Design of data acquisition system for artillery unit

Data acquisition involves gathering signals that measure real world physical conditions from measurement sources and then modify it into different format for storage purpose. Typically a Data acquisition system converts physical signals which are analog in nature into digital form which is to be manipulated by a computer. In this work a multi channel data acquisition system is developed to acquire the data from Artillery unit in real time environment. More importance is given on the accuracy of the data captured and speed of operation of the developed data acquisition system. Micro controller based hardware system is developed to generate prototype signals similar to the signal generated by the artillery unit. This is required to simulate firing pulses of the artillery unit in the laboratory to test the data acquisition system off line before implementing it in the real time environment. The driver software is programmed to implement sixteen channel data acquisition system. The front end is designed in a simplified manner from the user point of view where several buttons with different nomenclature are placed for the corresponding operation of data. The capability of storage of data, retrieving the stored data in a graphical format for back analysis and instant calculation of different timing parameters during the data acquisition process made the overall system into a powerful and efficient tool. In addition to that another feature is implemented in this system where, the quest for a particular segment of stored data can be done instantly without putting any effort and necessary information can be obtained from that segment. Further analysis of stored data is done where presence of error in the signal is detected. The data gets corrupted by noise during the process of firing which makes it difficult to detect the presence of error in the signal. Hence at the outset, the signal enhancement method is implemented to the data followed by which, the error detection method is applied to find out the presence of error

A Low Complexity Optimal LMMSE Channel Estimator for OFDM System

Linear minimum mean square error (LMMSE) is the optimal channel estimator in the mean square error (MSE) perspective, however, it requires matrix inversion with cubic complexity. In this paper, by exploiting the circulant property of the channel frequency autocorrelation matrix RHH, an efficient LMMSE channel estimation method has been proposed for orthogonal frequency division multiplexing (OFDM) based on fast Fourier transformation (FFT) and circular convolution theorem. Finally, the computer simulation is carried out to compare the proposed LMMSE method with the classical LS and LMMSE methods in terms of performance measure and computational complexity. The simulation results show that the proposed LMMSE estimator achieves exactly same performance as conventional LMMSE estimator with much lower computational complexity

Performance Evaluation of PID Controller for an Automobile Cruise Control System using Ant Lion Optimizer

This paper considers the design and performance evaluation of PID controller for an automobile cruise control system (ACCS). A linearized model of the cruise control system has been studied as per the dominant characteristics in closed loop system. The design problem is recast into an optimization problem which is solved using Ant Lion Optimization (ALO). The transient performance of proposed ACCS i.e., settling time, rise time, maximum overshot, peak time and steady state error are investigated by step input response and root locus analysis. To show the efficacy of the proposed algorithm over a state space method, classical PID, fuzzy logic, genetic algorithm, a comparison study is presented by using MATLAB/SIMULINK. Furthermore, the robustness of the system is evaluated by using bode analysis, sensitivity, complimentary sensitivity and controller sensitivity. The results indicate that the designed ALO based PID controller for ACCS achieves better performance than other recent methods reported in the literature.This paper considers the design and performance evaluation of PID controller for an automobile cruise control system (ACCS). A linearized model of the cruise control system has been studied as per the dominant characteristics in closed loop system. The design problem is recast into an optimization problem which is solved using Ant Lion Optimization (ALO). The transient performance of proposed ACCS i.e., settling time, rise time, maximum overshot, peak time and steady state error are investigated by step input response and root locus analysis. To show the efficacy of the proposed algorithm over a state space method, classical PID, fuzzy logic, genetic algorithm, a comparison study is presented by using MATLAB/SIMULINK. Furthermore, the robustness of the system is evaluated by using bode analysis, sensitivity, complimentary sensitivity and controller sensitivity. The results indicate that the designed ALO based PID controller for ACCS achieves better performance than other recent methods reported in the literature

Distributed MIMO Systems with ZF Detectors in Rayleigh-Inverse Gaussian Composite Fading Channels

