Trainable Least Squares to Reduce PAPR in OFDM-based Hybrid Beamforming Systems

In this paper, we propose a trainable least squares (LS) approach for reducing the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals in a hybrid beamforming (HBF) system. Compared to digital beamforming (DBF), in HBF technology the number of antennas exceeds the number of digital ports. Therefore, PAPR reduction capabilities are restricted by both a limited bandwidth and the reduced size of digital space. The problem is to meet both conditions. Moreover, the major HBF advantage is a reduced system complexity, thus the complexity of the PAPR reduction algorithm is expected to be low. To justify the performance of the proposed trainable LS, we provide a performance bound achieved by convex optimization using the CVX Matlab package. Moreover, the complexity of the proposed algorithm can be comparable to the minimal complexity of the digital ``twin'' calculation in HBF. The abovementioned features prove the feasibility of the trained LS for PAPR reduction in fully-connected HBF

Virtual Sectorization to Enable Hybrid Beamforming in mm-Wave mMIMO

Hybrid beamforming (HBF) is a key technology to enable mm-wave Massive multiple-input multiple-output (mMIMO) receivers for future-generation wireless communications. It combines beamforming in both analog (via phase shifters) and digital domains, resulting in low power consumption and high spectral efficiency. In practice, the problem of joint beamforming in multi-user scenarios is still open because an analog beam can't cover all users simultaneously. In this paper, we propose a hierarchical approach to divide users into clusters. Each cluster consists of users inside a virtual sector produced by the analog beamforming of an HBF-based mMIMO receiver. Thus, inside each sector, a lower-cost digital beamforming serves a limited number of users within the same cluster. Simulations with realistic non-line-of-sight scenarios generated by the QuaDRiGa 2.0 demonstrate that our methods outperform standard FFT-based alternatives and almost achieve SVD-based beamspace performance bound

Attentional bias modification in social anxiety: Effects on the N2pc component

Several meta-analyses to date have confirmed the efficacy of attentional bias modification (ABM) in shifting reaction times away from threatening stimuli, reducing anxiety symptoms, and buffering against stressor vulnerability. The reliability of reaction time differences, however, has been found to show unacceptable psychometric properties. In this study, we tested the impact of an extensive Dot-Probe ABM procedure, consisting of close to 7000 trials, concurrently with behavioral and electrophysiological measures within a large sample of over 100 highly socially anxious participants. Results indicated that the N2pc component demonstrates superior internal consistency and more statistical power in detecting attentional biases and their modification than reaction time (RT) differences. RTs were neither indicative of an attentional bias before ABM nor of a modification over time. In contrast, the N2pc indexed both an initial attentional preference for threatening stimuli and an alteration of this relationship after training. Outcomes were not specific for attentional training away from threat but also occurred in the no-contingency control procedure, casting doubt on the theoretic underpinnings of ABM. Electrophysiological measures are an important complement to the ABM literature and should be further utilized to assess attentional biases with excellent reliability

Midfrontal mechanisms of performance monitoring continuously adapt to incoming information during outcome anticipation

Performance monitoring is essential for successful action execution and previous studies have suggested that frontomedial theta (FMT) activity in scalp-recorded EEG reflects need for control signaling in response to negative outcomes. However, these studies have overlooked the fact that anticipating the most probable outcome is often possible. To optimize action execution, it is necessary for the time-critical performance monitoring system to utilize continuously updated information to adjust actions in time. This study used a combination of mobile EEG and virtual reality to investigate how the performance monitoring system adapts to continuously updated information during brief phases of outcome evaluation that follow action execution. In two virtual shooting tasks, participants were either able to observe the projectile and hence anticipate the outcome or not. We found that FMT power increased in response to missing shots in both tasks, but this effect was suppressed when participants were able to anticipate the outcome. Specifically, the suppression was linearly related to the duration of the anticipatory phase. Our results suggest that the performance monitoring system dynamically integrates incoming information to evaluate the most likely outcome of an action as quickly as possible. This dynamic mode of performance monitoring provides significant advantages over idly waiting for an action outcome before getting engaged. Early and adaptive performance monitoring not only helps prevent negative outcomes but also improves overall performance. Our findings highlight the crucial role of dynamic integration of incoming information in the performance monitoring system, providing insights for real-time decision-making and action control

Midfrontal mechanisms of performance monitoring continuously adapt to incoming information during outcome anticipation

