Efficient eigenvalue assignments for general linear MIMO systems

최근 대용량, 초고속 통신 서비스의 비중이 높아짐에 따라 배열 안테나를 사용하는 MIMO(Multi-Input Multi-Output) 시스템의 활용이 중요하게 평가되고 있다. 하지만 기존의 MIMO 시스템은 다수의 안테나를 사용하기 때문에 안테나의 개수만큼 RF(Radio Frequency) 체인이 요구되며, 이로 인해 복잡도와 전력 소모가 크다는 단점을 가진다. 이러한 기존 MIMO 시스템의 단점을 해결하기 위해서 단일 능동 소자와 다수의 기생 소자를 이용하는 방식의 ESPAR(Electronically Steerable Parasitic Array Radiator) 안테나를 사용하는 빔 공간 MIMO 시스템에 대한 연구가 활발히 진행되고 있다. ESPAR 안테나를 사용하는 빔 공간 MIMO 시스템은 단일 RF 체인으로 구성되어 있기 때문에 기존 MIMO 시스템의 단점을 해결할 수 있다. 본 논문에서는 시스템의 보안성을 향상시키기 위해 QPSK(Quadrature Phase Shift Keying) 변조 방식의 ESPAR 안테나를 사용하는 빔 공간 MIMO 시스템에 비예측성, 비주기성, 구현의 용이성, 민감한 초기조건 등의 특징을 가지고 있는 카오스 통신 알고리즘을 적용하여 QPSK 변조 방식의 ESPAR 안테나를 사용하는 카오스 빔 공간 MIMO 시스템을 구성하고 성능을 평가한다. Recently, utilization of MIMO(Multi-Input Multi-Output) system using array antennas is evaluated significantly according to the extension of high-capacity and high-speed communication services. However, MIMO system has disadvantages such as high-complexity and high-power-consumption, because RF(Radio Frequency) chain is required as antenna number, and several array antenna is used in conventional MIMO system. In order to solve these problems, research about beamspace MIMO system using ESPAR(Electronically Steerable Parasitic Array Radiator) antenna that has single RF chain by using one active antenna and several parasitic elements has been studied actively. Beamspace MIMO system using ESPAR antenna is possible to solve the problems of conventional MIMO system, because this system is composed by single RF chain. In this paper, in order to improve the system security, chaos communication algorithm that has characteristics such as non-periodic, non-predictability, easy implementation and initial condition is applied to QPSK (Quadrature Phase Shift Keying) modulated beamspace MIMO system. We design the chaos QPSK modulated beamspace MIMO system, and evaluate SER performance of this system.

In this paper the Routh Approximation method is explored for getting the reduced order model of a higher order model. The reduced order modeling of a large system is necessary to ease the analysis of the system. The approach is examined and compared to single-input single-output (SISO) and multi-input multi-output (MIMO) systems. The response comparison is considered in terms of step response parameters and graphical comparisons. It is reported that the reduced order model using proposed Routh Approximation (RA) method is almost similar in behavior to that of with original systems.

In wireless communication, multiple signals are utilized to receive and send information in the form of signals simultaneously. These signals consume little power and are usually inexpensive, with a high data rate during data transmission. An Multi Input Multi Output (MIMO) system uses numerous antennas to enhance the functionality of the system. Moreover, system intricacy and power utilization are difficult and highly complicated tasks to achieve in an Analog to Digital Converter (ADC) at the receiver side. An infinite number of MIMO channels are used in wireless networks to improve efficiency with Cross Entropy Optimization (CEO). ADC is a serious issue because the data of the accepted signal are completely lost. ADC is used in the MIMO channels to overcome the above issues, but it is very hard to implement and design. So, an efficient way to enhance the estimation of channels in the MIMO system is proposed in this paper with the utilization of the heuristic-based optimization technique. The main task of the implemented channel prediction framework is to predict the channel coefficient of the MIMO system at the transmitter side based on the receiver side error ratio, which is obtained from feedback information using a Hybrid Serial Cascaded Network (HSCN). Then, this multi-scaled cascaded autoencoder is combined with Long Short Term Memory (LSTM) with an attention mechanism. The parameters in the developed Hybrid Serial Cascaded Multi-scale Autoencoder and Attention LSTM are optimized using the developed Hybrid Revised Position-based Wild Horse and Energy Valley Optimizer (RP-WHEVO) algorithm for minimizing the "Root Mean Square Error (RMSE), Bit Error Rate (BER) and Mean Square Error (MSE)" of the estimated channel. Various experiments were carried out to analyze the accomplishment of the developed MIMO model. It was visible from the tests that the developed model enhanced the convergence rate and prediction performance along with a reduction in the computational costs.

Blending based multiple-model adaptive control of multivariable systems with application to lateral vehicle motion control

This paper develops a multiple fixed model blending based adaptive parameter identification scheme for multi-input multi-output (MIMO) systems with polytopic parameter uncertainty. The developed identification scheme is proven to be asymptotically stable for uncertain linear time-invariant MIMO systems, and is shown to provide fast adaptation for even uncertain linear time-varying (LTV) systems. Furthermore, utilizing the proposed parameter identification scheme, a linear-quadratic (LQ) optimal multiple model adaptive control (MMAC) scheme is developed for linear MIMO systems with polytopic uncertainties. The proposed MMAC scheme is applied to tracking control of uncertain lateral vehicle dynamics. A set of simulation test results are presented to verify the stability and effectiveness of the proposed MMAC scheme.

