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A practical guide to radio channel measurement techniques Whilst there are numerous books describing modern wireless communication systems that contain overviews of radio propagation and radio channel modelling, few contain detailed information on the design, implementation and calibration of radio channel measurement equipment, the planning of experiments and the in depth analysis of measured data. This work redresses that balance. Beginning with an explanation of the fundamentals of radio wave propagation, the book progresses through a series of topics, including the measurement of radio channel characteristics, radio channel sounders, measurement strategies, data analysis techniques and radio channel modelling. Application of results for the prediction of achievable digital link performance are discussed with examples pertinent to single carrier, multi-carrier and spread spectrum radio links. It addresses specifics of communications in various different frequency bands for both long range and short range fixed and mobile radio links. Key features: Focuses on radio channel measurements and characterization with analysis of MIMO channels Discusses the physical and technical considerations involved in the proper assessment of radio channel characteristics for efficient radio system planning, design, and implementation Provides in-depth information on the planning of experiments and the detailed analysis of measured data from radio propagation and channel modelling Unique practical approach describing how to design and implement channel sounders

The ionosphere's dynamic structure affects electromagnetic radiation by altering radio wave propagation, impacting daily communications. The characteristics of the ionosphere are primarily characterized by electron density parameters. This paper proposes a method to construct Three‐Dimensional (3‐D) electron density distributions with arbitrary spatiotemporal resolution in ISR observational regions. The method, termed Artificial Intelligence‐based data assimilation (AI‐Assim), integrates data assimilation directly into a neural network. It assimilates electron density from the IRI‐2020 model to fill ISR observation gaps. Experiments conducted using the Sanya Incoherent Scatter Radar (SYISR) in Hainan, China, successfully constructed a 3‐D electron density structure over the region, with a 0.2° latitude/longitude resolution and 1 km height resolution. The method's effectiveness was validated by calculating the mean square error and comparing the results with digisonde measurements. Plain Language Summary This study leverages the most powerful ionospheric observation tool, the ISR, to construct 3‐D electron density distributions with arbitrary spatial resolution. Relying solely on empirical models often leads to accuracy issues, while 3‐D electron density models based purely on observational methods typically suffer from low resolution. All observational methods encounter difficulties in achieving continuous, high spatial resolution monitoring of the entire sky, and ISR is one of the most effective techniques available. However, even with interpolation methods, the coverage area of ISR remains limited. Therefore, this study explores a method that uses the neural network to assimilate electron density values from the IRI‐2020 model, aiming to fill the gaps in ISR detection. By assimilating International Reference Ionosphere values to approximate observed values, the accuracy of the 3‐D electron density results is enhanced. Multiple iterations of AI‐ Assim enable the construction of 3‐D electron density distributions with arbitrary spatial resolution. Key Points We developed a method for constructing 3‐D electron density distributions with arbitrary spatiotemporal resolution at ISR stations The method termed AI‐Assim, continuously assimilating electron density from the IRI‐2020 model to fill ISR observation gaps Experiments using SYISR data achieved a 3‐D electron density model with 0.2° map resolution and 1 km height resolution

The Very Low Frequency (VLF) radio wave propagation characteristics play a very important role in understanding the behaviour of the D-region. The earth-ionosphere wave guide theory has been used to evaluate the reflection height of VLF radio waves using the electron density profiles obtained from the International Reference Ionosphere (IRI) 2012 and 2016 models. For calculating the conductivity parameter, two different collision frequency models have been used. The diurnal shift in reflection height of 16-kHz VLF waves is evaluated for the midpoint of Visakhapatnam-Rugby path using the two IRI models and the results are compared with those values derived from VLF phase measurements made at Visakhapatnam. The theoretically evaluated values using the FT-2001 option for the D-region electron density profile in the IRI-2012 and IRI–2016 models are in good agreement with those obtained from phase measurements, especially in summer. The day to night shift in reflection height obtained using exponential collision critical frequency model are in good agreement with those derived from VLF phase measurements. The diurnal shift in reflection height of VLF radio waves during winter months derived from IRI models are much lower than those obtained from measurements.

The millimeter-wave (mmWave) is expected to deliver a huge bandwidth to address the future demands for higher data rate transmissions. However, one of the major challenges in the mmWave band is the increase in signal loss as the operating frequency increases. This has attracted several research interests both from academia and the industry for indoor and outdoor mmWave operations. This paper focuses on the works that have been carried out in the study of the mmWave channel measurement in indoor environments. A survey of the measurement techniques, prominent path loss models, analysis of path loss and delay spread for mmWave in different indoor environments is presented. This covers the mmWave frequencies from 28 GHz to 100 GHz that have been considered in the last two decades. In addition, the possible future trends for the mmWave indoor propagation studies and measurements have been discussed. These include the critical indoor environment, the roles of artificial intelligence, channel characterization for indoor devices, reconfigurable intelligent surfaces, and mmWave for 6G systems. This survey can help engineers and researchers to plan, design, and optimize reliable 5G wireless indoor networks. It will also motivate the researchers and engineering communities towards finding a better outcome in the future trends of the mmWave indoor wireless network for 6G systems and beyond.

