Future generations of wireless communications systems are expected to evolve toward allowing massive ubiquitous connectivity and achieving ultra-reliable and low-latency communications (URLLC) with extremely high data rates. Massive multiple-input multiple-output (m-MIMO) is a crucial transmission technique to fulfill the demands of high data rates in the upcoming wireless systems. However, obtaining a downlink (DL) training sequence (TS) that is feasible for fast channel estimation, i.e., meeting the low-latency communications required by future generations of wireless systems, in m-MIMO with frequency-division-duplex (FDD) when users have different channel correlations is very challenging. Therefore, a low-complexity solution for designing the DL training sequences to maximize the achievable sum rate of FDD systems with limited channel coherence time (CCT) is proposed using a waterfilling power allocation method. This achievable sum rate maximization is achieved using sequences produced from a summation of the user’s covariance matrices and then applying a waterfilling power allocation method to the obtained low-complexity training sequence. The results show that the proposed TS outperforms the existing methods in the medium and high SNR regimes while reducing computational complexity. The obtained results signify the proposed TS’s feasibility for practical consideration compared with the existing DL training sequence designs.
This research presents a response surface methodology (RSM) with I‐optimal method of DESIGN EXPERT (version 13 Stat‐Ease) for optimization and analysis of the adsorption process of the cyanide from aqueous solution by activated carbon (AC) and composite activated carbon (CuO/AC) produced by pyro carbonic acid microwave using potato peel waste as raw material. Pyrophosphate 60% (wt) was used for impregnation with an impregnation ratio 3:1, impregnation time of 4 h at 25°C, radiant power of 700 W, and activation time of 20 min. Batch experiments were conducted to determine the removal efficiency of cyanide from aqueous solution to evaluate the influences of various experimental parameters su
As an important resource, entanglement light source has been used in developing quantum information technologies, such as quantum key distribution(QKD). There are few experiments implementing entanglement-based deterministic QKD protocols since the security of existing protocols may be compromised in lossy channels. In this work, we report on a loss-tolerant deterministic QKD experiment which follows a modified “Ping-Pong”(PP) protocol. The experiment results demonstrate for the first time that a secure deterministic QKD session can be fulfilled in a channel with an optical loss of 9 dB, based on a telecom-band entangled photon source. This exhibits a conceivable prospect of ultilizing entanglement light source in real-life fiber-based
... Show MoreIn this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa
... Show MoreThe present study is meant to inquire about the training needs of middle stage leaders in Bisha, (Saudi Arabia) from the perspective of teachers. To achieve this purpose, the researcher has designed a questionnaire containing (31) items, distributed to a sample of (157) teacher (male and female) from the target population.
This research has demonstrated that the level of training needs for middle stage leaders was moderately reported with an arithmetic mean equivalent to (2.42), and a standard deviation of (0.36). Results have shown no significant differences at (α=0.05) in the sample’s expectations of the study’s variables.
The study concludes with a list of recommendations such as working on developing training pro
... Show MoreThe current research aims to identify the nature of the relationship between training human resources in administrative innovation elements In the General Directorate for the education of the third Rusafa one of the formations of the Iraqi Ministry of Education in Baghdad, In order to achieve the objectives of the research, the researcher provided a comprehensive theoretical framework and the preparation and development of a questionnaire as a tool for collecting data based on the prepared measurements and benefit from previous studies, which contains (28) For the purpose of obtaining realistic results for the variables of the research, the researcher used the random sample in the selection of the research sample A total of (63)
... Show MoreIn the postmodern era, the graphic design styles showed a new visualization method when the graphic designers had changed the traditional conditions by using design elements with new technics for photos, collage and comics illustration. The researcher assumes that the graphic design styles were affected by the art's movement at that period throw the same perspective of view for the concept presented in the art pieces and their entire message. Therefore, the researcher chooses field was the period of 1945-1970 in the USA for the (pop-art and conceptual-art) and explored the main visual effects that expressed the visual dialogue and compared them with the most common design styles ant the same period and location, the results of selected e
... Show MoreWithin the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo
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