arXiv subjects

Bjorn Ottersten

Publications and source records attributed to Bjorn Ottersten.

At least 37 records · Page 2Linked to original sources

arXiv2022

When RIS Meets GEO Satellite Communications: A New Sustainable Optimization Framework in 6G

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 $ε-$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.

eess.SP↗

arXiv2022

Impact of Phase-Noise and Spatial Correlation on Double-RIS-Assisted Multiuser MISO Networks

We study the performance of a phase-noise impaired double reconfigurable intelligent surface (RIS)-aided multiuser (MU) multiple-input single-output (MISO) system under spatial correlation at both RISs and base-station (BS). The downlink achievable rate is derived in closed-form under maximum ratio transmission (MRT) precoding. In addition, we obtain the optimal phase-shift design at both RISs in closed-form for the considered channel and phase-noise models. Numerical results validate the analytical expressions, and highlight the effects of different system parameters on the achievable rate. Our analysis shows that phase-noise can severely degrade the performance when users do not have direct links to both RISs, and can only be served via the double-reflection link. Also, we show that high spatial correlation at RISs is essential for high achievable rates.

cs.IT↗

arXiv2022

Energy Efficiency Optimization for Backscatter Enhanced NOMA Cooperative V2X Communications under Imperfect CSI

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.

eess.SP↗

arXiv2022

FedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud Systems

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 fog-cloud 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.

cs.LG↗

arXiv2022

Backscatter-Aided NOMA V2X Communication under Channel Estimation Errors

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.

eess.SP↗

arXiv2021

Joint Optimization of Beam-Hopping Design and NOMA-Assisted Transmission for Flexible Satellite Systems

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.

cs.IT↗

arXiv2021

Successive Decode-and-Forward Relaying with Reconfigurable Intelligent Surfaces

The key advantage of successive relaying (SR) networks is their ability to mimic the full-duplex (FD) operation with half-duplex (HD) relays. However, the main challenge that comes with such schemes is the associated inter-relay interference (IRI). In this work, we propose a reconfigurable intelligent surface (RIS)-enhanced SR network, where one RIS is deployed near each of the two relay nodes to provide spatial suppression of IRI, and to maximize the gain of desired signals. The resultant max-min optimization problem with joint phase-shift design for both RISs is first tackled via the semidefinite programming (SDP) approach. Then, a lower-complexity solution suitable for real-time implementation is proposed based on particle swarm optimization (PSO). Numerical results demonstrate that even relatively small RISs can provide significant gains in achievable rates of SR networks, and the proposed PSO scheme can achieve a near optimal performance.

cs.IT↗

arXiv2021

UAV Relay-Assisted Emergency Communications in IoT Networks: Resource Allocation and Trajectory Optimization

Unmanned aerial vehicle (UAV) communication has emerged as a prominent technology for emergency communications (e.g., natural disaster) in the Internet of Things (IoT) networks to enhance the ability of disaster prediction, damage assessment, and rescue operations promptly. A UAV can be deployed as a flying base station (BS) to collect data from time-constrained IoT devices and then transfer it to a ground gateway (GW). In general, the latency constraint at IoT devices and UAV's limited storage capacity highly hinder practical applications of UAV-assisted IoT networks. In this paper, {full-duplex (FD) radio} is adopted at the UAV to overcome these challenges. In addition, half-duplex (HD) scheme for UAV-based relaying is also considered to provide a comparative study between two modes (viz., FD and HD). {Herein, a device is considered to be successfully served iff its data is collected by the UAV and conveyed to GW timely during flight time}. In this context, we aim to maximize the number of served IoT devices by jointly optimizing bandwidth, power allocation, and the UAV trajectory while satisfying each device's requirement and the UAV's limited storage capacity. The formulated optimization problem is troublesome to solve due to its non-convexity and combinatorial nature. {Towards appealing applications, we first relax binary variables into continuous ones and transform the original problem into a more computationally tractable form.} By leveraging inner approximation framework, we derive newly approximated functions for non-convex parts and then develop a simple yet efficient iterative algorithm for its solutions. Next, we attempt to maximize the total throughput subject to the number of served IoT devices. Finally, numerical results show that the proposed algorithms significantly outperform benchmark approaches in terms of the number of served IoT devices and system throughput.

eess.SP↗

arXiv2021

Double-RIS Communication with DF Relaying for Coverage Extension: Is One Relay Enough?

In this work, we investigate the decode-and-forward (DF) relay-aided double reconfigurable intelligent surface (RIS)-assisted networks, where the signal is subject to reflections from two RISs before reaching the destination. Different relay-aided network architectures are considered for maximum achievable rate under a total power constraint. Phase optimization for the double-RIS channels is tackled via the alternating optimization and majorization-minimization (MM) schemes. Moreover, closed-form solutions are obtained for each case. Numerical results indicate that the deployment of two relays, one near each RIS, achieves higher rates at low and medium signal-to noise ratios (SNRs) compared to placing a single relay between the two RISs; while at high SNRs, the latter approach achieves higher rates only if the inter-relay interference for the former case is considerably high.

cs.IT↗

arXiv2021

LEO Satellite Constellations for 5G and Beyond: How Will They Reshape Vertical Domains?

