Residual Attention networks (RANs) are a class of Convolutional Neural networks (CNNs) that integrate attention mechanisms into deep architectures. RANs employ stacked attention modules to generate attention-aware fea...
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Space-Air-Ground Integrated networks (SAGIN) is expected to become an important information infrastructure in the future spatial information field. However, most existing architectures introduce new protocols to inter...
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Addressing performance portability across diverse accelerator architectures has emerged as a major challenge in the development of application and programming systems for high-performance computing environments. Altho...
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Tuning parallel applications on multi-core architectures is an arduous task. Several studies have utilized auto-tuning for openMP applications via standardized user-facing features, namely number of threads, thread pl...
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The application of neural networks to learning physical systems has seen tremendous growth. This is due in part to the ability of neural networks to act as finite or even infinite dimension solution operators. One rec...
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open Radio Access network (O-RAN) is very promising for flexible and efficient 5G and 6G wireless networks. The O-RAN architecture consists of three main units: Radio Unit (RU), Distributed Unit (DU), and Centralized ...
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ISBN:
(纸本)9798350311143
open Radio Access network (O-RAN) is very promising for flexible and efficient 5G and 6G wireless networks. The O-RAN architecture consists of three main units: Radio Unit (RU), Distributed Unit (DU), and Centralized Unit (CU). In this paper, we study the placement of virtualized DUs. This placement has strong consequences on cost and delay, among others, and is thus an important challenge. First, we analyze the throughput between the O-RAN interfaces. Based on our analysis, we propose an efficient Integer Linear programming (ILP) model. The objective is to minimize the O-RAN cost depending on the DU placement while respecting the delay and capacity constraints. We evaluate our model on a real topology. Our results provide interesting insights into the cost savings with regard to a legacy architecture. Moreover, the proposed model provides solutions in a configuration where a fully centralized Cloud RAN architecture would not. We also estimate the limits of capacity of a given configuration.
Beyond 5G and 6G systems provide significant advances in network architectural design and deployment with the ever-increasing connected devices. In order to address the tremendous growth of cellular traffic, both hard...
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A critical aspect in robot technology lies in ensuring that the robot arm executes the intended task or movement. The conventional teaching-playback technique for programming robot arm movements generates excessive to...
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ISBN:
(纸本)9798350359329;9798350359312
A critical aspect in robot technology lies in ensuring that the robot arm executes the intended task or movement. The conventional teaching-playback technique for programming robot arm movements generates excessive torque when the initial posture differs from that during motion teaching or when external disturbances disrupt robotic arm execution. To address this problem, this study proposed a motion generation system with echo state networks (ESNs) for robot arms. These networks can reproduce trajectories including features such as attractors and bifurcations by training time-series data originating from a dynamical system. By leveraging this capability, the proposed approach enables an ESN to infer a dynamical system underlying demonstrated motions to perform a specific task on the basis of state feedback. Subsequently, the trained ESN generates reference signals to replicate the learned motion based on the current robot state. These reference signals can be used for linear feedback at the joint level. Redundant robots can easily transition to unobserved states because of their degrees of freedom. However, the trained ESN exhibits remarkable generalization capabilities, effectively guiding the robot back to its intended motion in those unobserved states. Numerical simulations confirmed that the proposed system dynamically adapts to robot behavior, effectively mitigating excessive acceleration, even in scenarios with initial posture deviations or external disturbances, thereby outperforming conventional teaching-playback methods.
The proliferation of GPUs and accelerators in recent supercomputing systems, so called heterogeneous architectures, has led to increased complexity in execution environments and programming models as well as to deeper...
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There is an evolution in cellular communication due to the high demand for better quality of service, data rates, capacity, and lower latency. To satisfy these expectations, cellular network design is being drasticall...
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ISBN:
(纸本)9781665483032
There is an evolution in cellular communication due to the high demand for better quality of service, data rates, capacity, and lower latency. To satisfy these expectations, cellular network design is being drastically improved. This paper provides a survey of cellular networkarchitectures, multiple access techniques, and emerging technologies from first generation (1G) to fifth generation (5G). The paper also includes a glimpse at what the forthcoming sixth generation (6G) might anticipate. The architecture of the cellular network from 1G to 5G is presented. Some of the important emerging technologies that enable the architecture to be improved and fulfill user needs are discussed. These emerging technologies include massive MIMO, software-defined networking, mm-Wave, etc. Moreover, multiple access techniques used from 1G to 5G are studied. Comparison among different generations of cellular communication is presented. There are challenges and open issues for 6G which are described.
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