Ultrasonic transit time (TT)-based local pulse wave velocity (PWV) measurement is defined as the distance between two beam positions on a segment of common carotid artery (CCA) divided by the TT in the pulse wave propagation. However, the arterial wall motions (AWMs) estimated from ultrasonic radio frequency (RF) signals with a limited number of frames using the motion tracking are typically discrete. In this work, we develop a method involving motion tracking combined with reconstructive interpolation (MTRI) to reduce the quantification errors in the estimated PWs, and thereby improve the accuracy of the TT-based local PWV measurement for CCA. For each beam position, normalized cross-correlation functions (NCCFs) between the reference (the first frame) and comparison (the remaining frames) RF signals are calculated. Thereafter, the reconstructive interpolation is performed in the neighborhood of the NCCFs’ peak to identify the interpolation-deduced peak locations, which are more exact than the original ones. According to which, the improved AWMs are obtained to calculate their TT along a segment of the CCA. Finally, the local PWV is measured by applying a linear regression fit to the time-distance result. In ultrasound simulations based on the pulse wave propagation models of young, middle-aged, and elderly groups, the MTRI method with different numbers of interpolated samples was used to estimate AWMs and local PWVs. Normalized root mean squared errors (NRMSEs) between the estimated and preset values of the AWMs and local PWVs were calculated and compared with ones without interpolation. The means of the NRMSEs for the AWMs and local PWVs based on the MTRI method with one interpolated sample decrease from 1.14% to 0.60% and 7.48% to 4.61%, respectively. Moreover, Bland-Altman analysis and coefficient of variation were used to validate the performance of the MTRI method based on the measured local PWVs of 30 healthy subjects. In conclusion, the reconstructive interpolation for the pulse wave estimation improves the accuracy and repeatability of the carotid local PWV measurement.Ultrasonic transit time-based local pulse wave velocity (PWV) measurement is defined as the distance between two beam positions on a segment of common carotid artery (CCA) divided by the transit time of the pulse wave (PW). However, PWs estimated from ultrasonic radio frequency (RF) signals with a limited number of frames using the motion tracking are typically discontinuous. In this work, a method that involves motion tracking combined with reconstructive interpolation (MTRI) is proposed for PW estimation to improve local PWV measurement. For each beam position, normalized cross-correlation functions (NCCFs) between the reference (the first frame) and comparison (the remaining frames) RF signals are calculated. Thereafter, the reconstructive interpolation is performed in the neighborhood of the NCCFs’ peak to identify the interpolation-deduced peak locations, which are more exact than the original ones. According to which, the improved PWs are obtained to calculate their transit time along a segment of the CCA. Finally, the local PWV is measured by applying a linear regression fit to the time-distance result. In ultrasound simulations based on the PW propagation models of young, middle-aged, and elderly groups, the MTRI method with different numbers of interpolated samples was used to estimate PWs and local PWVs. Normalized root mean squared errors (NRMSEs) between the estimated and preset values of the PWs and local PWVs were calculated and compared with ones without interpolation. The means of the NRMSEs for the PWs and local PWVs based on the MTRI method with one interpolated sample decrease from 1.14% to 0.60% and 7.48% to 4.61%, respectively. Moreover, Bland-Altman analysis and coefficient of variation were used to validate the performance of the MTRI method based on the measured local PWVs of 30 healthy subjects. In conclusion, the MTRI method can improve the PW estimation and thus afford more accurate local PWV measurement.

Energetic electron precipitation (EEP) from the Earth's radiation belts can ionize neutral molecules in the D-region ionosphere (60–90 km altitude), significantly influencing the conductivity and chemical species therein. However, due to the limited resolution of space-borne instruments, the energy and fluxes of electrons that truly precipitate into the atmosphere still remain poorly investigated. To resolve this problem, in this study, we have utilized the wave and particle data measured by the Electric Field Detector (EFD) and High-Energy Particle Detector (HEPP) on board the China Seismo-Electromagnetic Satellite (CSES-01) during nighttime conditions between 2019 and 2021. Using the measurements of extremely low frequency (ELF) waves, we have derived the reflection height of the D-region ionosphere, which turn out to be highly consistent with the electron and X-ray measurements of the CSES. Our results show that the influence of EEP on the two hemispheres is asymmetric: the reflection height in the Northern Hemisphere is in general lowered by 2.5 km, while that in the Southern Hemisphere is lowered by 1.5 km, both of which are consistent with first-principles chemical simulations. We have also found that the decrease in reflection height exhibits strong seasonal variation, which appears to be stronger during wintertime and relatively weaker during summertime. This seasonal difference is likely related to the variation of the background ionospheric electron density. Our findings provide a quantitative understanding of how EEP influences the lower ionosphere during solar minimum periods, which is critical for understanding the magnetosphere–ionosphere coupling and assessing the impact on radio wave propagation.