The rapid development of communication technologies in the past decades has provided immense vertical opportunities for individuals and enterprises. However, conventional terrestrial cellular networks have unfortunately neglected the huge geographical digital divide, since high bandwidth wireless coverage is concentrated to urban areas. To meet the goal of ``connecting the unconnected'', integrating low Earth orbit (LEO) satellites with the terrestrial cellular networks has been widely considered as a promising solution. In this article, we first introduce the development roadmap of LEO satellite constellations (SatCons), including early attempts in LEO satellites with the emerging LEO constellations. Further, we discuss the unique opportunities of employing LEO SatCons for the delivery of integrating 5G networks. Specifically, we present their key performance indicators, which offer important guidelines for the design of associated enabling techniques, and then discuss the potential impact of integrating LEO SatCons with typical 5G use cases, where we engrave our vision of various vertical domains reshaped by LEO SatCons. Technical challenges are finally provided to specify future research directions.

eess.SP↗

arXiv2021

Machine Learning-Enabled Joint Antenna Selection and Precoding Design: From Offline Complexity to Online Performance

We investigate the performance of multi-user multiple-antenna downlink systems in which a BS serves multiple users via a shared wireless medium. In order to fully exploit the spatial diversity while minimizing the passive energy consumed by radio frequency (RF) components, the BS is equipped with M RF chains and N antennas, where M < N. Upon receiving pilot sequences to obtain the channel state information, the BS determines the best subset of M antennas for serving the users. We propose a joint antenna selection and precoding design (JASPD) algorithm to maximize the system sum rate subject to a transmit power constraint and QoS requirements. The JASPD overcomes the non-convexity of the formulated problem via a doubly iterative algorithm, in which an inner loop successively optimizes the precoding vectors, followed by an outer loop that tries all valid antenna subsets. Although approaching the (near) global optimality, the JASPD suffers from a combinatorial complexity, which may limit its application in real-time network operations. To overcome this limitation, we propose a learning-based antenna selection and precoding design algorithm (L-ASPA), which employs a DNN to establish underlaying relations between the key system parameters and the selected antennas. The proposed L-ASPD is robust against the number of users and their locations, BS's transmit power, as well as the small-scale channel fading. With a well-trained learning model, it is shown that the L-ASPD significantly outperforms baseline schemes based on the block diagonalization and a learning-assisted solution for broadcasting systems and achieves higher effective sum rate than that of the JASPA under limited processing time. In addition, we observed that the proposed L-ASPD can reduce the computation complexity by 95% while retaining more than 95% of the optimal performance.

cs.IT↗

arXiv2020

A Remote Carrier Synchronization Technique for Coherent Distributed Remote Sensing Systems

Phase, frequency, and time synchronization are crucial requirements for many applications, such as multi-static remote sensing and communication systems. Moreover, the synchronization solution becomes even more challenging when the nodes are orbiting or flying on airborne or spaceborne platforms. This paper compares the available technologies used for the synchronization and coordination of nodes in distributed remote sensing applications. Additionally, this paper proposes a general system model and identifies preliminary guidelines and critical elements for implementing the synchronization mechanisms exploiting the inter-satellite communication link. The distributed phase synchronization loop introduced in this work deals with the self-interference in a full-duplex point to point scenario by transmitting two carriers at each node. All carriers appear with different frequency offsets around a central frequency, called the application central-frequency or the beamforming frequency. This work includes a detailed analysis of the proposed algorithm and the required simulations to verify its performance for different phase noise, AWGN, and Doppler shift scenarios.

eess.SP↗

arXiv2020

Throughput Maximization for Wireless Communication systems with Backscatter- and Cache-assisted UAV Technology

Unmanned aerial vehicle (UAV) has been widely adopted in wireless systems due to its flexibility, mobility, and agility. Nevertheless, a limited onboard battery greatly hinders UAV to prolong the serving time from communication tasks that need a high power consumption in active RF communications. Fortunately, caching and backscatter communication (BackCom) are appealing technology for energy efficient communication systems. This motivates us to investigate a wireless communication network with backscatter- and cache-assisted UAV technology. We assume a UAV with a cache memory is deployed as a flying backscatter device (BD), term the UAV-enabled BD (UB), to relay the source's signals to the destination. Besides, the UAV can harvest energy from the source's RF signals and then utilizes it for backscattering information to the destination. In this context, we aim to maximize the total throughput by jointly optimizing the dynamic time splitting (DTS) ratio, backscatter coefficient, and the UB's trajectory with caching capability at the UB corresponding to linear energy harvesting (LEH) and non-linear energy harvesting (NLEH) models. These formulations are troublesome to directly solve since they are mixed-integer non-convex problems. To find solutions, we decompose the original problem into three subproblems, whereas we first optimize the DTS ratio for a given backscatter coefficient and UB's trajectory, followed by the backscatter coefficient optimization for a given DTS ratio and UB's trajectory, and the UB's trajectory is finally optimized for a given DTS ratio and backscatter coefficient. Finally, the intensive numerical results demonstrate that our proposed schemes achieve significant throughput gain in comparison to the benchmark schemes.

