scholarly journals Capacity comparison of MIMO and cooperative MIMO

2017 ◽  
Vol 7 (1.1) ◽  
pp. 638
Author(s):  
Ashish Kumar Sarangi ◽  
Amrit Mukherjee ◽  
Amlan Datta
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
High Capacity ◽  
High Data ◽  
Cooperative Mimo ◽  
Main Requirement ◽  
Data Rates ◽  
Multiple Input ◽  
Input Multiple Output

To achieve high capacity and high data rates is the main requirement for today’s generation. This paper studies about the performance and capacity comparison of MIMO and cooperative MIMO systems. The comparison of capacity between multiple- input- multiple- output (MIMO) and cooperative MIMO systems helps us to know that which system have better performance and better capacity. The simulation results shows that among SISO, SIMO, MISO and MIMO  system the capacity of MIMO will be better but in between MIMO and cooperative MIMO, Cooperative MIMO system have high capacity than MIMO systems.  

PERFORMANCE EVALUATION OF TRANSMISSION FOR MULTIUSER MIMO BROADCAST CHANNEL

2016 ◽  
Vol 78 (5-7) ◽  
Author(s):  
Mohd Syarhan Idris ◽  
Nur Idora Abdul Razak ◽  
Azlina Idris ◽  
Ruhani Ab Rahman
Keyword(s):  
Mimo System ◽  
Multiple Input Multiple Output ◽  
System Capacity ◽  
Broadcast Channel ◽  
High Data ◽  
Dirty Paper Coding ◽  
Percentage Improvement ◽  
Data Rates ◽  
Multiple Input ◽  
Input Multiple Output

Multiple Input Multiple Output (MIMO) system has been brought a great improvement in spectral efficiency and the system capacity by serving multiple users simultaneously. The mathematical model of downlink Multi-user MIMO system and its capacity has been presented as well as different precoded transmission schemes. It is to implementing the downlink MU-MIMO system, such as channel inversion (CI), block diagonalization (BD), dirty paper coding (DPC) and tomlinsonharashimaprecoding (THP). It is because, in wireless and mobile communication system has been requires a reliable transmission of high data rates under various channel type different scenarios and reduce MU interference in the system.   These compares the method of transmission for broadcast channel (BC) and propose the best one method that outperforms existing technique with percentage improvement from the worst performance.

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.

scholarly journals An Evaluation of Successive Pilot Decontamination in Massive MIMO

2018 ◽  
Vol 39 (2) ◽  
pp. 107
Author(s):  
Victor Croisfelt Rodrigues ◽  
Taufik Abrão
Keyword(s):  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Pilot Training ◽  
Pilot Contamination ◽  
Fundamental Issue ◽  
Data Rates ◽  
Multiple Input ◽  
Input Multiple Output

The demand for higher data rates can be satisfied by the spectral efficiency (SE) improvement offered by Massive multiple-input multiple-output (M-MIMO) systems. However, the pilot contamination remains as a fundamental issue to obtain the paramount SE in such systems. This propitiated the research of several methods to mitigate pilot contamination. One of these procedures is based on the coordination of the cells, culminating in proposals with multiple pilot training phases. This paper aims to expand the results of the original paper, whereby the concepts of large pilot training phases were offered. The evaluation of such method was conducted through more comprehensible numerical results, in which a large number of antennas were assumed and more rigorous SE expressions were used. The channel estimation approaches relying on multiple pilot training phases were considered cumbersome for implementation and an uninteresting solution to overcome pilot contamination; contradicting the results presented in the genuine paper.

scholarly journals 3D Multiple Input Multiple Output Large-Scale Antenna Systems

2020 ◽  
Vol 55 (6) ◽  
Author(s):  
Saif Saad Hameed ◽  
Fouad H. Awad ◽  
Adnan Yousif Dawod ◽  
Ayoob Abdulmunem Abdulhameed
Keyword(s):  
Large Scale ◽  
Random Noise ◽  
Multiple Input Multiple Output ◽  
Least Square ◽  
Noise Sources ◽  
Estimation Algorithms ◽  
High Data ◽  
Data Rates ◽  
Multiple Input ◽  
Input Multiple Output

The channel could be evaluated by utilizing several estimation algorithms. The various patterns of pilot arrangements for the channel appreciation are a huge problem in channel appreciation techniques since all the processes depends on it; this paper discusses improvements in channel selection. The Least Square and Least Square Mean methods are common, simple ways to begin to estimate a channel; however, they are less efficient than more complex approaches. Due to the boost in demand with high data rates in communications, developers continue to invent new methods and mechanisms to adjust the capacity and the accuracy of the communication network. One of the primary troubles in wireless communication is the communication channel, which is affected by nonlinear and random noise sources, which decrease the quality of the service on the network; in this case, the channel must be equalized to increase performance with minimal error. In this paper, a Massive Multiple Input Multiple Output was designed and simulated in order to estimate the channel and the performance of the network through using Least Square and Least Square Mean.

