Sparse Array Enabled Near-Field Communications: Beam Pattern Analysis and Hybrid Beamforming Design

Extremely large-scale array (XL-array) has emerged as a promising technology to enable near-field communications for achieving enhanced spectrum efficiency and spatial resolution, by drastically increasing the number of antennas. However, this also inevitably incurs higher hardware and energy cost, which may not be affordable in future wireless systems. To address this issue, we propose in this paper to exploit two types of sparse arrays (SAs) for enabling near-field communications. Specifically, we first consider the linear sparse array (LSA) and characterize its near-field beam pattern. It is shown that despite the achieved beam-focusing gain, the LSA introduces several undesired grating-lobes, which have comparable beam power with the main-lobe and are focused on specific regions. An efficient hybrid beamforming design is then proposed for the LSA to deal with the potential strong inter-user interference (IUI). Next, we consider another form of SA, called extended coprime array (ECA), which is composed of two LSA subarrays with different (coprime) inter-antenna spacing. By characterizing the ECA near-field beam pattern, we show that compared with the LSA with the same array sparsity, the ECA can greatly suppress the beam power of near-field grating-lobes thanks to the offset effect of the two subarrays, albeit with a larger number of grating-lobes. This thus motivates us to propose a customized two-phase hybrid beamforming design for the ECA. Finally, numerical results are presented to demonstrate the rate performance gain of the proposed two SAs over the conventional uniform linear array (ULA).Comment: In this paper, we propose to exploit sparse arrays for enabling near-field communications and characterize its unique beam pattern for facilitating its hybrid beamforming desig

Behavioral Framework of Asset Price Bubbles: Theoretical and Empirical Analyses

Sentiment and extrapolation are ubiquitous in the financial market, and they are not only the embodiment of human nature, but also the primary drivers of asset price bubbles. In this study, we first constructed a theoretical model that included fundamental traders and extrapolated investors, and we assessed the time series characteristics of asset prices under different types of information shocks. According to the research results, good news about the fundamentals can lead to positive asset price bubbles, and correspondingly, bad news can lead to negative asset price bubbles; however, the decrease in asset prices in the case of negative bubbles is not as substantial as the increase in prices in the case of positive bubbles, and the time for prices to reverse is also long, which can be explained by the short-selling constraints. According to the comparative static analysis, the scales of the positive and negative foams depend on the proportion of investors in the market and the extrapolation coefficient. We verified the conclusion of the theoretical model from two aspects: (1) we analyzed the relationship between investor sentiment and the prevalence of informed trading, and according to the results, the increase (decrease) in investor sentiment can reduce the information content of asset prices and increase price volatility; however, the impact of low sentiment is not substantial, which preliminarily tests the conclusion of the theoretical model; (2) we examined the relationship between the cumulative change in investor sentiment and future portfolio returns, and we found that the cumulative increase in investor sentiment can have a positive impact on future portfolio returns at the initial stage, and depress future portfolio returns in the long term, which forms positive asset price bubbles. The cumulative depression of investor sentiment can depress the future portfolio returns at the initial stage, and positively influence the future portfolio returns in the long term, which forms negative asset price bubbles. Moreover, these two nonlinear relationships exhibit cross-sectional differences in different types of asset portfolios, which further validates the key proposition of the theoretical model

Noise Trader Risk and Wealth Effect: A Theoretical Framework

This paper discusses the impact of noise trader risk on total consumption and investor consumption. The model predicts that: (1) If noise traders show optimistic beliefs, they will have a restraining effect on the total consumption when the noise trading intensity is high enough, they will expand consumption at t = 1 and reduce consumption at t = 2, and rational investors will reduce consumption at t = 1 and expand consumption at t = 2; (2) if the beliefs of noise traders do not show bias, the consumption of rational investors is always higher than that of noise traders and exceeds the market benchmark; (3) the relative consumption of rational investors and noise traders depends on the risk, risk aversion, fundamental risk and market ratio of noise traders; (4) based on the reasonable range of noise traders’ beliefs, the lifetime consumption of noise traders will be higher than that of rational investors and the market, and the excess consumption will change with a series of parameters

Noise Trader Risk and Wealth Effect: A Theoretical Framework

This paper discusses the impact of noise trader risk on total consumption and investor consumption. The model predicts that: (1) If noise traders show optimistic beliefs, they will have a restraining effect on the total consumption when the noise trading intensity is high enough, they will expand consumption at t = 1 and reduce consumption at t = 2, and rational investors will reduce consumption at t = 1 and expand consumption at t = 2; (2) if the beliefs of noise traders do not show bias, the consumption of rational investors is always higher than that of noise traders and exceeds the market benchmark; (3) the relative consumption of rational investors and noise traders depends on the risk, risk aversion, fundamental risk and market ratio of noise traders; (4) based on the reasonable range of noise traders’ beliefs, the lifetime consumption of noise traders will be higher than that of rational investors and the market, and the excess consumption will change with a series of parameters

Renin-angiotensin system inhibitors mitigate radiation pneumonitis by activating ACE2-angiotensin-(1–7) axis via NF-κB/MAPK pathway

Abstract Radiation pneumonitis (RP) affects both patients and physicians during radiation therapy for lung cancer. To date, there are no effective drugs for improving the clinical outcomes of RP. The activation of angiotensin-converting enzyme 2 (ACE2) improves experimental acute lung injury caused by severe acute respiratory syndrome coronavirus, acid inhalation, and sepsis. However, the effects and underlying mechanisms of ACE2 in RP remain unclear. Therefore, this study aimed to investigate the effects of angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers on RP and ACE2/angiotensin-(1–7)/Mas receptor pathway activation. We found that radiotherapy decreased the expression of ACE2 and that overexpression of ACE2 alleviated lung injury in an RP mouse model. Moreover, captopril and valsartan restored ACE2 activation; attenuated P38, ERK, and p65 phosphorylation; and effectively mitigated RP in the mouse model. Further systematic retrospective analysis illustrated that the incidence of RP in patients using renin-angiotensin system inhibitors (RASis) was lower than that in patients not using RASis (18.2% vs. 35.8% at 3 months, p = 0.0497). In conclusion, the current findings demonstrate that ACE2 plays a critical role in RP and suggest that RASis may be useful potential therapeutic drugs for RP