Non-Orthogonal Multiple Access(NOMA)is an ideal choice for 5G waveforms due to their characteristics such as high data rate,massive device connectivity,high spectral access,and effective frequency selective ***,it per...
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Non-Orthogonal Multiple Access(NOMA)is an ideal choice for 5G waveforms due to their characteristics such as high data rate,massive device connectivity,high spectral access,and effective frequency selective ***,it permits gigantic *** spectrum overlaps with NOMA,which consents several operators to segment the spectrum at the same *** features make NOMA more suitable for use beyond *** to Average Power(PAPR)is a major problem in Multi-Carrier Techniques(MCT)like NOMA and it also degrades the performance of the *** Partial Transmission Sequence(PTS)is a superior algorithm for moderating the ***,it also increases the complexity of the *** PAPR is reduced in NOMA by multiplying the NOMA signal with optimised phase vectors(P).The phase vectors are generated by using the Vandermonde Matrix(VM).In this work,we proposed a VM-PTS algorithm for the NOMA system,and the number of computations to search the optimal phase vectors for NOMA high PAPR signal is less as compared with existing *** outcomes demonstrate that the performance of the recommended PTS in terms of PAPR,Bit Error Rate(BER),and complexity is better than the conventional PTS(C-PTS).
A reconfigurable low-noise amplifier (LNA) is proposed with integrated bandpass filter (BPF) responses covering 2.8 3.8 GHz in this letter. The proposed LNA consists of three cascaded transistor stages. By integrating...
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Due to their need to handle a huge size of image data and limited battery power at each node, visual sensor networks (VSNs) suffer from short network lifetime and long network delay. Consequently, how to reduce networ...
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Building energy demand response is projected to be important in decarbonizing energy use. A demand responseprogram that communicates ‘‘artificial’’ hourly price signals to workers as part of a social game has the ...
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Building energy demand response is projected to be important in decarbonizing energy use. A demand responseprogram that communicates ‘‘artificial’’ hourly price signals to workers as part of a social game has the potentialto elicit energy consumption changes that simultaneously reduce energy costs and emissions. The efficacy ofsuch a program depends on the pricing agent’s ability to learn how workers respond to prices and mitigatethe risk of high energy costs during this learning process. We assess the value of deep reinforcement learning(RL) for mitigating this risk. Specifically, we explore the value of combining: (i) a model-free RL method thatcan learn by posting price signals to workers, (ii) a supervisory ‘‘planning model’’ that provides a syntheticlearning environment, and (iii) a guardrail method that determines whether a price should be posted to realworkers or the planning environment for feedback. In a simulated medium-sized office building, we compareour pricing agent against existing model-free and model-based deep RL agents, and the simpler strategy ofpassing on the time-of-use price signal to workers. We find that our controller eliminates 175,000 US Dollarsin initial investment, decreases by 30% the energy cost, and curbs emissions by 32% compared to energyconsumption under the time-of-use rate. In contrast, the model-free and model-based deep RL benchmarksare unable to overcome initial learning costs. Our results bode well for risk-aware deep RL facilitating thedeployment of building demand response.
This paper aims to apply knowledge graph construction techniques to textbooks, explicitly focusing on the challenge of the absence of domain-specific schema for each textbook. Various entity and relation extraction mo...
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Background: Cardiovascular Diseases (CVD) requires precise and efficient diagnostic tools. The manual analysis of Electrocardiograms (ECGs) is labor-intensive, necessitating the development of automated methods to enh...
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Over the decades, technology has presented human facets with diverse means of accomplishing complex tasks, especially in the communication domain. One of the risks identified over the decade terrifying network devices...
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Exterior painting of high-rise buildings is a challenging task. In our country, as well as in other countries of the world, this task is accomplished manually, which is risky and life-threatening for the workers. Rese...
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In this work we present the design and development of a twitching control system for pneumatic artificial muscle (PAM) actuators. In this system, a shape memory alloy (SMA) poppet valve is used to control the flow of ...
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