Digital Radio Encoding and Power Amplifier Design for Multimode and Multiband Wireless Communications

The evolution of wireless technology has necessitated the support of multiple communication standards by mobile devices. At present, multiple chipsets/radios operating at predefined sets of modulation schemes, frequency bands, bandwidths and output power levels are used to achieve this objective. This leads to higher component counts, increased cost and limits the capacity to cope with future communication standards. In order to tackle different wireless standards using a single chipset, digital circuits have been increasingly deployed in radios and demonstrated re-configurability in different modulation schemes (multimode) and frequency bands (multiband). Despite efforts and progress made in digitizing the entire radio, the power amplifier (PA) is still designed using an conventional approach and has become the bottleneck in digital transmitters, in terms of low average power efficiency, poor compatibility with modern CMOS technology and limited re-configurability. This research addresses these issues from two aspects. The first half of the thesis investigates signal encoding issues between the modulator and PA. We propose, analyze and evaluate a new hybrid amplitude/time signal encoding scheme that significantly improves the coding efficiency and dynamic range of a digitally modulated power amplifier (DMPA) without significantly increasing design complexity. The proposed hybrid amplitude/time encoding scheme combines both the amplitude domain and the time domain to optimally encode information. Experimental results show that hybrid amplitude/time encoding results in a 35% increase in the average coding efficiency with respect to conventional time encoding, and is only 6.7% lower than peak efficiency when applied to a Wireless Local Area Network (WLAN) signal with a peak to average power ratio equal to 9.9 dB. A new DMPA architecture, based on the proposed hybrid encoding, is also proposed. The second half of this thesis presents the design, analysis and implementation of a CMOS PA that is amenable to the proposed hybrid encoding scheme. A multi-way current mode class-D PA architecture has been proposed and realized in 130 nm CMOS technology. The designed PA has satisfied the objectives of wide bandwidth (1.5 GHz - 2.7 GHz at 1 dB output power), and high efficiency (PAE 63%) in addition to demonstrating linear responses using the proposed digital encoding. A complete digital transmitter combining the encoder and the multi-way PA was also investigated. The overall efficiency is 27% modulating 7.3 dB peak to average power ratio QAM signals

Stiffness of a new unilateral external fixator – a biomechanical study

Unilateral external fixator is commonly used to stabilize initial fractured bone for polytraumatised patients, which is simple and effective method. The stiffness property of the external fixator has a great influence on the local biomechanical environment of bone tissue. In order to investigate the rigidity characteristics of a novel fixator with serrated structure through comparing the stiffness of the Sarafix fixator and the novel fixator in experimental measurement. Polyacetal tubes simulating human tibia were fixed in novel fixator. Axial stiffness, torsional stiffness and bending stiffness of novel fixator were measured through universal material testing machine. In order to improve reliability, corresponding test must be repeated ten times. Due to the improvement of novel fixator’s structural, which has serrated connection between fixator joints, the performance of the novel fixator is better than Sarafix fixator under bending and torsional loads, there is no big difference in axial load for two fixators. The novel fixator has good stiffness properties, the novel fixator with serrated structure plays an important role to improve the stiffness of the novel fixator system. These analysis results can also aid the performance assessment of an novel external fixator and facilitate appropriate application of such a device

Supply Chain Joint Inventory Management and Cost Optimization Based on Ant Colony Algorithm and Fuzzy Model

With the advancement of the marketization process, inventory management has transformed from a single backup protection function to an essential function for enterprises, which helps to survive and develop. Inventory control in supply chain management is the important content of supply chain management. The new management mode makes inventory management present many new characteristics and problems compared with traditional inventory management. From the view of system theory and integration theory, it is imperative to re-examine the problem of inventory control, put forward new inventory management strategies adapted to integrated supply chain management, and improve the integration of the whole supply chain, which can enhance the agility and market response speed of enterprises. Based on the in-depth study of the joint inventory management model, this paper analyzed the current situation of the joint inventory management to optimize the inventory. In view of the achievements and shortcomings of the current research, a more systematic and improved optimization model of the supply chain inventory was proposed by using the basic ideas of ant colony algorithm and fuzzy model

INFLUENCES ANALYSIS OF CONFIGURATIONS ON THE PERFORMANCE OF PARALLEL TYPE SIX-AXIS ACCELEROMETERS

The development of parallel type six-axis accelerometers was hindered for their complicated forward kinematics and dynamics algorithms which make it difficult to decouple the six acceleration components timely, accurately and stably. This paper applies four parallel configurations with 6-DOF and a closed-form solution of the forward kinematics to six-axis accelerometers as the elastic bodies, where the piezoelectric ceramics act as the sensitive elements and play the role of prismatic pairs. An efficient decoupling algorithm was derived to calculate the six acceleration components completely by the use of Kane’s dynamics method in configuration space. Considering the differences in sensing properties of the four six-axis accelerometers, a quantitative comparison was conducted to reveal the configurations’ direct influences on some static characteristics, including accuracy, efficiency, sensitivity, isotropy, and working frequency range, which makes a theoretical foundation for the subsequent design of a reconfigurable prototype

INFLUENCES ANALYSIS OF CONFIGURATIONS ON THE PERFORMANCE OF PARALLEL TYPE SIX-AXIS ACCELEROMETERS

The development of parallel type six-axis accelerometers was hindered for their complicated forward kinematics and dynamics algorithms which make it difficult to decouple the six acceleration components timely, accurately and stably. This paper applies four parallel configurations with 6-DOF and a closed-form solution of the forward kinematics to six-axis accelerometers as the elastic bodies, where the piezoelectric ceramics act as the sensitive elements and play the role of prismatic pairs. An efficient decoupling algorithm was derived to calculate the six acceleration components completely by the use of Kane’s dynamics method in configuration space. Considering the differences in sensing properties of the four six-axis accelerometers, a quantitative comparison was conducted to reveal the configurations’ direct influences on some static characteristics, including accuracy, efficiency, sensitivity, isotropy, and working frequency range, which makes a theoretical foundation for the subsequent design of a reconfigurable prototype

ImageNetVC: Zero-Shot Visual Commonsense Evaluation on 1000 ImageNet Categories

Recently, Pretrained Language Models (PLMs) have been serving as general-purpose interfaces, posing a significant demand for comprehensive visual knowledge. However, it remains unclear how well current PLMs and their visually augmented counterparts (VaLMs) can master visual commonsense knowledge. To investigate this, we propose ImageNetVC, a fine-grained, human-annotated dataset specifically designed for zero-shot visual commonsense evaluation across 1,000 ImageNet categories. Utilizing ImageNetVC, we delve into the fundamental visual commonsense knowledge of both unimodal PLMs and VaLMs, uncovering the scaling law and the influence of the backbone model on VaLMs. Furthermore, we investigate the factors affecting the visual commonsense knowledge of large-scale models, providing insights into the development of language models enriched with visual commonsense knowledge. Our code and dataset are available at https://github.com/hemingkx/ImageNetVC