scholarly journals Analysis and Optimization for Downlink Cell-Free Massive MIMO System with Mixed DACs

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2624
Author(s):  
Meng Zhou ◽  
Yao Zhang ◽  
Xu Qiao ◽  
Weiqiang Tan ◽  
Longxiang Yang
Keyword(s):  
Power Consumption ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Quantization Noise ◽  
Noise Model ◽  
Hardware Cost ◽  
Bisection Algorithm ◽  
Digital To Analog Converters ◽  
Rate Analysis ◽  
Channel Estimate

This paper concentrates on the rate analysis and optimization for a downlink cell-free massive multi-input multi-output (MIMO) system with mixed digital-to-analog converters (DACs), where some of the access points (APs) use perfect-resolution DACs, while the others exploit low-resolution DACs to reduce hardware cost and power consumption. By using the additive quantization noise model (AQNM) and conjugate beamforming receiver, a tight closed-form rate expression is derived based on the standard minimum mean square error (MMSE) channel estimate technique. With the derived result, the effects of the number of APs, the downlink transmitted power, the number of DAC bits, and the proportion of the perfect DACs in the mixed-DAC architecture are conducted. We find that the achievable sum rate can be improved by increasing the proportion of the perfect DACs and deploying more APs. Besides, when the DAC resolution arrives at 5-bit, the system performance will invariably approach the case of perfect DACs, which indicates that we can use 5-bit DACs to substitute the perfect DACs. Thus, it can greatly reduce system hardware cost and power consumption. Finally, the weighted max–min power allocation scheme is proposed to guarantee that the users with high priority have a higher rate, while the others are served with the same rate. The simulation results prove the proposed scheme can be effectively solved by the bisection algorithm.

scholarly journals ASEP of MIMO System with MMSE-OSIC Detection over Weibull-Gamma Fading Channel Subject to AWGGN

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Keerti Tiwari ◽  
Davinder S. Saini ◽  
Sunil V. Bhooshan
Keyword(s):  
Error Rate ◽  
System Performance ◽  
Interference Cancellation ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Noise Model ◽  
Composite Fading ◽  
Special Cases ◽  
The Impact

Ordered successive interference cancellation (OSIC) is adopted with minimum mean square error (MMSE) detection to enhance the multiple-input multiple-output (MIMO) system performance. The optimum detection technique improves the error rate performance but increases system complexity. Therefore, MMSE-OSIC detection is used which reduces error rate compared to traditional MMSE with low complexity. The system performance is analyzed in composite fading environment that includes multipath and shadowing effects known as Weibull-Gamma (WG) fading. Along with the composite fading, a generalized noise that is additive white generalized Gaussian noise (AWGGN) is considered to show the impact of wireless scenario. This noise model includes various forms of noise as special cases such as impulsive, Gamma, Laplacian, Gaussian, and uniform. Consequently, generalizedQ-function is used to model noise. The average symbol error probability (ASEP) of MIMO system is computed for 16-quadrature amplitude modulation (16-QAM) using MMSE-OSIC detection in WG fading perturbed by AWGGN. Analytical expressions are given in terms of Fox-H function (FHF). These expressions demonstrate the best fit to simulation results.

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.

scholarly journals Multiuser precoding scheme and achievable rate analysis for massive MIMO system

2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Weiqiang Tan ◽  
Wei Huang ◽  
Xi Yang ◽  
Zheng Shi ◽  
Wen Liu ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Mimo System ◽  
Achievable Rate ◽  
Rate Analysis ◽  
Multiuser Precoding

A NOVEL DECOMPOSITION APPROACH AND VLSI IMPLEMENTATION OF CHROMA INTERPOLATOR FOR H.264 ENCODERS

2013 ◽  
Vol 22 (10) ◽  
pp. 1340025
Author(s):  
TENG WANG ◽  
LEI ZHAO ◽  
ZI-YI HU ◽  
ZHENG XIE ◽  
XIN-AN WANG
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Hardware Design ◽  
Cmos Technology ◽  
Vlsi Implementation ◽  
Clock Frequency ◽  
Hardware Cost ◽  
Decomposition Approach ◽  
Lower Power ◽  
Decomposition Scheme

In this paper, a novel decomposition approach and VLSI implementation of the chroma interpolator with great hardware reuse and no multipliers for H.264 encoders are proposed. First, the characteristic of the chroma interpolation is analyzed to obtain an optimized decomposition scheme, with which the chroma interpolation can be realized with arithmetic elements (AEs) which are comprised of only adders. Four types of AEs are developed and a pipelining hardware design is proposed to conduct the chroma interpolation with great hardware reuse. The proposed design was prototyped within a Xilinx Virtex6 XC6VLX240T FPGA with a clock frequency as high as 245 MHz. The proposed design was also synthesized with SMIC 130 nm CMOS technology with a clock frequency of 200 MHz, which could support a real-time HDTV application with less hardware cost and lower power consumption.

An Adaptive Multiple LS Channel Estimation Method for MIMO System

2012 ◽  
Vol 239-240 ◽  
pp. 1084-1088
Author(s):  
Jin Lun Chen
Keyword(s):  
Numerical Simulation ◽  
Channel Estimation ◽  
Communication Systems ◽  
Mimo System ◽  
Estimation Method ◽  
Linear Least Squares ◽  
Mimo Communication ◽  
Channel Estimate ◽  
Wide Range ◽  
Multiple Input

Accurate channel estimation plays a key role in multiple-input and multiple-output (MIMO) communication systems. In this paper, we firstly discuss the popular linear least squares (LS) channel estimation and the multiple LS (MLS) channel estimation. Then an adaptive multiple LS (AMLS) channel estimate approach is proposed. Using numerical simulation, it is found that the proposed estimation method outperforms LS and MLS for a wide range of training SNRs.

A Comparative Study of Image Deblurring Techniques

2020 ◽  
Vol 17 (9) ◽  
pp. 4571-4579
Author(s):  
Rajbir Singh ◽  
Sumit Bansal
Keyword(s):  
Comparative Study ◽  
Image Restoration ◽  
Digital Image ◽  
Minimum Mean Square Error ◽  
Direct Methods ◽  
Structural Similarity ◽  
Single Step ◽  
Noise Model ◽  
Image Deconvolution ◽  
Indirect Methods

The method of recovering a true image from degraded one, to analyze that digital image and characteristics with no artifact errors is known as Image Restoration. These techniques are of two types: direct methods and indirect methods. Direct methods are those in which the results of image restoration are produced in one single step. Indirect methods are those in which the results of image restoration are produced after various steps. This method is termed as blind image deconvolution, when the known info is just the blurred digital image and no info about the (Point Spread Function) (PSF) or the degrading model. The target of the procedure is to recover both the latent (un-blurred) image and the blur kernel, simultaneously. In this paper, we presented a comprehensive research of image noise model,de-blurring methods, blur types, and a comparative study of various deblurring methods. We have implemented number experiments to study these methods according to their performance, (Peak Signal to Noise Ratio) PSNR, (structural similarity) SSIM, blur type, and (Minimum Mean Square Error) MMSE.

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