Cooperative Transmission for Downlink Distributed Antenna in Time Division Duplex System

Multi-user distributed antenna system (MU-DAS) systems play the essential role in improving throughput performance in wireless communications. This improvement can be achieved by exploiting the spatial domain and without the need of additional power and bandwidth. In this thesis, three main issues which are of importance to the data rate transmission have been investigated. Firstly, user clustering in MU-DAS downlink systems has been considered, where this technique can be effciently used to reduce the complexity and cost caused by radio frequency chains, associated with antennas while keeping most of the diversity advantages of the system. The proposed user clustering algorithm which can select an optimal set of antennas for transmission. The capacity achieved by the proposed algorithm is almost same as the capacity of the optimum search method, with much lower complexity. Secondly, interference alignment in MU-DAS downlink systems has been studied. The inter-cluster interference is uncoordinated and limits the system performance. The inter-cluster interference should be eliminated or minimized carefully. The interference alignment is proposed to consolidate the strong inter-cluster interference into smaller dimensions of signal space at each user and use the remaining dimensions to transmit the desired signals without any interference. The performance of single cluster is better than the proposed algorithm due to the absence of intercluster interference in the single cluster. The numerical shows that the proposed algorithm is more suitable in multi-cell DAS environment due to the presence of inter-cell interference. Finally, the impact of different user mobility on TDD downlink MUDAS has been studied. The downlink data transmission in time division duplex (TDD) systems is optimized according to the channel state information (CSI) which is obtained at the uplink time slot. However, the actual channel at downlink time slot may be different from the estimated channel due to channel variation in mobility environment. Based on mobility state information (MSI), an autocorrelation based feedback interval adjustment technique is proposed. The proposed technique adjusts the CSI update interval and mitigates the performance degradation imposed by the user mobility and the transmission delay. Cooperative clusters are formed to maximize sum rate. In order to reduce the computational complexity, a channel gain based antenna selection and signal-to-interference plus noise ratio (SINR) based user clustering are developed. A downlink ergodic capacity is derived in single user clustering. The derived analytical expressions of the downlink ergodic capacity are verified by system simulations. Numerical results show that the proposed scheme can improved sum rate over the non cooperative system and no MSI knowledge. The proposed technique has good performance for a wide range of user speed and suitable for future wireless communications systems

Removing knotted or stuck epidural catheters: a systematic review of case reports

Background The knotting or in vivo entrapment of epidural catheters is an uncommon but challenging issue for anesthesiologists. This study aimed to identify the possible causes behind entrapped epidural catheters and the effective methods for their removal. Methods A systematic review of relevant case reports and series was conducted using the patient/population, intervention, comparison and outcome framework and keywords such as “epidural,” “catheter,” “knotting,” “stuck,” “entrapped,” and “entrapment.” The Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement was followed, and the review protocol was registered with International Prospective Register for Systematic Reviews (CRD42021291266). Results The analysis included 59 cases with a mean depth of catheter insertion from the skin of 11.825 cm and an average duration of 8.17 h for the detection of non-functioning catheters. In 27 cases (45.8%), a radiological knot was found, with an average length of 2.59 cm from the tip. The chi-squared test revealed a significant difference between the initial and final positions of catheter insertion (P = 0.049). Conclusions Deep insertion was the primary cause of epidural catheter entrapment. To remove the entrapped catheters, the lateral decubitus position should be attempted first, followed by the position used during insertion. Based on these findings, recommendations for the prevention and removal of entrapped catheters have been formulated

Cooperative Transmission Strategy Over Users’ Mobility for Downlink Distributed Antenna Systems

Previously, a scheme in [1] is proposed for the outdated channel state information (CSI) problem, for data transmission in time division duplex (TDD) systems. In user movement environment, the actual channel of data transmission at downlink time slot is different from the estimated channel due to channel variation. In this paper the effect of different user mobility on TDD downlink multiuser distributed antenna system is investigated. An efficient autocorrelation based feedback interval technique is proposed and updates CSI at less cost of the downlink time slots. In the proposed technique, the frequency of CSI feedback for different users is proportional to their speed. Cooperative clusters are formed to maximize sum rate where channel gain based antenna selection and user clustering based on SINR threshold is applied to reduce computational complexity. Numerical results show that sum rate superiority of the proposed scheme over the user mobility

Multiphase flow estimation using accelerometers, ultrasonic sensors, and machine learning