cs.IT↗

arXiv2020

Precoding for Satellite Communications: Why, How and What next?

Precoding has stood out as a promising multi-user transmission technique to meet the emerging throughput demand of satellite communication systems while awaiting the technological maturity for exploiting higher bands. Precoding enables the reduction of interference among co-channel beams through spatial processing while promoting aggressive frequency reuse and improving spectral efficiency. Satellite systems offer multitude of system and service configurations, resulting in different precoder design methodologies. This article explores the motivation for the introduction of precoding, offers an insight to their theoretical development in a diverse scenarios and presents some avenues for future development.

eess.SP↗

arXiv2020

SHARP 2020: The 1st Shape Recovery from Partial Textured 3D Scans Challenge Results

The SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020, is the first edition of a challenge fostering and benchmarking methods for recovering complete textured 3D scans from raw incomplete data. SHARP 2020 is organised as a workshop in conjunction with ECCV 2020. There are two complementary challenges, the first one on 3D human scans, and the second one on generic objects. Challenge 1 is further split into two tracks, focusing, first, on large body and clothing regions, and, second, on fine body details. A novel evaluation metric is proposed to quantify jointly the shape reconstruction, the texture reconstruction and the amount of completed data. Additionally, two unique datasets of 3D scans are proposed, to provide raw ground-truth data for the benchmarks. The datasets are released to the scientific community. Moreover, an accompanying custom library of software routines is also released to the scientific community. It allows for processing 3D scans, generating partial data and performing the evaluation. Results of the competition, analysed in comparison to baselines, show the validity of the proposed evaluation metrics, and highlight the challenging aspects of the task and of the datasets. Details on the SHARP 2020 challenge can be found at https://cvi2.uni.lu/sharp2020/.

cs.CV↗

arXiv2020

On Performance Characterization of Cascaded Multiwire-PLC/MIMO-RF Communication System

The flexibility of radio frequency (RF) systems and the omnipresence of power cables potentially make the cascaded power line communication (PLC)/RF system an efficient and cost-effective solution in terms of wide coverage and high-speed transmission. This letter proposes an opportunistic decode-and-forward (DF)-based multi-wire/RF relaying system to exploit the advantages of both techniques. The outage probability, bit error rate, and system channel capacity are correspondingly chosen to analyze the properties of the proposed system, which are derived in closed-form expressions and validated via Monte-Carlo simulations. One can observe that our proposed system outperforms the wireless-only system in terms of coverage and data rate, especially when there exists a non-line-of-sight (NLoS) connection between the transmitter and receiver pair.

cs.IT↗

arXiv2020

Enabling and Emerging Technologies for Social Distancing: A Comprehensive Survey and Open Problems

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. To that end, we first provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effective and can be widely adopted in practice to keep distance, encourage, and enforce social distancing in general. After that, other emerging and related technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we provide important open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice. As an example, instead of reacting with ad-hoc responses to COVID-19-like pandemics in the future, smart infrastructures (e.g., next-generation wireless systems like 6G, smart home/building, smart city, intelligent transportation systems) should incorporate a pandemic mode in its standard architecture/design.

physics.soc-ph↗

arXiv2020

System Modelling and Design Aspects of Next Generation High Throughput Satellites

Future generation wireless networks are targeting the convergence of fixed, mobile and broadcasting systems with the integration of satellite and terrestrial systems towards utilizing their mutual benefits. Satellite Communications (Sat- Com) is envisioned to play a vital role to provide integrated services seamlessly over heterogeneous networks. As compared to terrestrial systems, the design of SatCom systems require a different approach due to differences in terms of wave propagation, operating frequency, antenna structures, interfering sources, limitations of onboard processing, power limitations and transceiver impairments. In this regard, this letter aims to identify and discuss important modeling and design aspects of the next generation High Throughput Satellite (HTS) systems. First, communication models of HTSs including the ones for multibeam and multicarrier satellites, multiple antenna techniques, and for SatCom payloads and antennas are highlighted and discussed. Subsequently, various design aspects of SatCom transceivers including impairments related to the transceiver, payload and channel, and traffic-based coverage adaptation are presented. Finally, some open topics for the design of next generation HTSs are identified and discussed.

eess.SP↗