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.

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.

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.

scholarly journals Pilot Decontamination Using Asynchronous Fractional Pilot Scheduling in Massive MIMO Systems

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6213
Author(s):  
Muhammad Irshad Zahoor ◽  
Zheng Dou ◽  
Syed Bilal Hussain Shah ◽  
Imran Ullah Khan ◽  
Sikander Ayub ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Ideal Number ◽  
Sum Rate ◽  
Inter Cell Interference ◽  
Time Division

Due to large spectral efficiency and low power consumption, the Massive Multiple-Input-Multiple-Output (MIMO) became a promising technology for the 5G system. However, pilot contamination (PC) limits the performance of massive MIMO systems. Therefore, two pilot scheduling schemes (i.e., Fractional Pilot Reuse (FPR) and asynchronous fractional pilot scheduling scheme (AFPS)) are proposed, which significantly mitigated the PC in the uplink time division duplex (TDD) massive MIMO system. In the FPR scheme, all the users are distributed into the central cell and edge cell users depending upon their signal to interference plus noise ratio (SINR). Further, the capacity of central and edge users is derived in terms of sum-rate, and the ideal number of the pilot is calculated which significantly maximized the sum rate. In the proposed AFPS scheme, the users are grouped into central users and edge users depending upon the interference they receive. The central users are assigned the same set of pilots because these users are less affected by interference, while the edge users are assigned the orthogonal pilots because these users are severely affected by interference. Consequently, the pilot overhead is reduced and inter-cell interference (ICI) is minimized. Further, results verify that the proposed schemes outperform the previous proposed traditional schemes, in terms of improved sum rates.

scholarly journals Performance analysis of massive multiple input multiple output for high speed railway

2021 ◽  
Vol 11 (6) ◽  
pp. 5180
Author(s):  
Maharshi K. Bhatt ◽  
Bhavin S. Sedani ◽  
Komal Borisagar
Keyword(s):  
Wireless Communication ◽  
Massive Mimo ◽  
High Speed ◽  
Communication Channel ◽  
Multiple Input Multiple Output ◽  
High Mobility ◽  
Data Rate ◽  
High Speed Train ◽  
Multiple Input ◽  
Input Multiple Output

This paper analytically reviews the performance of massive multiple input multiple output (MIMO) system for communication in highly mobility scenarios like high speed Railways. As popularity of high speed train increasing day by day, high data rate wireless communication system for high speed train is extremely required. 5G wireless communication systems must be designed to meet the requirement of high speed broadband services at speed of around 500 km/h, which is the expected speed achievable by HSR systems, at a data rate of 180 Mbps or higher. Significant challenges of high mobility communications are fast time-varying fading, channel estimation errors, doppler diversity, carrier frequency offset, inter carrier interference, high penetration loss and fast and frequent handovers. Therefore, crucial requirement to design high mobility communication channel models or systems prevails. Recently, massive MIMO techniques have been proposed to significantly improve the performance of wireless networks for upcoming 5G technology. Massive MIMO provide high throughput and high energy efficiency in wireless communication channel. In this paper, key findings, challenges and requirements to provide high speed wireless communication onboard the high speed train is pointed out after thorough literature review. In last, future research scope to bridge the research gap by designing efficient channel model by using massive MIMO and other optimization method is mentioned.

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>

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.

scholarly journals Effects of Path Visibility on Urban MIMO Systems

1970 ◽  
Vol 5 (1) ◽  
pp. 22-30
Author(s):  
Sirichai Hemrungrote ◽  
Toshikazu Hori ◽  
Mitoshi Fujimoto ◽  
Kentaro Nishimori
Keyword(s):  
Channel Capacity ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Propagation Characteristics ◽  
Simple Method ◽  
Limited Bandwidth ◽  
Multiple Input ◽  
Input Multiple Output

Multiple-Input Multiple-Output (MIMO) wireless communication technology is expected to improve the channel capacity over the limited bandwidth of existing networks. Since urban MIMO systems have complex propagation characteristics, the channel capacity cannot be estimated using a simple method. Hence, we introduce channel capacity characteristics to urban MIMO systems by using a combination of imaging and ray-launching methods as a ray-tracing scheme. A simulation based on these methods with variable parameters can reproducibly estimate various urban propagation characteristics and discriminate the effects of the urban model and antenna configurations. The characteristics of the Signal-to-Noise Ratio (SNR), the channel capacity, the spatial correlation, as well as the path visibility are then determined from the results of the simulation. The parameter called path visibility introduced in our previous study is considered again herein. We clarify that only this single parameter can be used to determine the channel capacity characteristics in urban MIMO scenarios. This parameter also provides guidance in determining the appropriate range for the base station (BS) height.

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.

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.

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