The new sensors, accelerometers, and ultrasonic sensors were installed in the existing multimodal sensor suite used in the multiphase flow in the process hall in Campus Porsgrunn of USN. Multiphase flow experiments were conducted, and measurements were recorded using different data acquisition systems. The collected measurements were preprocessed and analyzed to extract the useful features from the raw signals. To classify the flow regimes, the Classification Learner application was used, and the results from different models were compared based on their accuracies. The feature selection technique was implemented to evaluate the importance of each feature. Then, the models were trained with the new features. As a result, the accuracy of the Ensemble model with Bagged Trees was increased from 94.2 to 97.1%. The Random Forest and Decision Trees techniques were also implemented to classify the flow regimes. The flow rates of oil, water, and gas were successfully predicted using the Regression Learner tool. However, the measurements from ultrasonic sensors were not satisfactory due to technical problems related to wedge. In this case, the new wedge was designed and manufactured for the experiment but was unable to implement and collect measurements for this work due to time constraints

Strain Monitoring of Wind Turbines Using a Semi-Autonomous Drone

In this work, an approach is proposed that can perform a nondestructive evaluation of wind turbine structures using a non-contact, three-dimensional full-field optical digital image correlation (DIC) technique. This approach can quantify the level of strain and loading conditions that rotating structures such as wind turbines experience during operation. The optical technique does not interfere with the structural functionality of the wind turbine. Moreover, the use of Unmanned Aerial Vehicles (UAVs) for remote inspection enables robust measurements for periodic inspection. The strain obtained using the proposed approach is validated using strain gauges mounted on the blades. A control algorithm is designed for the UAV to stabilized and obtain the desired field of interest and working distance based on the turbine size. Blending the benefits of the remote accessibility of UAVs and full-field dynamic evaluation of structures using strain data obtained with DIC is a novel method of monitoring wind turbines

Non-contact Vibration Monitoring of Rotating Wind Turbines Using a Semi-autonomous UAV

With the recent demands for more efficient clean renewable energy sources, wind turbines are designed that have large rotor blade diameters. These large-sized wind turbines need to be periodically monitored to prevent catastrophic failures. This paper aims to develop a practice for obtaining the vibration characteristics of wind turbine blades that can be eventually used for structural health monitoring of these structures. This monitoring technique needs to be robust and non-contact to prevent any interference with the operation of the wind turbine. In this work, a digital image correlation (DIC) system installed on a drone is used as a sensing technique to obtain the dynamic characteristics of rotating wind turbine blades. The DIC uses a stereo-camera system to record the deflections of the blades and provides non-contact measurements. The unmanned aerial vehicle (UAV) enables on-site robust measurements. Furthermore, a dynamic stitching technique is used after DIC measurement to obtain vibration characteristics of the entire blade with high accuracy. The proposed health monitoring technique can be used by engineers for remote structural health monitoring of wind turbines during operation in both offshore and inland wind farms

Cooperative transmission strategy for downlink distributed antenna systems over time-varying channel

The channel state information (CSI) is used to optimise data transmission in time division duplex (TDD) systems, which is obtained at the time of channel estimation. The actual channel of data transmission at downlink time slot is different from the estimated channel due to channel variation in user movement environment. In this paper the impact of different user mobility on TDD downlink multiuser distributed antenna system is investigated. Based on mobility state information (MSI), an autocorrelation based feedback interval technique is proposed and updates CSI and mitigate the performance degradation imposed by the user speed and transmission delay. Cooperative clusters are formed to maximize sum rate and a channel gain based antenna selection and user clustering based on SINR threshold is applied to reduce computational complexity. Numerical results show that the proposed scheme can provide improved sum rate over the non cooperative system and no MSI knowledge. The proposed technique has good performance for wide range of speed and suitable for future wireless communication systems

Neostigmine and atropine as a treatment for postdural puncture headache after spinal anesthesia in cesarean section: A case report

Key Clinical message Neostigmine and atropine offer a promising treatment option for postdural puncture headache (PDPH) following spinal anesthesia in cesarean section, providing effective relief with a favorable risk–benefit profile. Abstract Postdural puncture headache (PDPH) is a common consequence of cesarean section surgeries after spinal anesthesia. This case study describes the successful treatment of PDPH with intravenous neostigmine and atropine. A 31 years female who underwent elective cesarean section with spinal anesthesia developed a severe headache on the 6th postoperative day and was diagnosed to have PDPH. PDPH failed to respond to conventional treatment modalities like hydration, a Non‐steroidal anti‐inflammatory drug, and sphenopalatine ganglion block. Epidural blood patch could not be performed due to lack of consent. A trial dose of intravenous neostigmine (20 mcg/kg) along with atropine (10 mcg/kg) successfully provided symptomatic and clinical relief. The combination of neostigmine and atropine demonstrates a rapid onset of action, providing patients with effective analgesia while avoiding the need for invasive procedures such as epidural blood patches and offers quicker pain relief. This promising result warrants additional research