Adaptive MIMO Systems with High Spectral Efficiency

2009 ◽  
pp. 286-307 ◽  
Author(s):  
Zhendong Zhou ◽  
Branka Vucetic
Keyword(s):  
Spectral Efficiency ◽  
Adaptive System ◽  
Mimo Systems ◽  
Mimo System ◽  
Adaptive Modulation ◽  
Multiple Input Multiple Output ◽  
Adaptive Modulation And Coding ◽  
Multiple Input ◽  
High Spectral Efficiency ◽  
Input Multiple Output

This chapter introduces the adaptive modulation and coding (AMC) as a practical means of approaching the high spectral efficiency theoretically promised by multiple-input multiple-output (MIMO) systems. It investigates the AMC MIMO systems in a generic framework and gives a quantitative analysis of the multiplexing gain of these systems. The effects of imperfect channel state information (CSI) on the AMC MIMO systems are pointed out. In the context of imperfect CSI, a design of robust near-capacity AMC MIMO system is proposed and its good performance is verified by simulation results. The proposed adaptive system is compared with the non-adaptive MIMO system, which shows the adaptive system approaches the channel capacity closer.

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 A Fast Adaptive Receive Antenna Selection Method in MIMO System

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Chaowei Wang ◽  
Weidong Wang ◽  
Cheng Wang ◽  
Shuai Wang ◽  
Yang Yu
Keyword(s):  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
System Capacity ◽  
Adaptive Antenna ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Hardware Costs ◽  
Receive Antenna

Antenna selection has been regarded as an effective method to acquire the diversity benefits of multiple antennas while potentially reduce hardware costs. This paper focuses on receive antenna selection. According to the proportion between the numbers of total receive antennas and selected antennas and the influence of each antenna on system capacity, we propose a fast adaptive antenna selection algorithm for wireless multiple-input multiple-output (MIMO) systems. Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory requirement and achieves considerable system capacity gain compared with the optimal selection technique in the same time.

A Comparison of Norm Based Antenna Selection and Random Antenna Selection with Regard to Energy Efficiency in Wireless System with Large Number of Users

2020 ◽  
Vol 10 (2) ◽  
pp. 189-196
Author(s):  
Ashu Taneja ◽  
Nitin Saluja
Keyword(s):  
Energy Efficiency ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Transmit Antenna Selection ◽  
Wireless System ◽  
Multiple Input ◽  
Input Multiple Output

Background: The paper considers the wireless system with large number of users (more than 50 users) and each user is assigned large number of antennas (around 200) at the Base Station (BS). Objective: The challenges associated with the defined system are increased power consumption and high complexity of associated circuitry. The antenna selection is introduced to combat these problems while the usage of linear precoding reduces computational complexity. The literature suggests number of antenna selection techniques based on statistical properties of signal. However, each antenna selection technique suits well to specific number of users. Methods: In this paper, the random antenna selection is compared with norm-based antenna selection. It is analysed that the random antenna selection leads to inefficient spectral efficiency if the number of users are more than 50 in Multi-User Multiple-Input Multiple Output (MU-MIMO) system. Results: The paper proposes the optimization of Energy-Efficiency (EE) with random transmit antenna selection for large number of users in MU-MIMO systems. Conclusion: Also the computation leads to optimization of number of transmit antennas at the BS for energy efficiency. The proposed algorithm results in improvement of the energy efficiency by 27% for more than 50 users.

scholarly journals Comparison of Semidefinite Relaxation Detectors for High-Order Modulation MIMO Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Z. Y. Shao ◽  
S. W. Cheung ◽  
T. I. Yuk
Keyword(s):  
Computational Complexity ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Semidefinite Relaxation ◽  
Attractive Alternative ◽  
Computationally Efficient ◽  
Multiple Input ◽  
Key Technologies ◽  
Input Multiple Output

Multiple-input multiple-output (MIMO) system is considered to be one of the key technologies of LTE since it achieves requirements of high throughput and spectral efficiency. The semidefinite relaxation (SDR) detection for MIMO systems is an attractive alternative to the optimum maximum likelihood (ML) decoding because it is very computationally efficient. We propose a new SDR detector for 256-QAM MIMO system and compare its performance with two other SDR detectors, namely, BC-SDR detector and VA-SDR detector. The tightness and complexity of these three SDR detectors are analyzed. Both theoretical analysis and simulation results demonstrate that the proposed SDR can provide the best BLER performance among the three detectors, while the BC-SDR detector and the VA-SDR detector provide identical BLER performance. Moreover, the BC-SDR has the lowest computational complexity and the VA-SDR has the highest computational complexity, while the proposed SDR is in between.

scholarly journals Performance Analysis of TAS/SC as well as TAS/MRC MIMO Techniques under α-μ Fading Channels

2019 ◽  
Vol 8 (3) ◽  
pp. 3272-3277
Keyword(s):  
Fading Channels ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Maximal Ratio Combining ◽  
Selection Combining ◽  
Transmit Antenna Selection ◽  
Multiple Input ◽  
Input Multiple Output

Multiple-Input-Multiple-Output (MIMO) system improves performance as well as the capacity of the wireless system. The use of large number of antennas in a MIMO system increases the hardware complexities and also its price. To overcome this, MIMO systems that activate single transmit antenna at a time, namely transmit antenna selection (TAS) is considered in this paper. Selection combining (SC) and Maximal ratio combining (MRC) are carried out at the receiver over    fading channels. Expressions for outage probability and average bit error rate (ABER) are derived considering TAS/SC as well as TAS/MRC MIMO systems. All the derived expressions are validated by Monte-Carlo simulation results.

Sign in / Sign up

Export Citation Format

Share Document