technologies in overcoming the limited energy resources in Internet-of-Things (IoT) networks and improving their spectral efficiency (SE). The article investigates the outage and throughput performance for a decode-and-forward (DF) relay SWIPT system, which consists of one source, multiple relays, and one destination. The relay nodes in this system can harvest energy from the source’s signal and operate in FD mode. A suboptimal, low-complexity, yet efficient relay selection scheme is also proposed. Specifically, a single relay is selected to convey information from a source to a destination so that it achieves the best channel from the source to the relays. An analysis of outage probability (OP) and throughput performed on two relaying strategies, termed static power splitting-based relaying (SPSR) and optimal dynamic power splitting-based relaying (ODPSR), is presented. Notably, we considered independent and non-identically distributed (i.n.i.d.) Rayleigh fading channels, which pose new challenges in obtaining analytical expressions. In this context, we derived exact closed-form expressions of the OP and throughput of both SPSR and ODPSR schemes. We also obtained the optimal power splitting ratio of ODPSR for maximizing the achievable capacity at the destination. Finally, we present extensive numerical and simulation results to confirm our analytical findings. Both simulation and analytical results show the superiority of ODPSR over SPSR. [less ▲]

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See detailNB-IoT Random Access for Non-Terrestrial Networks: Preamble Detection and Uplink Synchronization
Chougrani, Houcine UL; Kisseleff, Steven UL; Alves Martins, Wallace UL et al

in IEEE Internet of Things Journal (2021)

The satellite component is recognized as a promising solution to complement and extend the coverage of future Internet of things (IoT) terrestrial networks (TNs). In this context, a study item to ... [more ▼]

The satellite component is recognized as a promising solution to complement and extend the coverage of future Internet of things (IoT) terrestrial networks (TNs). In this context, a study item to integrate satellites into narrowband-IoT (NBIoT) systems has been approved within the 3rd Generation Partnership Project (3GPP) standardization body. However, as NBIoT systems were initially conceived for TNs, their basic design principles and operation might require some key modifications when incorporating the satellite component. These changes in NB-IoT systems, therefore, need to be carefully implemented in order to guarantee a seamless integration of both TN and non-terrestrial network (NTN) for a global coverage. This paper addresses this adaptation for the random access (RA) step in NBIoT systems, which is in fact the most challenging aspect in the NTN context, for it deals with multi-user time-frequency synchronization and timing advance for data scheduling. In particular, we propose an RA technique which is robust to typical satellite channel impairments, including long delays, significant Doppler effects, and wide beams, without requiring any modification to the current NB-IoT RA waveform. Performance evaluations demonstrate the proposal’s capability of addressing different NTN configurations recently defined by 3GPP for the 5G new radio system. [less ▲]

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See detailExperimental Comparison of RF Waveform Designs for Wireless Power Transmission
Gautam, Sumit; Kumar, Sumit UL; Chatzinotas, Symeon UL et al

in Experimental Comparison of RF Waveform Designs for Wireless Power Transmission (2021, October)

The possibility to harvest energy from ambient radio-frequency (RF) sources has intrigued humankind for the past several decades. In this context, there has been a tremendously growing research interest ... [more ▼]

The possibility to harvest energy from ambient radio-frequency (RF) sources has intrigued humankind for the past several decades. In this context, there has been a tremendously growing research interest in the field of wireless power transfer (WPT) using the RF range of the electromagnetic (EM) spectrum. In this paper, we experimentally investigate the aspect of real-time energy harvesting (EH) via different types of waveform designs such as orthogonal frequency division multiplexing (OFDM), square, triangular, sinusoidal, and sawtooth. We make use of a Software Defined Radio (SDR) and a Powercast P21XXCSR-EVB EH module to carry out the experiments on the practical device to assess performance. Specifically, we are interested in obtaining insights based on the comparison between the aforementioned waveform designs from the perspectives of the separation distance between the USRP and P21XXCSR-EVB EH module, and power emission via USRP. In this vein, some additional experiments are subsequently performed after a suitable candidate waveform has been reported. The demonstration of the EH is provided in terms of the abovementioned investigation metrics while seeking the best waveform to support WPT. [less ▲]

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