18,181 research outputs found

    CQI reporting strategies for nonregenerative two-way relay networks

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    This paper considers data exchange between two terminals in a nonregenerative two-way relay network. We first propose two efficient channel quality indicator (CQI) reporting schemes based on XOR and superposition coding for single-relay networks. These schemes allow two terminals to simultaneously estimate the CQI of the distant link without incurring additional overhead. In addition, the transmission time for CQI feedback is reduced by half while the loss of performance is negligible. Upper and lower bounds of the mean square error (MSE) of the estimated CQI are derived to analyze various effects on the performance of the proposed schemes. We then extend our MSE analysis to multi-relay networks where a low-complexity relay selection scheme is proposed based on the derived bounds. Simulation results show that, in comparison with conventional methods, this suboptimal bound-based scheme achieves satisfac- tory performance while reducing the complexity at least three times in case of large number of relays

    Linking top managers' behavioural traits with business practices and firm performance

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    We embed an experiment in an ongoing firm-level panel survey with a sample of 623 firms managed by their owners to explore the role of top managers’ behavioral traits as drivers of corporate strategies and performance. We find that present biased managers are less likely to invest in business practices, leading to lower sales revenue. Younger managers are more patient and less risk-averse than older ones, and they play a more significant role in improving firm performance than their counterparts. Interestingly, we find compelling evidence that business practices play a crucial role as a mediating mechanism through which managers’ present bias and loss aversion affect firm performance

    An exploration on the nexus between managers’ present bias and corporate investment

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    This study aims to explore the role of top manager’s present bias as a main driver of corporate investment. For this purpose, we embed an experiment in a firm-level panel survey with a sample of top managers from 623 textile and garment firms in Vietnam. The experiment enables us to elicit present bias for each individual manager. We find that firms led by managers with a greater level of present bias are more likely to have a lower investment. There also exists evidence that the effect of managers’ present bias on corporate investment is stronger for SMEs than for large firms

    Network coding-based channel quality indicator reporting for two-way multi-relay networks

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    This paper considers channel quality indicator (CQI) reporting for data exchange in a two-way multi-relay network. We first propose an efficient CQI reporting scheme based on network coding, where two terminals are allowed to simultaneously estimate the CQI of the distant terminal-relay link without suffering from additional overhead. In addition, the transmission time for CQI feedback at the relays is reduced by half while the increase in complexity and the loss of performance are negligible. This results in a system throughput improvement of 16.7% with our proposed CQI reporting. Upper and lower bounds of the mean square error (MSE) of the estimated CQI are derived to study performance behaviour of our proposed scheme. It is found that the MSE of the estimated CQI increases proportionally with the square of the cardinality of CQI level sets although an increased number of CQI levels would eventually lead to a higher data rate transmission. On the basis of the derived bounds, a low-complexity relay selection (RS) scheme is then proposed. Simulation results show that, in comparison with optimal methods, our suboptimal bound-based RS scheme achieves satisfactory performance while reducing the complexity at least three times in case of large number of relays

    Deep-NC: a secure image transmission using deep learning and network coding

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    Visual communications have played an important part in our daily life as a non-verbal way of conveying information using symbols, gestures and images. With the advances of technology, people can visually communicate with each other in a number of forms via digital communications. Recently Image Super-Resolution (ISR) with Deep Learning (DL) has been developed to reproduce the original image from its low-resolution version, which allows us to reduce the image size for saving transmission bandwidth. Although many benefits can be realised, the image transmission over wireless media experiences inevitable loss due to environment noise and inherent hardware issues. Moreover, data privacy is of vital importance, especially when the eavesdropper can easily overhear the communications over the air. To this end, this paper proposes a secure ISR protocol, namely Deep-NC, for the image communications based on the DL and Network Coding (NC). Specifically, two schemes, namely Per-Image Coding (PIC) and Per-Pixel Coding (PPC), are designed so as to protect the sharing of private image from the eavesdropper. Although the PPC scheme achieves a better performance than the PIC scheme for the entire image, it requires a higher computational complexity on every pixel of the image. In the proposed Deep-NC, the intended user can easily recover the original image achieving a much higher performance in terms of Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) than those at the eavesdropper. Simulation results show that an improvement of up to 32 dB in the PSNR can be obtained when the eavesdropper does not have any knowledge of the parameters and the reference image used in the mixing schemes. Furthermore, the original image can be downscaled to a much lower resolution for saving significantly the transmission bandwidth with negligible performance loss

    An induction theorem and nonlinear regularity models

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    A general nonlinear regularity model for a set-valued mapping F:X×R+⇉YF:X\times R_+\rightrightarrows Y, where XX and YY are metric spaces, is considered using special iteration procedures, going back to Banach, Schauder, Lusternik and Graves. Namely, we revise the induction theorem from Khanh, J. Math. Anal. Appl., 118 (1986) and employ it to obtain basic estimates for studying regularity/openness properties. We also show that it can serve as a substitution of the Ekeland variational principle when establishing other regularity criteria. Then, we apply the induction theorem and the mentioned estimates to establish criteria for both global and local versions of regularity/openness properties for our model and demonstrate how the definitions and criteria translate into the conventional setting of a set-valued mapping F:X⇉YF:X\rightrightarrows Y.Comment: 28 page

    Digital twin for O-RAN towards 6G

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    In future wireless systems of beyond 5G and 6G, addressing diverse applications with varying quality requirements is essential. Open Radio Access Network (O-RAN) architectures offer the potential for dynamic resource adaptation based on traffic demands. However, achieving real-time resource orchestration remains a challenge. Simultaneously, Digital Twin (DT) technology holds promise for testing and analysing complex systems, offering a unique platform for addressing dynamic operation and automation in O-RAN architectures. Yet, developing DTs for complex 5G/6G networks poses challenges, including data exchanges, ML model training data availability, network dynamics, processing power limitations, interdisciplinary collaboration needs, and a lack of standardized methodologies. This paper provides an overview of Open RAN architecture, trend and challenges, proposing the DT concepts for O-RAN with solution examples showcasing its integration into the framework

    Trust under the prospect theory and quasi-hyperbolic preferences: a field experiment in Vietnam

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    We conduct a field experiment in Vietnamese villages to explore the effect of the prospect theory and of quasi-hyperbolic time preferences parameters on trust and trustworthiness. We find that risk aversion, loss aversion and present bias do not influence trustors’ decisions, but a higher time discounting increases the amount sent in the South of Vietnam and probability weighting decreases it in the North. If time discounting and loss aversion do not influence trustworthiness, we show that more risk averse and less present biased trustees return a higher share of their wealth to the trustors. These results suggest that adopting another perspective than the expected utility theory and the exponential discounting approach of time preferences enables to uncover some channels by which risk and intertemporal time preferences influence trusting behavior in societies
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