Transmit diversity schemes have been studied for high spectral-efficiency and high bit-rate transmission, such as multi-input multi-output (MIMO) systems. In this paper, a novel dual polarized ceiling-mounted antenna is designed and simulated. In the MIMO systems, forward error correction coding is essential for high quality communications. At the two typical scenes, the single-input single-output system compared with two single polarized antennas and an dual polarized antenna MIMO system is tested. It is shown that the MIMO system have improved throughput level obviously. The dual polarized ceiling-Mounted dual streams MIMO antenna will save much construction cost in the long-term evaluation systems in the future, which can be called the “green” MIMO antenna.

Block synchronization is a prerequisite to data-dependent superimposed training (DDST) based channel estimation. Mainly designed for single input single output (SISO) system, the existing block synchronization algorithms can hardly work for multi-input multi-output (MIMO) system. A new joint block synchronization, channel and dc-offset estimation algorithm based on balanced zero correlation zone (ZCZ) sequence for MIMO system is proposed in this paper. Analysis and simulation results show that the new algorithm has the same performance for SISO systems as the existing algorithms when their block and cyclic prefix lengths are the same. While for MIMO systems, the performance of the proposed algorithm is much better than that of the existing algorithms.

Robust decentralised frequency stabilisers design of static synchronous series compensators by taking system uncertainties into consideration

<p class="Default">The consistent demand for higher data rates and need to send giant volumes of data while not compromising the quality of communication has led the development of a new generations of wireless systems. But range and data rate limitations are there in wireless devices. In an attempt to beat these limitations, Multi Input Multi Output (MIMO) systems will be used which also increase diversity and improve the bit error rate (BER) performance of wireless systems. They additionally increase the channel capacity, increase the transmitted data rate through spatial multiplexing, and/or reduce interference from other users. MIMO systems therefore create a promising communication system because of their high transmission rates without additional bandwidth or transmit power and robustness against multipath fading. This paper provides the overview of Multiuser MIMO system. A detailed review on how to increase performance of system and reduce the bit error rate (BER) in different fading environment e.g. Rayleigh fading, Rician fading, Nakagami fading, composite fading.</p>

In this article, an attempt is made to design the fractional order proportional integral derivative (FO-PID) controller for multi-input multi-output (MIMO) system using teaching learning-based optimization (TLBO) algorithm. The control of MIMO system always offers a complicated control paradigm due to its structure. It is realized that dynamic systems can be effectively represented by fractional order dynamics which is based on fractional calculus. The PID controller is still the most reliable controller due to its uncomplicated structure, and the FO-PID controller is predicted to have better performance as compared to conventional PID controller due to increment of two more parameters. The performance of non-integer PID controller depends upon the five constants; hence, the tuning of these five constants is most important for the optimum performance. In the presented work, TLBO technique is adopted for the tuning of the non-integer PID controller. The designed controller is implemented on the four tank MIMO system in MATLAB. The performance of the designed controller is also compared from the previous results available in literature.KeywordsFour tank MIMO systemFO-PIDTLBO

The paper proposes an approach to second order sliding mode control for multi-input multi-output (MIMO) nonlinear uncertain systems. Second order sliding mode techniques for single-input single-output (SISO) systems show, with respect to standard sliding mode control, the same properties of robustness and precision, feature a higher order accuracy and can be exploited to eliminate the chattering effect. The application of second order sliding mode control to MIMO nonlinear systems is a challenging matter. The presented MIMO control method applies to a quite large class of nonlinear processes affected by uncertainties of general nature; the control design is simple; the conditions of existence on the controllers are weak. The proposed procedure represents a general approach to the second order sliding mode control of MIMO systems

Robust model reference adaptive output feedback tracking for uncertain linear systems with actuator fault based on reinforced dead-zone modification

This study considers an improved likelihood probability in multi-input multi-output (MIMO) systems using one-bit analog-to-digital converters (ADCs). MIMO systems using one-bit ADCs are known to exhibit from performance degradation because of inaccurate likelihood probabilities. To overcome this degradation, the proposed method leverages the detected symbols to estimate the true likelihood probability by combining the initial likelihood probability. An optimization problem is formulated to minimize the mean-squared error between the true and combined likelihood probabilities, and a solution is derived using the least-squares method. Simulation results show that the proposed method obtains a signal-to-noise gain of approximately 0.3 dB to achieve a frame error rate of 10−1 compared to conventional methods. This improvement in performance is attributed to the enhanced reliability of the likelihood probability.

This paper addresses the problem of frequency offsets and channel gains estimation for a multi-input multi-output (MIMO) system in flat-fading channels. The general case where the frequency offsets are possibly different for each transmit antenna is considered. The maximum-likelihood (ML) estimation of the carrier frequency offset for each transmit antenna in a MIMO system is investigated in this paper, assuming that a training sequence is available. The exact solution to this estimation problem turns out to be too complex as it involves a search over a multi-dimensional domain. To solve this complex estimation problem, a novel joint estimation algorithm of frequency offsets and channel gains is proposed. Frequency offsets are first estimated by the particle swarm optimization theory. Then channel gains are estimated by the ML estimator. Simulation results show that the proposed algorithm has better performance as compared with the correlation-based estimation algorithm and asymptotically achieves the Cramer-Rao lower bound (CRLB), which provides a new idea to solve the problem of joint frequency offsets and channel gains estimation for MIMO systems.

This paper deals with a approximating method for large time-delays of multi-input multi-output (MIMO) dynamical systems. The methodology is an improved rational approximation approach. Time delay terms of the state space equations can be described by delay matrix in the complex domain and approximated by rational matrix Pade-type functions. The minimum variance estimation error is minimized to obtain rational approximation of MIMO systems to guarantee the poles located in the left half plane. Matrix Pade-type approximation can largely reduce the instability and the overshoot, so the fast-response property is improved. Simulation results of the proposed method are presented to illustrate the correctness and effectively.