Codebook Based Hybrid Precoding for Millimeter Wave Multiuser Systems

In millimeter wave (mmWave) systems, antenna architecture limitations make it difficult to apply conventional fully digital precoding techniques but call for low cost analog radio-frequency (RF) and digital baseband hybrid precoding methods. This paper investigates joint RF-baseband hybrid precoding for the downlink of multiuser multi-antenna mmWave systems with a limited number of RF chains. Two performance measures, maximizing the spectral efficiency and the energy efficiency of the system, are considered. We propose a codebook based RF precoding design and obtain the channel state information via a beam sweep procedure. Via the codebook based design, the original system is transformed into a virtual multiuser downlink system with the RF chain constraint. Consequently, we are able to simplify the complicated hybrid precoding optimization problems to joint codeword selection and precoder design (JWSPD) problems. Then, we propose efficient methods to address the JWSPD problems and jointly optimize the RF and baseband precoders under the two performance measures. Finally, extensive numerical results are provided to validate the effectiveness of the proposed hybrid precoders.Comment: 35 pages, 9 figures, to appear in Trans. on Signal Process, 201

Extremely preterm infants born outside a provincial tertiary perinatal center and transferred postnatally associated with poor outcomes: a real-world observational study

IntroductionExtremely preterm infants (EPIs) have high morbidity and mortality, and are recommended to be born in a tertiary perinatal center (inborn). However, many EPIs in central China are born in lower-level hospitals and transferred postnatally, the outcomes of which remain to be investigated.MethodsEPIs admitted to the Department of Neonatology, Maternal and Child Health Hospital of Hubei Province from January 2013 to December 2022 were retrospectively recruited and divided into the control (inborn) and transfer groups (born in other hospitals). The neonatal and maternal characteristics, neonatal outcomes, and the treatment of survival EPIs were analyzed.ResultsA total of 174 and 109 EPIs were recruited in the control and transfer groups, respectively. EPIs in the transfer group have a higher birth weight and a lower proportion of multiple pregnancies than the control group (all P < 0.05). The proportions of antenatal steroids, magnesium sulfate, cesarean delivery, premature rupture of membranes ≥18 h, gestational diabetes, and amniotic fluid abnormalities were lower in the transfer group (all P < 0.05). Survival rates (64.22% vs. 56.32%), proportions of severe periventricular-intraventricular hemorrhage (PIVH) (11.93% vs. 11.49%), severe bronchopulmonary dysplasia (sBPD) (21.05% vs. 20%), and severe retinopathy of prematurity (ROP) (24.77% vs. 20.11%) were similar in the transfer and control groups (all P > 0.05). However, the transfer group had higher proportions of severe birth asphyxia (34.86% vs. 13.22%, P < 0.001), PIVH (42.20% vs. 29.89%, P = 0.034), and extrauterine growth retardation (EUGR) (17.43% vs. 6.32%, P = 0.003). Less surfactant utilization was found in the transfer group among survival EPIs (70.00% vs. 93.88%, P < 0.001).ConclusionEPIs born outside a tertiary perinatal center and transferred postnatally did not have significantly higher mortality and rates of severe complications (severe PIVH, severe ROP, and sBPD), but there may be an increased risk of severe asphyxia, PIVH and EUGR. This may be due to differences in maternal and neonatal characteristics and management. Further follow-up is needed to compare neurodevelopmental outcomes, and it is recommended to transfer the EPIs in utero to reduce the risk of poor physical and neurological development

An NLoS-based Enhanced Sensing Method for MmWave Communication System

The millimeter-wave (mmWave)-based Wi-Fi sensing technology has recently attracted extensive attention since it provides a possibility to realize higher sensing accuracy. However, current works mainly concentrate on sensing scenarios where the line-of-sight (LoS) path exists, which significantly limits their applications. To address the problem, we propose an enhanced mmWave sensing algorithm in the 3D non-line-of-sight environment (mm3NLoS), aiming to sense the direction and distance of the target when the LoS path is weak or blocked. Specifically, we first adopt the directional beam to estimate the azimuth/elevation angle of arrival (AoA) and angle of departure (AoD) of the reflection path. Then, the distance of the related path is measured by the fine timing measurement protocol. Finally, we transform the AoA and AoD of the multiple non-line-of-sight (NLoS) paths into the direction vector and then obtain the information of targets based on the geometric relationship. The simulation results demonstrate that mm3NLoS can achieve a centimeter-level error with a 2m spacing. Compared to the prior work, it can significantly reduce the performance degradation under the NLoS condition

Joint Design of Access and Backhaul in Densely Deployed MmWave Small Cells

With the rapid growth of mobile data traffic, the shortage of radio spectrum resource has become increasingly prominent. Millimeter wave (mmWave) small cells can be densely deployed in macro cells to improve network capacity and spectrum utilization. Such a network architecture is referred to as mmWave heterogeneous cellular networks (HetNets). Compared with the traditional wired backhaul, The integrated access and backhaul (IAB) architecture with wireless backhaul is more flexible and cost-effective for mmWave HetNets. However, the imbalance of throughput between the access and backhaul links will constrain the total system throughput. Consequently, it is necessary to jointly design of radio access and backhaul link. In this paper, we study the joint optimization of user association and backhaul resource allocation in mmWave HetNets, where different mmWave bands are adopted by the access and backhaul links. Considering the non-convex and combinatorial characteristics of the optimization problem and the dynamic nature of the mmWave link, we propose a multi-agent deep reinforcement learning (MADRL) based scheme to maximize the long-term total link throughput of the network. The simulation results show that the scheme can not only adjust user association and backhaul resource allocation strategy according to the dynamics in the access link state, but also effectively improve the link throughput under different system configurations.Comment: 15 page