Numerical Simulation of the Deformation of Some MEMS

In this paper we present the numerical simulation of the deformation of two Micro-Electromechanical Systems (MEMS), a trampoline-type one i.e. a rectangular cantilever beam and an accelerometer that consists of a square plate with all edges simply supported. The deformation of these systems is modeled by fourth-order differential equations, ordinary and partial respectively. We find the approximate solutions by using the finite differences method programmed in Matlab, solving the system of linear equations associated with different methods to evaluate the efficiency of these. We obtained very good approximations with small errors compared to other articles that use other approaches

EXIT-chart aided quantum code design improves the normalised throughput of realistic quantum devices

In this contribution, the Hashing bound of Entanglement Assisted Quantum Channels (EAQC) is investigated in the context of quantum devices built from a range of popular materials, such as trapped ion and relying on solid state Nuclear Magnetic Resonance (NMR), which can be modelled as a so-called asymmetric channel. Then, Quantum Error Correction Codes (QECC) are designed based on Extrinsic Information Transfer (EXIT) charts for improving performance when employing these quantum devices. The results are also verified by simulations. Our QECC schemes are capable of operating close to the corresponding Hashing bound

Quantum-aided multi-user transmission in non-orthogonal multiple access systems

With the research on implementing a universal quantum computer being under the technological spotlight, new possibilities appear for their employment in wireless communications systems for reducing their complexity and improving their performance. In this treatise, we consider the downlink of a rank-deficient, multi-user system and we propose the discrete-valued and continuous-valued Quantum-assisted Particle Swarm Optimization (QPSO) algorithms for performing Vector Perturbation (VP) precoding, as well as for lowering the required transmission power at the Base Station (BS), while minimizing the expected average Bit Error Ratio (BER) at the mobile terminals. We use the Minimum BER (MBER) criterion. We show that the novel quantum-assisted precoding methodology results in an enhanced BER performance, when compared to that of a classical methodology employing the PSO algorithm, while requiring the same computational complexity in the challenging rank-deficient scenarios, where the number of transmit antenna elements at the BS is lower than the number of users. Moreover, when there is limited Channel State Information (CSI) feedback from the users to the BS, due to the necessary quantization of the channel states, the proposed quantum-assisted precoder outperforms the classical precoder

Serially concatenated unity-rate codes improve quantum codes without coding-rate reduction

Inspired by the astounding performance of the unity rate code (URC) aided classical coding and detection schemes, we conceive a quantum URC (QURC) for assisting the design of concatenated quantum codes. Unfortunately, a QURC cannot be simultaneously recursive as well as non-catastrophic. However, we demonstrate that, despite being non-recursive, our proposed QURC yields efficient concatenated codes, which exhibit a low error rate and a beneficial interleaver gain, provided that the coding scheme is carefully designed with the aid of EXtrinsic Information Transfer (EXIT) charts

Seasonal time-series imputation of gap missing algorithm (STIGMA)

summary:This work presents a new approach for the imputation of missing data in weather time-series from a seasonal pattern; the seasonal time-series imputation of gap missing algorithm (STIGMA). The algorithm takes advantage from a seasonal pattern for the imputation of unknown data by averaging available data. We test the algorithm using data measured every $10$ minutes over a period of $365$ days during the year 2010; the variables include global irradiance, diffuse irradiance, ultraviolet irradiance, and temperature, arranged in a matrix of dimensions $52,560$ rows for data points over time and $4$ columns for weather variables. The particularity of this work is that the algorithm is well-suited for the imputation of values when the missing data are presented continuously and in seasonal patterns. The algorithm employs a date-time index to collect available data for the imputation of missing data, repeating the process until all missing values are calculated. The tests are performed by removing $5\%$, $10\%$, $15\%$, $20\%$, $25\%$, and $30\%$ of the available data, and the results are compared to autoregressive models. The proposed algorithm has been successfully tested with a maximum of $2,736$ contiguous missing values that account for $19$ consecutive days of a single month; this dataset is a portion of all the missing values when the time-series lacks $30\%$ of all data. The metrics to measure the performance of the algorithms are root-mean-square error (RMSE) and the coefficient of determination ($R^{2}$). The results indicate that the proposed algorithm outperforms autoregressive models while preserving the seasonal behavior of the time-series. The STIGMA is also tested with non-weather time-series of beer sales and number of air passengers per month, which also have a cyclical pattern, and the results show the precise imputation of data

Fully-parallel quantum turbo decoder

Quantum Turbo Codes (QTCs) are known to operate close to the achievable Hashing bound. However, the sequential nature of the conventional quantum turbo decoding algorithm imposes a high decoding latency, which increases linearly with the frame length. This posses a potential threat to quantum systems having short coherence times. In this context, we conceive a Fully- Parallel Quantum Turbo Decoder (FPQTD), which eliminates the inherent time dependencies of the conventional decoder by executing all the associated processes concurrently. Due to its parallel nature, the proposed FPQTD reduces the decoding times by several orders of magnitude, while maintaining the same performance. We have also demonstrated the significance of employing an odd-even interleaver design in conjunction with the proposed FPQTD. More specifically, it is shown that an odd-even interleaver reduces the computational complexity by 50%, without compromising the achievable performance