Rethinking the frequency code: a meta-analytic review of the role of acoustic body size in communicative phenomena

The widely cited frequency code hypothesis attempts to explain a diverse range of communicative phenomena through the acoustic projection of body size. The set of phenomena includes size sound symbolism (using /i/ to signal smallness in words such as teeny ), intonational phonology (using rising contours to signal questions) and the indexing of social relations via vocal modulation, such as lowering one's voice pitch to signal dominance. Among other things, the frequency code is commonly interpreted to suggest that polite speech should be universally signalled via high pitch owing to the association of high pitch with small size and submissiveness. We present a cross-cultural meta-analysis of polite speech of 101 speakers from seven different languages. While we find evidence for cross-cultural variation, voice pitch is on average lower when speakers speak politely, contrary to what the frequency code predicts. We interpret our findings in the light of the fact that pitch has a multiplicity of possible communicative meanings. Cultural and contextual variation determines which specific meanings become manifest in a specific interactional context. We use the evidence from our meta-analysis to propose an updated view of the frequency code hypothesis that is based on the existence of many-to-many mappings between speech acoustics and communicative interpretations. This article is part of the theme issue ‘Voice modulation: from origin and mechanism to social impact (Part I)’.

Real-time single-frequency precise positioning with Galileo satellites

Following substantial progress achieved recently, the Galileo constellation provides a considerable satellite resource for the GNSS applications. In this regard, the performance assessment of real-time single-frequency precise positioning with Galileo satellites is the main objective of this research. For this purpose, several experimental tests were conducted in this study with two single-frequency positioning models, namely single-frequency code-based positioning and code-phase combination. The results show that Galileo presents an adequate number of visible satellites sufficient for single-frequency positioning. Also, the study demonstrates that, in comparison to GPS observations, Galileo observations have a significantly lower noise level. For the single-frequency code-based positioning, Galileo presents a better positioning accuracy than GPS by 25⋅8% on average. When compared with GPS, a 9⋅4% better positioning accuracy is acquired from Galileo for the single-frequency code-phase combination, with its average convergence time shorter than GPS by a ratio of 24⋅4%.

Phase Spectrometry For High Precision mm-Wave DoA Estimation In 5G Systems

In this paper, we introduce a direction of arrival (DoA) estimation method based on a technique named phase spectrometry (PS) that is mainly suitable for mm-Wave and Tera-hertz applications as an alternative for DoA estimation using antenna arrays. PS is a conventional technique in optics to measure phase difference between two waves at different frequencies of the spectrum. Here we adapt PS for the same purpose in the radio frequency band. We show that we can emulate a large array exploiting only two antennas. To this end, we measure phase difference between the two antennas for different frequencies using PS. Consequently, we demonstrate that we can radically reduce the complexity of the receiver required for DoA estimation employing PS. We consider two different schemes for implementation of PS: via a long wave-guide and frequency code-book. We show that using a frequency code-book, higher processing gain can be achieved. Moreover, we introduce three PS architectures: for device to device DoA estimation, for base-station in uplink scenario and an ultra-fast DoA estimation technique mainly for radar and aerial and satellite communications. Simulation and analytical results show that, PS is capable of detecting and discriminating between multiple incoming signals with different DoAs. Moreover, our results also show that, the angular resolution of PS depends on the distance between the two antennas and the band-width of the frequency code-book. Finally, the performance of PS is compared with a uniform linear array (ULA) and it is shown that PS can perform the same, with a much less complex receiver, and without the prerequisite of spatial search for DoA estimation.

Phase Spectrometry For High Precision mm-Wave DoA Estimation In 5G Systems

In this paper, we introduce a direction of arrival (DoA) estimation method based on a technique named phase spectrometry (PS) that is mainly suitable for mm-Wave and Tera-hertz applications as an alternative for DoA estimation using antenna arrays. PS is a conventional technique in optics to measure phase difference between two waves at different frequencies of the spectrum. Here we adapt PS for the same purpose in the radio frequency band. We show that we can emulate a large array exploiting only two antennas. To this end, we measure phase difference between the two antennas for different frequencies using PS. Consequently, we demonstrate that we can radically reduce the complexity of the receiver required for DoA estimation employing PS. We consider two different schemes for implementation of PS: via a long wave-guide and frequency code-book. We show that using a frequency code-book, higher processing gain can be achieved. Moreover, we introduce three PS architectures: for device to device DoA estimation, for base-station in uplink scenario and an ultra-fast DoA estimation technique mainly for radar and aerial and satellite communications. Simulation and analytical results show that, PS is capable of detecting and discriminating between multiple incoming signals with different DoAs. Moreover, our results also show that, the angular resolution of PS depends on the distance between the two antennas and the band-width of the frequency code-book. Finally, the performance of PS is compared with a uniform linear array (ULA) and it is shown that PS can perform the same, with a much less complex receiver, and without the prerequisite of spatial search for DoA estimation.

