scholarly journals Capacity Analysis and Linear Detection in Massive MIMO for 5G Wireless Systems

2019 ◽  
Vol 8 (9) ◽  
pp. 2938-2943
Keyword(s):  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Symbol Error Rate ◽  
Base Station ◽  
Matlab Simulation ◽  
Maximum Ratio Combining ◽  
Single Antenna ◽  
Air Interface ◽  
Multiple Input ◽  
Input Multiple Output

Multiple Input Multiple Output (MIMO) is an attractive air interface solution which is used in the 4 th generation wireless networks to achieve higher data rate. With a very large antenna array in Massive MIMO the capacity will increase drastically. In this paper channel capacity comparison for MIMO using known Channel State Information (CSI) and unknown CSI has been carried out for a higher number of antennas at transmitter and receiver side. It has shown that at lower SNR known CSI will give better performance compared to unknown CSI. At higher SNR known CSI and unknown CSI will provide similar results. Capacity comparison has been evaluated with help of MATLAB for known CSI and unknown CSI from a small number of antennas to hundred of antennas. Also, the performance evaluated with MATLAB simulation of linear detectors zero-forcing (ZF) and maximum ratio combining (MRC) method for large number of antennas at Base station (BS) which are serving a small number of single antenna users. Performance is evaluated in terms of Symbol Error Rate (SER) for ZF and MRC, and results show that ZF will outperform MRC. It has also been analyzed that increasing the antennas at BS for a small number of users will also help to reduce SER.

A companding approach for PAPR suppression in OFDM based massive MIMO system

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ajay Kumar Yadav ◽  
Pritam Keshari Sahoo ◽  
Yogendra Kumar Prajapati
Keyword(s):  
Massive Mimo ◽  
Orthogonal Frequency Division Multiplexing ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Average Power ◽  
Base Station ◽  
Convex Optimization Problem ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Ofdm

Abstract Orthogonal frequency division multiplexing (OFDM) based massive multiuser (MU) multiple input multiple output (MIMO) system is popularly known as high peak-to-average power ratio (PAPR) issue. The OFDM-based massive MIMO system exhibits large number of antennas at Base Station (BS) due to the use of large number of high-power amplifiers (HPA). High PAPR causes HPAs to work in a nonlinear region, and hardware cost of nonlinear HPAs are very high and also power inefficient. Hence, to tackle this problem, this manuscript suggests a novel scheme based on the joint MU precoding and PAPR minimization (PP) expressed as a convex optimization problem solved by steepest gradient descent (GD) with μ-law companding approach. Therefore, we develop a new scheme mentioned to as MU-PP-GDs with μ-law companding to minimize PAPR by compressing and enlarging of massive MIMO OFDM signals simultaneously. At CCDF = 10−3, the proposed scheme (MU-PP-GDs with μ-law companding for Iterations = 100) minimizes the PAPR to 3.70 dB which is better than that of MU-PP-GDs, (iteration = 100) as shown in simulation results.

A Review of Massive Multiple Input Multiple Output for 5G Communication: Benefits and Challenges

2020 ◽  
Vol 1 (1) ◽  
pp. 22-26
Author(s):  
Shaik Nilofer ◽  
Keyword(s):  
Wireless Communication ◽  
Channel Capacity ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
System Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Primary Advantage ◽  
Time Division

Massive MIMO (mMIMO) systems become a primary advantage to overcome the problem of bandwidth restrictions. It improves the channel capacity of remote systems.The paper reviews about mMIMO systems. mMIMO consists of several number of antennas at base station (BS) which improves spectrum efficacy. The extra benefit of the mMIMO system is that the components cost is low because of utilization of less power components. The paper also discusses about the channel estimation at the BS and generally time division mode (TDD) is assumed for mMIMO systems. The paper also discusses system model, benefits for 5G wireless communication and its challenges.

scholarly journals Performance enhancement of maximum ratio transmission in 5G system with multi-user multiple-input multiple-output

2022 ◽  
Vol 12 (2) ◽  
pp. 1650
Author(s):  
Sarmad K. Ibrahim ◽  
Saif A. Abdulhussien
Keyword(s):  
Massive Mimo ◽  
Orthogonal Frequency Division Multiplexing ◽  
Performance Enhancement ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Standard System ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Ratio Transmission ◽  
Maximum Ratio Transmission

