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Sensor Systems for Indoor Position Computation
Published in Krzysztof W. Kolodziej, Johan Hjelm, Local Positioning Systems, 2017
Krzysztof W. Kolodziej, Johan Hjelm
Many radio-based positioning systems use the observed signal strength as an indicator of distance from a radio source. In practice, this works only as well as the radio beacon’s signal strength decays predictably with distance and is not overly attenuated by factors such as the number of walls crossed, the composition of those walls, and multipath effects. For instance, buildings with brick walls attenuate radio signals by a different amount than buildings made of wood or glass. In addition to fixed obstructions in the environment, people, vehicles, and other moving objects can cause the attenuation to vary in a given place over time.
Propagation of Radiation
Published in Ronald L. Snell, Stanley E. Kurtz, Jonathan M. Marr, Fundamentals of Radio Astronomy, 2019
Ronald L. Snell, Stanley E. Kurtz, Jonathan M. Marr
At a wavelength of 100 cm an astronomical radio source is characterized by absorption coefficient κν = 1.3 × 10−20 cm−1 and source function Sν = 7.7 × 10 −14 erg s−1 cm−2 Hz−1 sr−1. If the depth of the radio source is 1 pc, what is the intensity of the radiation emitted by the source? How would the intensity change as the depth of the source is increased to 10 pc? to 100 pc? If the depth of the source were to increase beyond 100 pc would the intensity continue to increase?
Specifics in organization of the slope stability monitoring in high-strength hard rock massif of the Kovdor deposit
Published in Vladimir Litvinenko, Topical Issues of Rational Use of Natural Resources 2019, 2019
The radar operation principle is based on measuring the distance from a radio source to a monitored object. All existing radars differ in range (maximum range of 5000 m), viewing angles, and pixel size (characterizes the degree of detail of the monitored rock mass). At the same time, the maximum permissible environmental conditions (for air: temperature, pressure, humidity, etc.) are almost identical for all types of radar (for example, the temperature difference is from -50 to +50).
Implementing and Characterizing Real-Time Broadband RFI Excision System for the GMRT Wideband Backend
Published in IETE Technical Review, 2019
Kaushal D. Buch, Kishor Naik, Swapnil Nalawade, Shruti Bhatporia, Yashwant Gupta, Ajithkumar B.
Since broadband RFI primarily occurs due to sparking on high-voltage transmission lines around the GMRT array, it is found to be correlated for the closely spaced antennas. As the spacing between the antennas increases, RFI becomes less correlated. This leads to a spurious increase in the correlation even when the antennas are not observing a radio source (i.e. off-source). In order to study the effect of real-time broadband RFI filtering, tests were carried out with the antennas pointing 5 degrees away from the source. Figure 6 shows single spectral channel magnitude and phase of the cross correlation for two short spacing antennas C05-C06 and C06-C13 (left) and two long spacing antennas E03-C06 and W02-C06 (right). Simultaneous observations were carried out to observe the effects with and without filtering in the 250–500 MHz band of uGMRT. For the nearby antenna pairs, the effect of filtering on the magnitude of cross-correlation (subplots (a) and (c) in the left panel) is significant at 2σ threshold. The post-filtering phase of the correlation (subplots (b) and (d) in the left panel) becomes random indicating the reduction in the correlated component of the filtered signal. The antenna pairs separated by longer distances are not affected as seen in the subplots (e)–(h) in the right panel.
An Approach for Energy-Efficient Power Allocation in MIMO–NOMA System
Published in International Journal of Electronics, 2022
Khaleelahmed Sk, VenkateswaraRao N
MIMO increases the channel capacity through spatial multiplexing and increases the transmission reliability using antenna diversity (Gong et al., 2018). MIMO contains two HP architectures, namely sub-connected and fully connected architectures. Moreover, the spectrum efficiency is higher in the fully connected model, but the sub-connected model achieves better energy efficiency (Dai et al., 2018; Heath et al., 2016). Hence, in order to enhance the spectrum efficiency, the NOMA is introduced into the MIMO system (Dai et al., 2018; Ding et al., 2015; Yuan et al., 2017). Signal noise in the communication channel is modelled using probabilistic approaches, and the noise can be varied based on the type of signal transmission of the data (Acharya & Zhang, 2020). For instance, wavelets are being used extensively for data compression, communication applications where the signal is characterised as OFDM, and another application area, i.e., the authentication performed using visual cryptography with the help of wavelets. So, it is evident that efficient power allocation in advanced communication technologies using MIMO–NIMA is essential for better publication of channel resources (Dai et al., 2018; Nerella et al., 2012). NOMA is realised in Hybrid Precoding (HP) with low complexity, and the power was optimally allocated for enhancing sum rate (Dai et al., 2018). The users in the NOMA system utilise the whole modulation bandwidth by the coding of superposition at the transmitting region and SIC at the delivery region (Chen et al., 2018). Due to the efficiency of spectral enhancement, NOMA is substantial attention in the 5G network. NOMA allows different users to share a common radio source in the power field (Tong et al., 2019; Wang et al., 2017; Wei et al., 2018). Due to the efficiency available in the NOMA, the MIMO–NOMA is utilised in the 5 G system through power multiplexing (Al-Hussaibi, et al., 2018; George & Rajakumar, 2013; Perera et al., 2017; Srinivas, 2020; Xiao et al., 2019).