Phase Spectrometry For High Precision mm-Wave DoA Estimation In 5G Systems

In this paper, we introduce a direction of arrival (DoA) estimation method based on a technique named phase spectrometry (PS) that is mainly suitable for mm-Wave and Tera-hertz applications as an alternative for DoA estimation using antenna arrays. PS is a conventional technique in optics to measure phase difference between two waves at different frequencies of the spectrum. Here we adapt PS for the same purpose in the radio frequency band. We show that we can emulate a large array exploiting only two antennas. To this end, we measure phase difference between the two antennas for different frequencies using PS. Consequently, we demonstrate that we can radically reduce the complexity of the receiver required for DoA estimation employing PS. We consider two different schemes for implementation of PS: via a long wave-guide and frequency code-book. We show that using a frequency code-book, higher processing gain can be achieved. Moreover, we introduce three PS architectures: for device to device DoA estimation, for base-station in uplink scenario and an ultra-fast DoA estimation technique mainly for radar and aerial and satellite communications. Simulation and analytical results show that, PS is capable of detecting and discriminating between multiple incoming signals with different DoAs. Moreover, our results also show that, the angular resolution of PS depends on the distance between the two antennas and the band-width of the frequency code-book. Finally, the performance of PS is compared with a uniform linear array (ULA) and it is shown that PS can perform the same, with a much less complex receiver, and without the prerequisite of spatial search for DoA estimation.

Method for transforming symbolic radar marks of low-noticeable moving objects based on the Talbot effect

In this paper a method to transform radar images of moving aerial objects with scintillating inter-period fluctuations, sometimes resulting to complete signal fading, using the Talbot effect is considered. These transformations are reduced to the establishment of a certain correspondence of the asymptotic equality of perception of visual images, arbitrarily changing in time and space, in the statement about the conditions of simple equality of perception of images of radar marks that have different frequencies of fluctuations. It is shown how this approach can be used to analyze radar data by transforming and smoothing scintillating signal fluctuations, invisible in the presence of interference, into visible symbolic images. First, to detect and recognize the aerial objects from the analysis of relations and functional (semantic) dependencies between attributes, second, to make a decision based on semantic components of symbolic radar images. The possibility of using such transformation to generate pulse-frequency code of fluctuations of the symbolic radar angel-echo images as an important characteristic for their recognition has been experimentally verified. Algorithms for generating symbolic images in asynchronous and synchronous pulse-frequency code are formulated. The symbolic image represented by such a code is considered as an additional feature for recognizing and filtering out natural interferences such as angel-echoes.

Integration of precise point positioning and reduced inertial sensors system

In Global Positioning System (GPS), Precise Point Positioning (PPP) achieves the highest accuracy in point positioning. It approaches centimetre-level accuracy in static mode and sub-decimetre accuracy in kinematic mode. PPP is an alternative approach to carrier-phase-based Differential GPS (DGPS) and offers advantages over DGPS. PPP uses GPS observations from a single receiver for position estimation, which is simpler than using more than one GPS receiver. However, PPP needs rigorous modelling for all errors and biases, which are otherwise cancelled out or mitigated when using DGPS. PPP’s popularity is on the rise, as it is ideal for land-vehicle positioning and navigation. However, in challenging environments, PPP suffers from a signal loss that prevent continuous navigation or a reduction in the number of visible satellites that causes accuracy degradation. This research integrates PPP with a Reduced Inertial Sensors System (RISS) — a low-cost system that uses data from reduced MEMS-based inertial sensors and vehicle odometry — to provide accurate and inexpensive land-vehicle navigation systems. The system is integrated in a tightly coupled mode through the use of an Extended Kalman Filter (EKF), which employs an improved error model for the RISS data. The system was tested using data from real driving routes with single-frequency code-based PPP/RISS (SF-code-PPP/RISS), dual-frequency code-based PPP (DF-code-PPP/RISS), smoothed dual-frequency code-based PPP (S-DF-code-PPP/RISS), and code- and carrier-phase-based PPP (code-carrier-PPP/RISS). The performance of the developed PPP/RISS was evaluated using position RMS and maximum errors during continuous GPS availability as well as during signal outages. The developed integrated algorithms were assessed using three real road tests that capture different navigational conditions. The results show that when five or more satellites are available, code-carrier-PPP/RISS solution is superior to that of SF- and DF-code-PP/RISS. For latitude, code-carrier-PPP/RISS solution was 47% and 20% more precise than the SF- and DF-code- PP/RISS counterparts, respectively. For longitude, code-carrier-PPP/RISS solution was 65% and 31% more precise than the SF- and DF-Code-PP/RISS counterparts, respectively. Similarly, the altitude solution was improved by 46% and 25%, respectively. During GPS signal outages of 60 seconds, code-carrier-PPP/RISS’s algorithms outperformed that of SF- and DF-code-PPP/RISS by about 35% when the satellite availability level was set to three satellites. For other satellite availability levels, the algorithms performed almost identically.