<span>The downlink multi-user precoding of the multiple-input multiple-output (MIMO) method includes optimal channel state information at the base station and a variety of linear precoding (LP) schemes. Maximum ratio transmission (MRT) is among the common precoding schemes but does not provide good performance with massive MIMO, such as high bit error rate (BER) and low throughput. The orthogonal frequency division multiplexing (OFDM) and precoding schemes used in 5G have a flaw in high-speed environments. Given that the Doppler effect induces frequency changes, orthogonality between OFDM subcarriers is disrupted and their throughput output is decreased and BER is decreased. This study focuses on solving this problem by improving the performance of a 5G system with MRT, specifically by using a new design that includes weighted overlap and add (WOLA) with MRT. The current research also compares the standard system MRT with OFDM with the proposed design (WOLA-MRT) to find the best performance on throughput and BER. Improved system results show outstanding performance enhancement over a standard system, and numerous improvements with massive MIMO, such as best BER and throughput. Its approximately 60% more throughput than the traditional systems. Lastly, the proposed system improves BER by approximately 2% compared with the traditional system.</span>

A Review of Massive Multiple Input Multiple Output for 5G Communication: Benefits and Challenges

2020 ◽  
Vol 1 (1) ◽  
pp. 22-26
Author(s):  
Shaik Nilofer
Keyword(s):  
Wireless Communication ◽  
Channel Capacity ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
System Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Primary Advantage ◽  
Time Division

Massive MIMO (mMIMO) systems become a primary advantage to overcome the problem of bandwidth restrictions. It improves the channel capacity of remote systems.The paper reviews about mMIMO systems. mMIMO consists of several number of antennas at base station (BS) which improves spectrum efficacy. The extra benefit of the mMIMO system is that the components cost is low because of utilization of less power components. The paper also discusses about the channel estimation at the BS and generally time division mode (TDD) is assumed for mMIMO systems. The paper also discusses system model, benefits for 5G wireless communication and its challenges.

Fault-tolerant PWM inverter model development for safety electrical drives

2016 ◽  
Vol 7 (2) ◽  
pp. 77-83 ◽  
Author(s):  
Cs. Szász ◽  
R. Şinca
Keyword(s):  
Energy Efficiency ◽  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Mean Square ◽  
Maximum Ratio Combining ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Better Than

This paper deals with the most recent technology in wireless communication which is massive multiple input multiple output system. The paper studies the performance of massive multiple input multiple output uplink system over Rayleigh fading channel. The performance is measured in terms of spectral and energy efficiency using three schemes of linear detection, maximum-ratio-combining, zero forcing receiver, and minimum mean-square error receiver. The simulation results show that the spectral and energy efficiency increases with increasing the number of base station antennas. Also, the spectral and energy efficiency with minimum mean-square error receiver is better than that withzero forcing receiver, and the latter is better than that with maximum-ratio-combining. Furthermore, the energy efficiency decreases with increasing the spectral efficiency.

scholarly journals Downlink Spectral Efficiency Analysis in Distributed Massive MIMO with Phase Noise

Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 317 ◽  
Author(s):  
Qian Lv ◽  
Jiamin Li ◽  
Pengcheng Zhu ◽  
Dongming Wang ◽  
Xiaohu You
Keyword(s):  
Phase Noise ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Large Scale ◽  
Channel Model ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Small Scale ◽  
Multiple Input ◽  
Input Multiple Output

To achieve the advantages provided by massive multiple-input multiple-output (MIMO), a large number of antennas need to be deployed at the base station. However, for the reason of cost, inexpensive hardwares are employed in the realistic scenario, which makes the system distorted by hardware impairments. Hence, in this paper, we analyze the downlink spectral efficiency in distributed massive MIMO with phase noise and amplified thermal noise. We provide an effective channel model considering large-scale fading, small-scale fast fading and phase noise. Based on the model, the estimated channel state information (CSI) is obtained during the pilot phase. Under the imperfect CSI, the closed-form expressions of downlink achievable rates with maximum ratio transmission (MRT) and zero-forcing (ZF) precoders in distributed massive MIMO are derived. Furthermore, we also give the user ultimate achievable rates when the number of antennas tends to infinity with both precoders. Based on these expressions, we analyze the impacts of phase noise on the spectral efficiency. It can be concluded that the same limit rate is achieved with both precoders when phase noise is present, and phase noise limits the spectral efficiency. Numerical results show that ZF outdoes MRT precoder in spectral efficiency and ZF precoder is more affected by phase noise.

