16,297 research outputs found
Optimal Transmit Power and Channel-Information Bit Allocation With Zeroforcing Beamforming in MIMO-NOMA and MIMO-OMA Downlinks
In downlink, a base station (BS) with multiple transmit antennas applies
zeroforcing beamforming to transmit to single-antenna mobile users in a cell.
We propose the schemes that optimize transmit power and the number of bits for
channel direction information (CDI) for all users to achieve the max-min
signal-to-interference plus noise ratio (SINR) fairness. The optimal allocation
can be obtained by a geometric program for both non-orthogonal multiple access
(NOMA) and orthogonal multiple access (OMA). For NOMA, 2 users with highly
correlated channels are paired and share the same transmit beamforming. In some
small total-CDI rate regimes, we show that NOMA can outperform OMA by as much
as 3 dB. The performance gain over OMA increases when the
correlation-coefficient threshold for user pairing is set higher. To reduce
computational complexity, we propose to allocate transmit power and CDI rate to
groups of multiple users instead of individual users. The user grouping scheme
is based on K-means over the user SINR. We also propose a progressive filling
scheme that performs close to the optimum, but can reduce the computation time
by almost 3 orders of magnitude in some numerical examples
Formation control of robots in nonlinear two-dimensional potential
The formation control of multi-agent systems has garnered significant
research attention in both theoretical and practical aspects over the past two
decades. Despite this, the examination of how external environments impact
swarm formation dynamics and the design of formation control algorithms for
multi-agent systems in nonlinear external potentials have not been thoroughly
explored. In this paper, we apply our theoretical formulation of the formation
control algorithm to mobile robots operating in nonlinear external potentials.
To validate the algorithm's effectiveness, we conducted experiments using real
mobile robots. Furthermore, the results demonstrate the effectiveness of
Dynamic Mode Decomposition in predicting the velocity of robots in unknown
environments
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions
The Metaverse offers a second world beyond reality, where boundaries are
non-existent, and possibilities are endless through engagement and immersive
experiences using the virtual reality (VR) technology. Many disciplines can
benefit from the advancement of the Metaverse when accurately developed,
including the fields of technology, gaming, education, art, and culture.
Nevertheless, developing the Metaverse environment to its full potential is an
ambiguous task that needs proper guidance and directions. Existing surveys on
the Metaverse focus only on a specific aspect and discipline of the Metaverse
and lack a holistic view of the entire process. To this end, a more holistic,
multi-disciplinary, in-depth, and academic and industry-oriented review is
required to provide a thorough study of the Metaverse development pipeline. To
address these issues, we present in this survey a novel multi-layered pipeline
ecosystem composed of (1) the Metaverse computing, networking, communications
and hardware infrastructure, (2) environment digitization, and (3) user
interactions. For every layer, we discuss the components that detail the steps
of its development. Also, for each of these components, we examine the impact
of a set of enabling technologies and empowering domains (e.g., Artificial
Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on
its advancement. In addition, we explain the importance of these technologies
to support decentralization, interoperability, user experiences, interactions,
and monetization. Our presented study highlights the existing challenges for
each component, followed by research directions and potential solutions. To the
best of our knowledge, this survey is the most comprehensive and allows users,
scholars, and entrepreneurs to get an in-depth understanding of the Metaverse
ecosystem to find their opportunities and potentials for contribution
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
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Physical layer security for wireless-powered ambient backscatter cooperative communication networks
Low power consumption and high spectrum efficiency as the great challenges for multi-device access to Internet-of-Things (IoT) have put forward stringent requirements on the future intelligent network. Ambient backscatter communication (ABcom) is regarded as a promising technology to cope with the two challenges, where backscatter device (BD) can reflect ambient radio frequency (RF) signals without additional bandwidth. However, minimalist structural design of BD makes ABcom security vulnerable in wireless propagation environments. By virtue of this fact, this paper considers the physical layer security (PLS) of a wireless-powered ambient backscatter cooperative communication network threatened by an eavesdropper, where the BD with nonlinear energy harvesting model cooperates with decode-and-forward (DF) relay for secure communication. The PLS performance is investigated by deriving the secrecy outage probability (SOP) and secrecy energy efficiency (SEE). Specifically, the closed-form and asymptotic expressions of SOP are derived as well as the secrecy diversity order for the first time. As an energy-constrained device, balancing power consumption and security is major concern for BD, thus the SEE of the proposed network is studied. The results from numerical analysis show that the performance improvement of SOP and SEE is impacted by system parameters, including transmit power, secrecy rate threshold, reflection efficiency and distance between the source and BD, which provide guidance on balancing security and energy efficiency in ambient backscatter cooperative relay networks
Unpredictable Needs are Associated with Lower Expectations of Repayment
Sometimes people help one another expecting to be repaid, while at other times people help without an expectation of repayment. What might underlie this difference in expectations of repayment? We investigate this question in a nationally representative sample of US adults (N = 915), and find that people are more likely to expect repayment when needs are perceived to be more predictable. We then replicate these findings in a new sample of US adults (N = 417), and show that people have higher expectations of repayment when needs are perceived to be more predictable because people assign greater responsibility to others for experiencing such predictable needs (e.g., needing money for utilities). This is consistent with previous work based on smaller-scale societies, which shows that the predictability of needs influences expectations of repayment. Our results also add to this previous work by (1) showing that the positive relationship between predictability of needs and expectations of repayment previously found in smaller-scale communities is generalizable to the US population, and (2) showing that attributions of responsibility partially mediate this relationship. This work shows that the predictability of needs and attributions of responsibility for that need are important factors underlying the psychology of helping in times of need
A Design Science Research Approach to Smart and Collaborative Urban Supply Networks
Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness.
A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense.
Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice
The stumbling block in ‘the race of our lives’: transition-critical materials, financial risks and the NGFS climate scenarios
Several ‘critical’ raw materials, including metals, minerals and Rare Earth Elements (REEs), play a central role in the low-carbon transition and are needed to expand the deployment of low-carbon technologies. The reliable and affordable supply of these resources is subject to supply-side risks and demand-induced pressures. This paper empirically estimates the material demand requirements for ‘Transition-Critical Materials’ (TCMs) implied under two NGFS Climate Scenarios, namely the ‘Net Zero by 2050’ and ‘Delayed Transition’ scenarios. We apply material intensity estimates to the underlying assumptions on the deployment of low-carbon technologies to determine the implied material demand between 2021 and 2040 for nine TCMs. We find several materials to be subject to significant demand-induced pressures under both scenarios. Subsequently, the paper examines the possible emergence of material bottlenecks for three materials, namely copper, lithium and nickel. The results indicate possible substantial mismatches between supply and demand, which would be further exacerbated if the transition is delayed rather than realised immediately. We discuss these findings in the context of different possible transmission channels through which these bottlenecks could affect financial and price stability, and propose avenues for future research
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