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Signals and their functional representation
Published in Alexander D. Poularikas, ®, 2018
Present-day engineers have gone further in studying signals and have been able to establish a quantitative description and measure of the information contained in a signal. To develop their theory, they created a conceptual model communication system, as shown in Figure 1.1.1. To simplify the discussion, let us consider a person who is transmitting a message as an information source. The output of the information source is called a massage — it is what the person is saying. The transmitter is an apparatus that transforms the message into a form that allows it to be transmitted. A telephone handset that converts the acoustic message into a varying electrical current in the telephone line is such a transmitter. The communication channel is the medium over which the message is transmitted. The wires between two telephone receivers and the space between two microwave towers constitute two different types of channels.
Economics and Management of Innovation
Published in Constantine Stephanidis, User Interfaces for All, 2000
Nikolaos Vernardakis, Demosthenes Akoumianakis, Constantine Stephanidis
Innovations diffuse through communication channels. A communication channel is the means by which messages get from one individual to another. The effectiveness of a communication channel decides the fate of an innovation’s adoption. Mass media channels figure prominently in many diffusion processes because of their ability to carry information to a wide audience in a short amount of time. Another effective communication channel in the diffusion process is interpersonal communication. Information and advice from peers often carries more weight in an adoption decision than technical specifications or product documentation.
Mitigation of rock mass response through geotechnical quality assurance
Published in Tadeusz Szwedzicki, Rock Mass Response to Mining Activities, 2018
A communication and reporting system between various levels of a management structure and between all professionals involved in ground control issues should be established and enforced. Communication can be formal (e.g. written instructions, memoranda) or informal (e.g. verbal during meetings). The communication system should ensure that all interested parties receive the required information and that information is understood. Proper communication channels should allow for effective feedback.
Performance analysis of downlink massive MIMO system with precoding techniques and pilot reuse factor
Published in Cogent Engineering, 2023
Fikreselam Gared Mengistu, Gebey Admassu Worku
The simulation parameters were selected for the simulation based on the operation of Massive MIMO technology that can help for the performance of wireless communication systems (particularly, for 5 G, Massive MIMO is one of the enabler technologies for 5 G). For example, 2 GHz carriers frequency was selected because Massive MIMO technology can operate at this frequency and enhance the spectral efficiency of 5 G without increasing bandwidth (for example at 20 MHz).So, the parameters that are described in Table 1 are operate at 2 GHz carriers and communication channel bandwidth of 20 MHz. is the median channel gain at reference distance of 1 km, the path loss exponent, and the standard deviation, are inspired by the NLoS macro cell 3GPP model for 2 GHz carriers (Bjornson et al., 2017). At 20 MHz communication channel bandwidth, UL and DL transmit power are 20dBm per UE(assume both are the same) and receiver noise power is (including thermal noise and a noise figure of in the receiver hardware in case of imperfect CSI).
Modelling and quantification of industry 4.0 manufacturing complexity based on information theory: a robotics case study
Published in International Journal of Production Research, 2019
Dimitris Mourtzis, Sophia Fotia, Nikoletta Boli, Ekaterini Vlachou
As it has been analysed in the previous section, the model that represents a typical Digitalised Manufacturing System is illustrated in Figure 1. Following this modelling, the quantification of the complexity will be performed by measuring the entropy of each system that comprises the Industry 4.0 paradigm (Mourtzis, Fotia, and Vlachou 2017). The Entropy measurement of a system is based on the analogous of Shannon’s communication system (ICTC 2015). According to this, the basic components of a communication system are the information source, the message, the transmitter, the signal, the noise source, the receiver, and the destination. More specifically, the information source selects a desired message out of a set of possible messages (this is a particularly important remark, which requires considerable explanation later). The transmitter transforms this message into the signal, which is sent over the communication channel to the receiver. The receiver changes the transmitted signal back into a message, handing this message to the destination. During the transmission, distortions which were not intended by the information source, are added to the signal. These unwanted additions comprise the noise of the channel. In the Figure 3, Shannon’s communication system is presented.
Optimization–based decoding algorithms for LDPC convolutional codes in communication systems
Published in IISE Transactions, 2019
Banu Kabakulak, Z. Caner Taşkın, Ali Emre Pusane
Digital communication systems transmit information from a sender to a receiver over a communication channel. Communication channels are unreliable environments, such as air, that many sender–receiver pairs share. Hence, during transmission some of the transmitted symbols can be lost or their values can change. In coding theory, information is encoded in order to overcome the occurence of such errors during the transmission. Let the information to be sent be represented by a k–bits long sequence . In order to test whether the information is sent correctly or not, parity bits are added by the encoder. This is done with a k × n generator matrix G through the operation (mod 2). As a result, an n–bits long codeword is obtained. Without loss of generality, we can assume that the first k bits of the codeword are information bits, and the remaining n – k bits are parity bits.