New formulations of algebraic criteria for controllability and observability of a linear MIMO-system

2021 ◽  
Keyword(s):  
Dynamical System ◽  
Mimo Systems ◽  
Mimo System ◽  
Linear Dynamical System ◽  
Linear Combinations ◽  
Matrix Kernel ◽  
Algebraic Criterion ◽  
Control Matrix ◽  
Controllability And Observability ◽  
Inputs And Outputs

New formulations of algebraic criteria for controllability and observability of a linear dynamical system with multiple inputs and outputs (MIMO-systems) are given, the corresponding theorems are formulated. The criteria are based on algebraic relations between linear combinations of the control matrix columns and own vectors of the free dynamics matrix. Keywords algebraic criterion; controllability; observability; linear MIMO-system; own value; own vector; Krylov vector and matrix; kernel; cokernel

MIMO Systems in a Composite Fading and Generalized Noise Scenario: A Review

2020 ◽  
Vol 14 ◽  
Author(s):  
Keerti Tiwari
Keyword(s):  
System Performance ◽  
Performance Enhancement ◽  
Channel Model ◽  
Mimo Systems ◽  
Mimo System ◽  
Spatial Diversity ◽  
Spatial Multiplexing ◽  
Channel Models ◽  
Efficient System ◽  
Composite Channel

: Multiple-input multiple-output (MIMO) systems have been endorsed to enable future wireless communication requirements. The efficient system designing appeals an appropriate channel model, that considers all the dominating effects of wireless environment. Therefore, some complex or less analytically acquiescent composite channel models have been proposed typically for single-input single-output (SISO) systems. These models are explicitly employed for mobile applications, though, we need a specific study of a model for MIMO system which can deal with radar clutters and different indoor/outdoor and mobile communication environments. Subsequently, the performance enhancement of MIMO system is also required in such scenario. The system performance enhancement can be examined by low error rate and high capacity using spatial diversity and spatial multiplexing respectively. Furthermore, for a more feasible and practical system modeling, we require a generalized noise model along with a composite channel model. Thus, all the patents related to MIMO channel models are revised to achieve the near optimal system performance in real world scenario. This review paper offers the methods to improve MIMO system performance in less and severe fading as well as shadowing environment and focused on a composite Weibull-gamma fading model. The development is the collective effects of selecting the appropriate channel models, spatial multiplexing/detection and spatial diversity techniques both at the transmitter and the receivers in the presence of arbitrary noise.

A novel unified approach to invariance conditions for a linear dynamical system

2017 ◽  
Vol 298 ◽  
pp. 351-367 ◽  
Author(s):  
Zoltán Horváth ◽  
Yunfei Song ◽  
Tamás Terlaky
Keyword(s):  
Dynamical System ◽  
Linear Dynamical System ◽  
Unified Approach

scholarly journals Communicating vessels: a non-linear dynamical system

2017 ◽  
Vol 39 (3) ◽  
Author(s):  
Roberto De Luca ◽  
Orazio Faella
Keyword(s):  
Dynamical System ◽  
Fluid Flow ◽  
Ideal Fluid ◽  
Oscillatory Motion ◽  
Linear Dynamical System ◽  
Static Properties ◽  
Bernoulli’S Equation ◽  
Non Linear ◽  
Dynamical Properties

The dynamics of an ideal fluid contained in two communicating vessels is studied. Despite the fact that the static properties of this system have been known since antiquity, the knowledge of the dynamical properties of an ideal fluid flowing in two communicating vessels is not similarly widespread. By means of Bernoulli's equation for non-stationary fluid flow, we study the oscillatory motion of the fluid when dissipation can be neglected.

scholarly journals The Downlink Performance for Cell-Free Massive MIMO with Instantaneous CSI in Slowly Time-Varying Channels

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1552
Author(s):  
Tongzhou Han ◽  
Danfeng Zhao
Keyword(s):  
Power Control ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Time Varying ◽  
Input Multiple Output ◽  
Efficiency Performance ◽  
A Cell ◽  
Time Varying Channel

In centralized massive multiple-input multiple-output (MIMO) systems, the channel hardening phenomenon can occur, in which the channel behaves as almost fully deterministic as the number of antennas increases. Nevertheless, in a cell-free massive MIMO system, the channel is less deterministic. In this paper, we propose using instantaneous channel state information (CSI) instead of statistical CSI to obtain the power control coefficient in cell-free massive MIMO. Access points (APs) and user equipment (UE) have sufficient time to obtain instantaneous CSI in a slowly time-varying channel environment. We derive the achievable downlink rate under instantaneous CSI for frequency division duplex (FDD) cell-free massive MIMO systems and apply the results to the power control coefficients. For FDD systems, quantized channel coefficients are proposed to reduce feedback overhead. The simulation results show that the spectral efficiency performance when using instantaneous CSI is approximately three times higher than that achieved using statistical CSI.