Distributed multiple-input multiple-output (D-MIMO) system has become a promising technique for next generation wireless networks, which offer considerably high throughput and link reliability over conventional point-to-point MIMO. This is achieved by packing multiple antennas at one end of the wireless channel into spatially separated multiple radio ports (RPs). Performance analysis of such distributed antenna systems (DASs) having different propagation paths pertaining to individual RPs becomes a challenging task as the communicating channel experiences combined effect of both small and large-scale fading, also known as composite fading. Composite fading is more realistic for systems like DAS and relay systems, and in such systems small-scale fading alone does not provide accurate statistical distribution of fading channels. In this dissertation, we consider D-MIMO wireless channels experiencing Nakagami-Inverse Gaussian (G) and Rayleigh-Inverse Gaussian (RIG) composite distributions and investigate the uplink performance of such systems in terms of ergodic capacity, average symbol error rate (SER) and outage probability (OP). We begin with the discussion on state-of-the-art composite distributions in modelling single-input single-output (SISO) and MIMO channels. Then the widely used Rayleigh-Gamma (a.k.a. K) and Nakagami-Gamma (a.k.a. KG) distributions are reviewed in detail, and the performance of MIMO systems over such channels are compared with RIG and G distributions, respectively in subsequent part of this dissertation. To this end, a reparametrized KG (KG(R)) model is proposed in the formulation of signal-to-noise ratio (SNR) distribution for SISO communication system. In the analysis of Inverse Gaussian (IG) shadowed composite fading channels, upper and lower bounds of ergodic capacity for optimal detectors are evaluated over G fading D-MIMO channels. However, the analysis of exact ergodic capacity and other performance measures can not be accomplished due to the unavailability of joint channel statistics of non-Gaussian fading channels. In order to perform in-depth characterization of channels operating over G distribution, we consider a point-to-point MIMO system with orthogonal space-time block code (OSTBC) transmit diversity technique. Interestingly, the MIMO OSTBC channel can be transformed into an equivalent scalar channel that significantly simplifies the mathematical exercise for analysis. Detailed analytical investigation is performed for MIMO OSTBC systems considering aforementioned figure of merits. In subsequent analysis, we consider low complexity linear zero forcing (ZF) detector which requires closed form density function of pseudo inverse of D-MIMO channel matrix. Therefore, analytically tractable Rayleigh distribution is assumed here as small-scale fading component that leads to RIG composite distribution in modelling D-MIMO channels. The presence of spatial correlation was also taken into consideration which is experienced frequently in multi-antenna scenarios. We first demonstrate the effects of spatial correlation on spatially multiplexed point-to-point MIMO system in reference to beamforming system which is highly immune to such correlation. In the next part of the analysis, a systematic characterization of RIG distribution is provided in modelling D-MIMO channels with ZF detectors in presence of transmit antenna correlation. Closed-form expressions of exact ergodic capacity, their approximations in high and low SNR regime and ergodic capacity bounds are found. The analytical expressions of average SER and OP are also deduced in tractable form. Additionally, we propose to formulate simplified expressions of average SER as well as OP in high SNR regime and assess their approximation accuracy. In further analysis of this dissertation, a D-MIMO system is considered in massive MIMO scenario and the performance of the resulting distributed massive MIMO (DM-MIMO) system is evaluated in detail. We consider two different D-MIMO architectures with the base station (BS) containing large number of antennas. The architecture of DM-MIMO-I system is analogous to the D-MIMO systems described earlier. For instance, in uplink scenario the RPs having multiple antennas of a DM-MIMO-I system are placed at arbitrary locations and simultaneously communicate with the centrally located BS. Here, the instantaneous output SNR of kth subchannel is formulated by applying the law of large numbers. On the other hand, the DM-MIMO-II architecture comprises of multiple BSs or remote access units (RAUs), distributed across the cell and arbitrarily located mobile unit. The performance of such systems are evaluated for both finite and infinite number of RAU antennas. In the latter case, approximated SNR is expressed as a sum of unequal IG random variables and subsequently the closed-form expressions of asymptotic ergodic capacity and average SER are formulated. The correctness of theoretical analysis presented in this dissertation are corroborated through Monte-Carlo simulations. In light of this, the efficacy of considered systems are investigated in various severity of shadowing environments including light, average and frequent heavy shadowing. Moreover, the implications of fading and shadowing parameters, number of antennas, positions of RPs, locations of RAUs, antenna correlation, etc. on system performance are investigated

A DFT-based Low Complexity LMMSE Channel Estimation Technique for OFDM Systems

The linear minimum mean square error (LMMSE) channel estimation technique is often employed in orthogonal frequency division multiplexing (OFDM) systems because of its optimal performance in the mean square error (MSE) performance. However, the LMMSE method requires cubic complexity of order O(N 3 p ), where Np is the number of pilot subcarriers. To reduce the computational complexity, a discrete Fourier transform (DFT) based LMMSE method is proposed in this paper for OFDM systems in the frequency selective channel. To validate the proposed method, the closed form mean square error (MSE) expression is also derived. Finally, a computer simulation is carried out to compare the performance of the proposed LMMSE method with the classical LS and LMMSE methods in terms of bit error rate (BER) and computational complexity. Results of the simulation show that the proposed LMMSE method achieves exactly the same performance as the conventional LMMSE method, with much lower computational complexity

A DFT-based Low Complexity LMMSE Channel Estimation Technique for OFDM Systems, Journal of Telecommunications and Information Technology, 2022, nr 1

The linear minimum mean square error (LMMSE) channel estimation technique is often employed in orthogonal frequency division multiplexing (OFDM) systems because of its optimal performance in the mean square error (MSE) performance. However, the LMMSE method requires cubic complexity of order O(N 3 p ), where Np is the number of pilot subcarriers. To reduce the computational complexity, a discrete Fourier transform (DFT) based LMMSE method is proposed in this paper for OFDM systems in the frequency selective channel. To validate the proposed method, the closed form mean square error (MSE) expression is also derived. Finally, a computer simulation is carried out to compare the performance of the proposed LMMSE method with the classical LS and LMMSE methods in terms of bit error rate (BER) and computational complexity. Results of the simulation show that the proposed LMMSE method achieves exactly the same performance as the conventional LMMSE method, with much lower computational complexity

An Ordered QR Decomposition based Signal Detection Technique for Uplink Massive MIMO System

Signal detection turns out to be a critical challenge in massive MIMO (m-MIMO) system due to the deployment of large number of antennas at the base station. Although, the minimum mean square error (MMSE) is one of the popular signal detection method, but, it requires matrix inversion with cubic complexity. In order to reduce computational complexity, several suboptimal signal detection methods were proposed such as Gauss-Seidel, successive over relaxation, Jacobi, Richardson methods. Although, these methods provide low complexity but their performance are limited to MMSE method. In this paper, we have proposed two signal detection techniques namely QR decompositions (QRD) and ordered QRD (OQRD). Finally, the performances of proposed signal detection methods are compared with various conventional methods in terms of symbol error rate (SER) and computational complexity. The simulation results validate that the proposed methods outperform the MMSE method with substantially lower computational complexity