Performance monitoring is essential for successful action execution and previous studies have suggested that frontomedial theta (FMT) activity in scalp-recorded EEG reflects need for control signaling in response to negative outcomes. However, these studies have overlooked the fact that anticipating the most probable outcome is often possible. To optimize action execution, it is necessary for the time-critical performance monitoring system to utilize continuously updated information to adjust actions in time. This study used a combination of mobile EEG and virtual reality to investigate how the performance monitoring system adapts to continuously updated information during brief phases of outcome evaluation that follow action execution. In two virtual shooting tasks, participants were either able to observe the projectile and hence anticipate the outcome or not. We found that FMT power increased in response to missing shots in both tasks, but this effect was suppressed when participants were able to anticipate the outcome. Specifically, the suppression was linearly related to the duration of the anticipatory phase. Our results suggest that the performance monitoring system dynamically integrates incoming information to evaluate the most likely outcome of an action as quickly as possible. This dynamic mode of performance monitoring provides significant advantages over idly waiting for an action outcome before getting engaged. Early and adaptive performance monitoring not only helps prevent negative outcomes but also improves overall performance. Our findings highlight the crucial role of dynamic integration of incoming information in the performance monitoring system, providing insights for real-time decision-making and action control

Stimulus complexity and the latency of the Feedback-related Negativity in the EEG

The Feedback-related Negativity is component of the event-related potential in the EEG that can be observed as a negative deflection at fronto-central electrodes 250 to 350ms following negative, compared to positive feedback stimuli (Miltner, Braun, & Coles, 1997). The component is viewed as endogen, i.e. relatively unrelated to stimulus features. However, across studies, a considerable variability especially regarding the latency of the FRN can be observed. According to a review of these studies, we hypothesize that the complexity of the stimulus modifies the latency of the FRN-effect (operationalized as a difference wave between neural responses to negative, compared to positive feedback), but not the latency of the co-occurring P2 and N2 components. Additionally, we hypothesize that the amplitude of the FRN effect, obtained in an interval around the peak latency, will be unaffected by stimulus complexity. We compare these results with an alternative indicator for feedback-related processing, i.e. power in the theta band obtained via time-frequency analysis

A neural signature of the creation of social evaluation

Photograph used for a story in the Daily Oklahoman newspaper. Caption: "Flight record book and woman's purse at crash site.

Patterns of theta oscillation reflect the neural basis of individual differences in epistemic motivation

Theta oscillations in the EEG have been shown to reflect ongoing cognitive processes related to mental effort. Here, we show that the pattern of theta oscillation in response to varying cognitive demands reflects stable individual differences in the personality trait epistemic motivation: Individuals with high levels of epistemic motivation recruit relatively more cognitive resources in response to situations possessing high, compared to low, cognitive demand; individuals with low levels do not show such a specific response. Our results provide direct evidence for the theory of the construct need for cognition and add to our understanding of the neural processes underlying theta oscillations. More generally, we provide an explanation how individual differences in personality traits might be represented on a neural level

The reality of virtual reality

Virtual reality (VR) has become a popular tool for investigating human behavior and brain functions. Nevertheless, it is unclear whether VR constitutes an actual form of reality or is more like an advanced simulation. Determining the nature of VR has been mostly achieved by self-reported presence measurements, defined as the feeling of being submerged in the experience. However, subjective measurements might be prone to bias and, most importantly, do not allow for a comparison with real-life experiences. Here, we show that real-life and VR height exposures using 3D-360° videos are mostly indistinguishable on a psychophysiological level (EEG and HRV), while both differ from a conventional 2D laboratory setting. Using a fire truck, three groups of participants experienced a real-life (N = 25), a virtual (N = 24), or a 2D laboratory (N = 25) height exposure. Behavioral and psychophysiological results suggest that identical exogenous and endogenous cognitive as well as emotional mechanisms are deployed to process the real-life and virtual experience. Specifically, alpha- and theta-band oscillations in line with heart rate variability, indexing vigilance, and anxiety were barely indistinguishable between those two conditions, while they differed significantly from the laboratory setup. Sensory processing, as reflected by beta-band oscillations, exhibits a different pattern for all conditions, indicating further room for improving VR on a haptic level. In conclusion, the study shows that contemporary photorealistic VR setups are technologically capable of mimicking reality, thus paving the way for the investigation of real-world cognitive and emotional processes under controlled laboratory conditions. For a video summary, see https://youtu.be/fPIrIajpfiA