scholarly journals Maximizing Energy Efficiency for Consumption Circuit Power in Downlink Massive MIMO Wireless Networks

2017 ◽  
Vol 7 (6) ◽  
pp. 2977 ◽  
Author(s):  
Adeeb Salh ◽  
Lukman Audah ◽  
Nor Shahida M. Shah ◽  
Shipun A. Hamzah
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Data Rate ◽  
Optimal Number ◽  
Zero Forcing ◽  
High Data ◽  
Circuit Power

<span>Massive multi-input–multi-output (MIMO) systems are crucial to maximizing energy efficiency (EE) and battery-saving technology. Achieving EE without sacrificing the quality of service (QoS) is increasingly important for mobile devices. We first derive the data rate through zero forcing (ZF) and three linear precodings: maximum ratio transmission (MRT), zero forcing (ZF), and minimum mean square error (MMSE). Performance EE can be achieved when all available antennas are used and when taking account of the consumption circuit power ignored because of high transmit power. The aim of this work is to demonstrate how to obtain maximum EE while minimizing power consumed, which achieves a high data rate by deriving the optimal number of antennas in the downlink massive MIMO system. This system includes not only the transmitted power but also the fundamental operation circuit power at the transmitter signal. Maximized EE depends on the optimal number of antennas and determines the number of active users that should be scheduled in each cell. We conclude that the linear precoding technique MMSE achieves the maximum EE more than ZF and MRT</span><em></em><span>because the MMSE is able to make the massive MIMO system less sensitive to SNR at an increased number of antennas</span><span>.</span>

scholarly journals Performance Analysis of Rate Splitting in Massive MIMO Systems with Low Resolution ADCs/DACs

2021 ◽  
Vol 11 (20) ◽  
pp. 9409
Author(s):  
Roger Kwao Ahiadormey ◽  
Kwonhue Choi
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Quantization Noise ◽  
High Signal ◽  
Low Resolution ◽  
Rate Splitting ◽  
Noise Ratio

In this paper, we propose rate-splitting (RS) multiple access to mitigate the effects of quantization noise (QN) inherent in low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). We consider the downlink (DL) of a multiuser massive multiple-input multiple-output (MIMO) system where the base station (BS) is equipped with low-resolution ADCs/DACs. The BS employs the RS scheme for data transmission. Under imperfect channel state information (CSI), we characterize the spectral efficiency (SE) and energy efficiency (EE) by deriving the asymptotic signal-to-interference-and-noise ratio (SINR). For 1-bit resolution, the QN is very high, and the RS scheme shows no rate gain over the non-RS scheme. As the ADC/DAC resolution increases (i.e., 2–3 bits), the RS scheme achieves higher SE in the high signal-to-noise ratio (SNR) regime compared to that of the non-RS scheme. For a 3-bit resolution, the number of antennas can be reduced by 27% in the RS scheme to achieve the same SE as the non-RS scheme. Low-resolution DACs degrades the system performance more than low-resolution ADCs. Hence, it is preferable to equip the system with low-resolution ADCs than low-resolution DACs. The system achieves the best SE/EE tradeoff for 4-bit resolution ADCs/DACs.

Precoding for Multiuser MIMO

2012 ◽  
pp. 130-156 ◽  
Author(s):  
Elsadig Saeid ◽  
Varun Jeoti ◽  
Brahim Belhaouari Samir
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Achievable Rate ◽  
Multiple Access Channels ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Single User ◽  
A New Technique ◽  
Improved Technique

Future Wireless Networks are expected to adopt multi-user multiple input multiple output (MU-MIMO) systems whose performance is maximized by making use of precoding at the transmitter. This chapter describes the recent advances in precoding design for MU-MIMO and introduces a new technique to improve the precoder performance. Without claiming to be comprehensive, the chapter gives deep introduction on basic MIMO techniques covering the basics of single user multiple input multiple output (SU-MIMO) links, its capacity, various transmission strategies, SU-MIMO link precoding, and MIMO receiver structures. After the introduction, MU-MIMO system model is defined and maximum achievable rate regions for both MU-MIMO broadcast and MU-MIMO multiple access channels are explained. It is followed by critical literature review on linear precoding design for MU-MIMO broadcast channel. This paves the way for introducing an improved technique of precoding design that is followed by its performance evaluation.

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