Spectral and energy efficiency of massive MIMO system

2016 ◽  
Vol 7 (2) ◽  
pp. 71-75
Author(s):  
M. Al-Rawi ◽  
M. Al-Rawi
Keyword(s):  
Energy Efficiency ◽  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Mean Square ◽  
Maximum Ratio Combining ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Better Than

This paper deals with the most recent technology in wireless communication which is massive multiple input multiple output system. The paper studies the performance of massive multiple input multiple output uplink system over Rayleigh fading channel. The performance is measured in terms of spectral and energy efficiency using three schemes of linear detection, maximum-ratio-combining, zero forcing receiver, and minimum mean-square error receiver. The simulation results show that the spectral and energy efficiency increases with increasing the number of base station antennas. Also, the spectral and energy efficiency with minimum mean-square error receiver is better than that withzero forcing receiver, and the latter is better than that with maximum-ratio-combining. Furthermore, the energy efficiency decreases with increasing the spectral efficiency.

scholarly journals Implementation of a Zero-Forcing Precoding Algorithm Combined with Adaptive Beamforming Based on WiMAX System

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Hyunwook Yang ◽  
Seungwon Choi
Keyword(s):  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Experimental System ◽  
Multiple Access Interference ◽  
Adaptive Beamforming ◽  
Base Station ◽  
Zero Forcing ◽  
Single Antenna ◽  
Input Multiple Output ◽  
Wimax System

We propose a novel precoding algorithm that is a zero-forcing (ZF) method combined with adaptive beamforming in the Worldwide Interoperability for Microwave Access (WiMAX) system. In a Multiuser Multiple-Input Multiple-Output (MU-MIMO) system, ZF is used to eliminate the Multiple Access Interference (MAI) in order to allow several users to share a common resource. The adaptive beamforming algorithm is used to achieve the desired SNR gain. The experimental system consists of a WiMAX base station that has 2 MIMO elements, each of which is composed of three-array antennas and two mobile terminals, each of which has a single antenna. Through computer simulations, we verified that the proposed method outperforms the conventional ZF method by at least 2.4 dB when the BER is 0.1%, or 1.7 dB when the FER is 1%, in terms of the SNR. Through a hardware implementation of the proposed method, we verified the feasibility of the proposed method for realizing a practical WiMAX base station to utilize the channel resources as efficiently as possible.

PROBLEM STATEMENT OF JOINT ANTENNA SELECTION AND PRECODING IN MASSIVE MIMO COMMUNICATION SYSTEMS

2021 ◽  
Author(s):  
В.Б. КРЕЙНДЕЛИН ◽  
М.В. ГОЛУБЕВ
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Research Areas ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Legal Restrictions ◽  
Multiple Transmission

Совместный с прекодингом автовыбор антенн на приемной и передающей стороне - одно из перспективных направлений исследований для реализации технологий Multiple Transmission and Reception Points (Multi-TRP, множество точек передачи и приема) в системах со многими передающими и приемными антеннами Massive MIMO (Multiple-Input-Multiple-Output), которые активно развиваются в стандарте 5G. Проанализированы законодательные ограничения, влияющие на применимость технологий Massive MIMO, и специфика реализации разрабатываемого алгоритма в миллиметровомдиапа -зоне длин волн. Рассмотрены алгоритмы формирования матриц автовыбора антенн как на передающей, так и на приемной стороне. Сформулирована строгая математическая постановка задачи для двух критериев работы алгоритма: максимизация взаимной информации и минимизация среднеквадратичной ошибки. Joint precoding and antenna selection both on transmitter and receiver sides is one of the promising research areas for evolving toward the Multiple Transmission and Reception Points (Multi-TRP) concept in Massive MIMO systems. This technology is under active development in the coming 5G 3GPP releases. We analyze legal restrictions for the implementation of 5G Massive MIMO technologies in Russia and the specifics of the implementation of the developed algorithm in the millimeter wavelength range. Algorithms of antenna auto-selection matrices formation on both transmitting and receiving sides are considered. Two criteria are used for joint antenna selection and precoding: maximizing mutual information and minimizing mean square error.

scholarly journals Investigation of the Effect of Noise Correlations on Diversity Gains and Capacities of Multiport Antennas Using Reverberation Chamber

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaoming Chen ◽  
Jian Yang
Keyword(s):  
Multiple Input Multiple Output ◽  
Correlation Effects ◽  
Reverberation Chamber ◽  
Maximum Ratio Combining ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Capacity ◽  
First Time ◽  
Diversity Gains ◽  
Correlated Noises

Most of previous studies on diversity gains and capacities of multiantenna systems assumed independent and identically distributed (i.i.d.) Gaussian noises. There are a few studies about the noise correlation effects on diversity gains or MIMO capacities, however, by simulations only. In this paper, the maximum ratio combining (MRC) diversity gain and multiple-input multiple-output (MIMO) capacity including correlated noises are presented. Based on the derived formulas, measurements in a reverberation chamber are performed for the first time to observe the effect of noise correlations on diversity gains and MIMO capacities.

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