The concept that geospace storms are comprised of synergistically coupled magnetic storms, ionospheric storms, atmospheric storms, and storms in the electric field originating in the magnetosphere, the ionosphere, and the atmosphere (i.e., electrical storms) was validated a few decades ago. Geospace storm studies require the employment of multiple-method approaches to the Sun–interplanetary medium–magnetosphere–ionosphere–atmosphere–Earth system. This study provides general analysis of the 30 August–2 September 2019 geospace storm, the analysis of disturbances in the geomagnetic field and in the ionosphere, as well as the influence of the ionospheric storm on the characteristics of high frequency (HF) radio waves over the People's Republic of China. The main results of the study are as follows. The energy and power of the geospace storm have been estimated to be 1.5×1015 J and 1.5×1010 W, and thus, this storm is weak. The energy and power of the magnetic storm have been estimated to be 1.5×1015 J and 9×109 W, i.e., this storm is moderate, and a characteristic feature of this storm is the duration of the main phase of up to 2 d. The recovery phase also was lengthy and was no less than 2 d. On 31 August and 1 September 2019, the variations in the H and D components attained 60–70 nT, while the Z-component variations did not exceed 20 nT. On 31 August and 1 September 2019, the level of fluctuations in the geomagnetic field in the 100–1000 s period range increased from 0.2–0.3 to 2–4 nT, while the energy of the oscillations showed a maximum in the 300–400 to 700–900 s period range. During the geospace storm, a moderately to strongly negative ionospheric storm manifested itself by the reduction in the ionospheric F-region electron density by a factor of 1.4 to 2.4 times on 31 August and 1 September 2019, compared to the its values on the reference day. Appreciable disturbances were also observed to occur in the ionospheric E region and possibly in the Es layer. In the course of the ionospheric storm, the altitude of reflection of radio waves could sharply increase from ∼150 to ∼300–310 km. The atmospheric gravity waves generated within the geospace storm modulated the ionospheric electron density; for the ∼30 min period oscillation, the amplitude of the electron density disturbances could attain ∼40 %, while it did not exceed 6 % for the ∼15 min period. At the same time, the height of reflection of the radio waves varied quasi-periodically with a 20–30 km amplitude. The results obtained have made a contribution to the understanding of the geospace storm physics, to developing theoretical and empirical models of geospace storms, to the acquisition of detailed understanding of the adverse effects that geospace storms have on radio wave propagation, and to applying that knowledge to effective forecasting of these adverse influences.

This paper deals with the variations in the Doppler spectra and in the relative amplitudes of the signals observed at oblique incidence over the People's Republic of China (PRC) during the partial solar eclipse of 5–6 January 2019 and on reference days. The observations were made using the multifrequency multipath radio system for sounding the ionosphere at oblique incidence. The receiver system is located at the Harbin Engineering University, PRC, and 14 HF broadcasting station transmitters are used for taking measurements along the following radio-wave propagation paths: Lintong/Pucheng to Harbin, Hwaseong to Harbin, Chiba/Nagara to Harbin, Hailar/Nanmen to Harbin, Beijing to Harbin (three paths), Goyang to Harbin, Ulaanbaatar/Khonkhor to Harbin, Yakutsk to Harbin (two paths), Shijiazhuang to Harbin, Hohhot to Harbin, and Yamata to Harbin. The specific feature of this partial solar eclipse was that it occurred during the local morning with a geomagnetic disturbance (Kp ≈ 3−) in the background. The response of the ionosphere to the solar eclipse has been inferred from temporal variations in the Doppler spectra, the Doppler shift, and the signal relative amplitude. The partial solar eclipse was found to be associated with broadening of the Doppler spectrum, up to ± 1.5 Hz, alternating sign Doppler-shift variations, up to ± 0.5 Hz, in the main ray, and quasi-periodic Doppler-shift changes. The relative amplitude of electron density disturbances in the 15 min period of atmospheric gravity wave field and in the 4–5 min period of infrasound wave field is estimated to be 1.6 %–2.4 % and 0.2 %–0.3 %, respectively. The estimates of a maximum decrease in the electron density are in agreement with the observations.

—Ground-based magnetometers and ionospheric radio probing by means of GPS were used to analyze and interpret specific variations of the geomagnetic field and the total electron content of the ionosphere during strong catastrophic earthquakes in Turkey on February 6, 2023. It is shown that the ionospheric responses to these earthquakes recorded at distances of 1200–1600 km from the epicenter in the lower ionosphere and at distances of up to 500 km from the epicenter in the upper ionosphere can be interpreted in terms of the propagation of the Rayleigh seismic wave and atmospheric waves—shock, acoustic and internal, that is, those waves that are generated by the earthquake itself. The energy of seismic events was estimated from the ionospheric response.