996 resultados para Optimum Frequency


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This paper investigates the feasibility of using an energy harvesting device tuned such that its natural frequency coincides with higher harmonics of the input to capture energy from walking or running human motion more efficiently. The paper starts by reviewing the concept of a linear resonant generator for a tonal frequency input and then derives an expression for the power harvested for an input with several harmonics. The amount of power harvested is estimated numerically using measured data from human subjects. Assuming that the input is periodic, the signal is reconstructed using a Fourier series before being used in the simulation. It is found that although the power output depends on the input frequency, the choice of tuning the natural frequency of the device to coincide with a particular higher harmonic is restricted by the amount of damping that is needed to maximize the amount of power harvested, as well as to comply with the size limit of the device. It is also found that it is not feasible to tune the device to match the first few harmonics when the size of the device is small, because a large amount of damping is required to limit the motion of the mass.

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Multi-input multi-output (MIMO) technology is an emerging solution for high data rate wireless communications. We develop soft-decision based equalization techniques for frequency selective MIMO channels in the quest for low-complexity equalizers with BER performance competitive to that of ML sequence detection. We first propose soft decision equalization (SDE), and demonstrate that decision feedback equalization (DFE) based on soft-decisions, expressed via the posterior probabilities associated with feedback symbols, is able to outperform hard-decision DFE, with a low computational cost that is polynomial in the number of symbols to be recovered, and linear in the signal constellation size. Building upon the probabilistic data association (PDA) multiuser detector, we present two new MIMO equalization solutions to handle the distinctive channel memory. With their low complexity, simple implementations, and impressive near-optimum performance offered by iterative soft-decision processing, the proposed SDE methods are attractive candidates to deliver efficient reception solutions to practical high-capacity MIMO systems. Motivated by the need for low-complexity receiver processing, we further present an alternative low-complexity soft-decision equalization approach for frequency selective MIMO communication systems. With the help of iterative processing, two detection and estimation schemes based on second-order statistics are harmoniously put together to yield a two-part receiver structure: local multiuser detection (MUD) using soft-decision Probabilistic Data Association (PDA) detection, and dynamic noise-interference tracking using Kalman filtering. The proposed Kalman-PDA detector performs local MUD within a sub-block of the received data instead of over the entire data set, to reduce the computational load. At the same time, all the inter-ference affecting the local sub-block, including both multiple access and inter-symbol interference, is properly modeled as the state vector of a linear system, and dynamically tracked by Kalman filtering. Two types of Kalman filters are designed, both of which are able to track an finite impulse response (FIR) MIMO channel of any memory length. The overall algorithms enjoy low complexity that is only polynomial in the number of information-bearing bits to be detected, regardless of the data block size. Furthermore, we introduce two optional performance-enhancing techniques: cross- layer automatic repeat request (ARQ) for uncoded systems and code-aided method for coded systems. We take Kalman-PDA as an example, and show via simulations that both techniques can render error performance that is better than Kalman-PDA alone and competitive to sphere decoding. At last, we consider the case that channel state information (CSI) is not perfectly known to the receiver, and present an iterative channel estimation algorithm. Simulations show that the performance of SDE with channel estimation approaches that of SDE with perfect CSI.

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Warehouse is an essential component in the supply chain, linking the chain partners and providing them with functions of product storage, inbound and outbound operations along with value-added processes. Allocation of warehouse resources should be efficient and effective to achieve optimum productivity and reduce operational costs. Radio frequency identification (RFID) is a technology capable of providing real-time information about supply chain operations. It has been used by warehousing and logistic enterprises to achieve reduced shrinkage, improved material handling and tracking as well as increased accuracy of data collection. However, both academics and practitioners express concerns about challenges to RFID adoption in the supply chain. This paper provides a comprehensive analysis of the problems encountered in RFID implementation at warehouses, discussing the theoretical and practical adoption barriers and causes of not achieving full potential of the technology. Lack of foreseeable return on investment (ROI) and high costs are the most commonly reported obstacles. Variety of standards and radio wave frequencies are identified as source of concern for decision makers. Inaccurate performance of the RFID within the warehouse environment is examined. Description of integration challenges between warehouse management system and RFID technology is given. The paper discusses the existing solutions to technological, investment and performance RFID adoption barriers. Factors to consider when implementing the RFID technology are given to help alleviate implementation problems. By illustrating the challenges of RFID in the warehouse environment and discussing possible solutions the paper aims to help both academics and practitioners to focus on key areas constituting an obstacle to the technology growth. As more studies will address these challenges, the realisation of RFID benefits for warehouses and supply chain will become a reality.

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This paper develops a theoretical analysis of the tradeoff between carrier suppression and nonlinearities induced by optical IQ modulators in direct-detection subcarrier multiplexing systems. The tradeoff is obtained by examining the influence of the bias conditions of the modulator on the transmitted single side band signal. The frequency components in the electric field and the associated photocurrent at the output of the IQ modulator are derived mathematically. For any frequency plan, the optimum bias point can be identified by calculating the sensitivity gain for every subchannel. A setup composed of subcarriers located at multiples of the data rate ensures that the effects of intermodulation distortion are studied in the most suitable conditions. Experimental tests with up to five QPSK electrical subchannels are performed to verify the mathematical model and validate the predicted gains in sensitivity.

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Competing approaches exist, which allow control of phase noise and frequency tuning in mode-locked lasers, but no judgement of pros and cons based on a comparative analysis was presented yet. Here, we compare results of hybrid mode-locking, hybrid mode-locking with optical injection seeding, and sideband optical injection seeding performed on the same quantum dot laser under identical bias conditions. We achieved the lowest integrated jitter of 121 fs and a record large radio-frequency (RF) tuning range of 342 MHz with sideband injection seeding of the passively mode-locked laser. The combination of hybrid mode-locking together with optical injection-locking resulted in 240 fs integrated jitter and a RF tuning range of 167 MHz. Using conventional hybrid mode-locking, the integrated jitter and the RF tuning range were 620 fs and 10 MHz, respectively. © 2014 AIP Publishing LLC.