Integration of precise point positioning and reduced inertial sensors system

In Global Positioning System (GPS), Precise Point Positioning (PPP) achieves the highest accuracy in point positioning. It approaches centimetre-level accuracy in static mode and sub-decimetre accuracy in kinematic mode. PPP is an alternative approach to carrier-phase-based Differential GPS (DGPS) and offers advantages over DGPS. PPP uses GPS observations from a single receiver for position estimation, which is simpler than using more than one GPS receiver. However, PPP needs rigorous modelling for all errors and biases, which are otherwise cancelled out or mitigated when using DGPS. PPP’s popularity is on the rise, as it is ideal for land-vehicle positioning and navigation. However, in challenging environments, PPP suffers from a signal loss that prevent continuous navigation or a reduction in the number of visible satellites that causes accuracy degradation. This research integrates PPP with a Reduced Inertial Sensors System (RISS) — a low-cost system that uses data from reduced MEMS-based inertial sensors and vehicle odometry — to provide accurate and inexpensive land-vehicle navigation systems. The system is integrated in a tightly coupled mode through the use of an Extended Kalman Filter (EKF), which employs an improved error model for the RISS data. The system was tested using data from real driving routes with single-frequency code-based PPP/RISS (SF-code-PPP/RISS), dual-frequency code-based PPP (DF-code-PPP/RISS), smoothed dual-frequency code-based PPP (S-DF-code-PPP/RISS), and code- and carrier-phase-based PPP (code-carrier-PPP/RISS). The performance of the developed PPP/RISS was evaluated using position RMS and maximum errors during continuous GPS availability as well as during signal outages. The developed integrated algorithms were assessed using three real road tests that capture different navigational conditions. The results show that when five or more satellites are available, code-carrier-PPP/RISS solution is superior to that of SF- and DF-code-PP/RISS. For latitude, code-carrier-PPP/RISS solution was 47% and 20% more precise than the SF- and DF-code- PP/RISS counterparts, respectively. For longitude, code-carrier-PPP/RISS solution was 65% and 31% more precise than the SF- and DF-Code-PP/RISS counterparts, respectively. Similarly, the altitude solution was improved by 46% and 25%, respectively. During GPS signal outages of 60 seconds, code-carrier-PPP/RISS’s algorithms outperformed that of SF- and DF-code-PPP/RISS by about 35% when the satellite availability level was set to three satellites. For other satellite availability levels, the algorithms performed almost identically.

Adaptive Subcarrier Allocation for Orthogonal Frequency Code Division Multiplexing (OFCDM)

In this thesis, a novel adaptive subcarrier allocation algorithm is developed for OFCDM. This algorithm utilizes groups of evenly spaced, non-contiguous subcarriers throughout the spectrum. The users are allocated to subcarriers groups with the intention of minimizing the overall BER. This is accomplished by assigning a user to the set of subcarriers that provides the best Signal to Interfenence and Noise Ratio (SINR), while producing the least amount of interference to other users accessing the same subcarrier group. The expected interference produced by this user is then utilized to recalculate the SINR for the subcarrier goup, and the allocation process continues recursively until all users are assigned to subcarriers. The proposed alogrithm is shown to provide a performance improvement ranging from 1.5dB with 2x16 spreading, 7dB with 16x2 spreading. The algorithm is also shown to maintain or improve the BER floor for each OFCDM spreading configuration.

Adaptive Subcarrier Allocation for Orthogonal Frequency Code Division Multiplexing (OFCDM)

In this thesis, a novel adaptive subcarrier allocation algorithm is developed for OFCDM. This algorithm utilizes groups of evenly spaced, non-contiguous subcarriers throughout the spectrum. The users are allocated to subcarriers groups with the intention of minimizing the overall BER. This is accomplished by assigning a user to the set of subcarriers that provides the best Signal to Interfenence and Noise Ratio (SINR), while producing the least amount of interference to other users accessing the same subcarrier group. The expected interference produced by this user is then utilized to recalculate the SINR for the subcarrier goup, and the allocation process continues recursively until all users are assigned to subcarriers. The proposed alogrithm is shown to provide a performance improvement ranging from 1.5dB with 2x16 spreading, 7dB with 16x2 spreading. The algorithm is also shown to maintain or improve the BER floor for each OFCDM spreading configuration.