Integration of backscatter communication with multi-cell NOMA: a spectral efficiency optimization under imperfect SIC

Poster (2022, November 03)

Future wireless networks are expected to connect large-scale low-powered communication devices using the available spectrum resources. Backscatter communications (BC) is an emerging technology towards ... [more ▼]

Future wireless networks are expected to connect large-scale low-powered communication devices using the available spectrum resources. Backscatter communications (BC) is an emerging technology towards battery-free transmission in future wireless networks by leveraging ambient radio frequency (RF) waves that enable communications among wireless devices. Non-orthogonal multiple access (NOMA) has recently drawn significant attention due to its high spectral efficiency. The combination of these two technologies can play an important role in the development of future networks. This paper proposes a new optimization approach to enhance the spectral efficiency of nonorthogonal multiple access (NOMA)-BC network. Our framework simultaneously optimizes the power allocation of base station and reflection coefficient (RC) of the backscatter device in each cell under the assumption of imperfect signal decoding. The problem of spectral efficiency maximization is coupled on power and RC which is challenging to solve. To make this problem tractable, we first decouple it into two subproblems and then apply the decomposition method and Karush-Kuhn-Tucker conditions to obtain the efficient solution. Numerical results show the performance of the proposed NOMA-BC network over the pure NOMA network without BC. [less ▲]

Towards the Application of Neuromorphic Computing to Satellite Communications

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

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

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

Satellite Beam Densification for High-Demand Areas

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

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

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

Learning to Optimize: Balancing Two Conflict Metrics in MB-HTS Networks

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

Enhanced Communications on Satellite-Based IoT Systems to Support Maritime Transportation Services

in Sensors (2022), 22(17),

Maritime transport has become important due to its ability to internationally unite all continents. In turn, during the last two years, we have observed that the increase of consumer goods has resulted in ... [more ▼]

Maritime transport has become important due to its ability to internationally unite all continents. In turn, during the last two years, we have observed that the increase of consumer goods has resulted in global shipping deadlocks. In addition, the future goes through the role of ports and efficiency in maritime transport to decarbonize its impact on the environment. In order to improve the economy and people’s lives, in this work, we propose to enhance services offered in maritime logistics. To do this, a communications system is designed on the deck of ships to transmit data through a constellation of satellites using interconnected smart devices based on IoT. Among the services, we highlight the monitoring and tracking of refrigerated containers, the transmission of geolocation data from Global Positioning System (GPS), and security through the Automatic Identification System (AIS). This information will be used for a fleet of ships to make better decisions and help guarantee the status of the cargo and maritime safety on the routes. The system design, network dimensioning, and a communications protocol for decision-making will be presented. [less ▲]

Rate Splitting Multiple Access for Next Generation Cognitive Radio Enabled LEO Satellite Networks

in Bulletin. Cornell University Libraries (2022)

Low Earth Orbit (LEO) satellite communication (SatCom) has drawn particular attention recently due to its high data rate services and low round-trip latency. It has low launching and manufacturing costs ... [more ▼]

Low Earth Orbit (LEO) satellite communication (SatCom) has drawn particular attention recently due to its high data rate services and low round-trip latency. It has low launching and manufacturing costs than Medium Earth Orbit (MEO) and Geostationary Earth Orbit (GEO) satellites. Moreover, LEO SatCom has the potential to provide global coverage with a high-speed data rate and low transmission latency. However, the spectrum scarcity might be one of the challenges in the growth of LEO satellites, impacting severe restrictions on developing ground-space integrated networks. To address this issue, cognitive radio and rate splitting multiple access (RSMA) are the two emerging technologies for high spectral efficiency and massive connectivity. This paper proposes a cognitive radio enabled LEO SatCom using RSMA radio access technique with the coexistence of GEO SatCom network. In particular, this work aims to maximize the sum rate of LEO SatCom by simultaneously optimizing the power budget over different beams, RSMA power allocation for users over each beam, and subcarrier user assignment while restricting the interference temperature to GEO SatCom. The problem of sum rate maximization is formulated as non-convex, where the global optimal solution is challenging to obtain. Thus, an efficient solution can be obtained in three steps: first we employ a successive convex approximation technique to reduce the complexity and make the problem more tractable. Second, for any given resource block user assignment, we adopt Karush–Kuhn–Tucker (KKT) conditions to calculate the transmit power over different beams and RSMA power allocation of users over each beam. Third, using the allocated power, we design an efficient algorithm based on the greedy approach for resource block user assignment. For comparison, we propose two suboptimal schemes with fixed power allocation over different beams and random resource block user assignment as the benchmark. Numerical results provided in this work are obtained based on the Monte Carlo simulations, which demonstrate the benefits of the proposed optimization scheme compared to the benchmark schemes. [less ▲]

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

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 ▲]

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

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 ▲]

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

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 ▲]

Machine Learning for Radio Resource Management in Multibeam GEO Satellite Systems

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 ▲]