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.

scholarly journals Practical and Simple Wireless Channel Models for Use in Multipolarized Antenna Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
KwangHyun Jeon ◽  
Xin Su ◽  
Bing Hui ◽  
KyungHi Chang
Keyword(s):  
Channel Model ◽  
Mimo Systems ◽  
Wireless Channel ◽  
Spatial Multiplexing ◽  
Channel Models ◽  
Data Rates ◽  
Outdoor Environments ◽  
Wireless Channel Models ◽  
2D And 3D ◽  
Antenna Systems

The next-generation wireless systems are expected to support data rates of more than 100 Mbps in outdoor environments. In order to support such large payloads, a polarized antenna may be employed as one of the candidate technologies. Recently, the third generation partnership standards bodies (3GPP/3GPP2) have defined a cross-polarized channel model in SCM-E for MIMO systems; however, this model is quite complex since it considers a great many channel-related parameters. Furthermore, the SCM-E channel model combines the channel coefficients of all the polarization links into one complex output, making it impossible to exploit the MIMO spatial multiplexing or diversity gains in the case of employing polarized antenna at transmitter and receiver side. In this paper, we present practical and simple 2D and 3D multipolarized multipath channel models, which take into account both the cross-polarization discrimination (XPD) and the Rician factor. After verifying the proposed channel models, the BER and PER performances and throughput using the EGC and MRC combining techniques are evaluated in multipolarized antenna systems.

scholarly journals Performance Enhancement in SU and MU MIMO-OFDM Technique for Wireless Communication: A Review

2017 ◽  
Vol 7 (5) ◽  
pp. 2459
Author(s):  
S.N. Raut ◽  
R.M. Jalnekar
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Performance Enhancement ◽  
Mimo Systems ◽  
Mimo System ◽  
Wireless Systems ◽  
Multipath Fading ◽  
Data Rate ◽  
Spatial Multiplexing ◽  
Rician Fading

<p class="Default">The consistent demand for higher data rates and need to send giant volumes of data while not compromising the quality of communication has led the development of a new generations of wireless systems. But range and data rate limitations are there in wireless devices. In an attempt to beat these limitations, Multi Input Multi Output (MIMO) systems will be used which also increase diversity and improve the bit error rate (BER) performance of wireless systems. They additionally increase the channel capacity, increase the transmitted data rate through spatial multiplexing, and/or reduce interference from other users. MIMO systems therefore create a promising communication system because of their high transmission rates without additional bandwidth or transmit power and robustness against multipath fading. This paper provides the overview of Multiuser MIMO system. A detailed review on how to increase performance of system and reduce the bit error rate (BER) in different fading environment e.g. Rayleigh fading, Rician fading, Nakagami fading, composite fading.</p>

Performance of OQAM/GFDM in Spatial Multiplexing MIMO Systems

2020 ◽  
Vol 11 (2) ◽  
pp. 39-57
Author(s):  
Simon Wissam Tarbouche ◽  
Abdel-Nasser Assimi
Keyword(s):  
Interference Cancellation ◽  
Pulse Shaping ◽  
Matched Filter ◽  
Mimo Systems ◽  
Mimo System ◽  
Spatial Multiplexing ◽  
Frequency Division ◽  
Fifth Generation ◽  
Additional Processing ◽  
Simulation Results

Generalized frequency division multiplexing (GFDM) is a prominent candidate to be used by the mobile Fifth Generation (5G) physical layer. Nevertheless, the integration of GFDM with Spatial Multiplexing (SM) MIMO system is essential to fulfill the data rate requirements. SM detection of MIMO-GFDM becomes a more challenging topic because of ICI and ISI due to the non-orthogonal nature of GFDM, along with IAI. In this article, the authors propose a system that combines the Offset-Quadrature Amplitude Modulation (OQAM) with GFDM to mitigate self-induced interference, by using a simple Matched Filter (MF) detector and minimum additional processing at the receiver. Simulation results show a considerable achieved improvement in BER by the proposed OQAM/GFDM compared to QAM/GFDM when using MMSE-based Ordered Successive Interference Cancellation (OSIC) detector. Furthermore, this system is unaffected by the roll-off factor variations of used pulse-shaping filters.

scholarly journals Capacity Enhancement for the Vehicular Network using Spatial Multiplexing

2018 ◽  
Vol 7 (4.19) ◽  
pp. 772
Author(s):  
Hassan Hadi Saleh ◽  
Saad Talib Hasoon
Keyword(s):  
Road Safety ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Mimo Systems ◽  
Mimo System ◽  
Spatial Multiplexing ◽  
Intelligent Transport System ◽  
Spatial Reuse ◽  
Single Input Single Output

Vehicular Ad hoc Network (VANET) is an advanced system and subcategory of a Mobile Ad hoc Network (MANET), it has as the potential to significantly impact road safety and improve traffic by providing critical information to drivers on critical routes. The system can inform the driver of a local anomaly, which is a very short distance from the sensors. Data from this sensors can be passing between vehicles so as to increase awareness of this environment. Intelligent Transport System (ITS) applications will include traffic efficiency, comfort of driving and road safety. The transaction of warning messages exploits a limited capacity because these applications generate little separate messages. Estimating the capacity of the VANET is therefore essential, as it may limit the deployment or usefulness of these applications. Therefore, an estimate must be made in advance for application design with capacity limitations in mind. VANET capacity is limited mainly through spatial reuse.  Multiple-Input Multiple-Output (MIMO) structures have been suggested to replace the conventional systems. In MIMO systems, a much higher data rate can be achieved than in a VANET environment. The objectives of the paper to study the capacity of the VANET network associated with new promising MIMO technology. Spatial multiplexing (SM),utilizes the spatial dimension to maximizethe capacity of a link without expanding a bandwidth. The SM gain is achieved throughtransmitting signals concurrently on parallel channels spatially with the same frequency. Capacity calculated over VANETs environments with MIMO/SM techniques, using Rayleigh Fading Channel with BPSK modulation. The results of MATLAB simulation package 2017a, indicate the enhancement in the unit of bit per second per Hertz (b/s/Hz). A maximum capacity improvement for MIMO system over Single Input Single Output (SISO) was achieved by using (4 x 4) system, it is about 16.14 b/s/Hz.   

A Successive Iterative Optimal Pre-Coding Algorithm for Downlink Multi-User MIMO System

2012 ◽  
Vol 457-458 ◽  
pp. 1012-1018
Author(s):  
Xian Kun Gao ◽  
Jian Hua Qu ◽  
Chuan An Yao ◽  
Yong Chang Yu
Keyword(s):  
System Performance ◽  
Optimal Algorithm ◽  
Mimo System ◽  
Spatial Multiplexing ◽  
Considerable Improvement ◽  
The Other ◽  
Multiple Data ◽  
Simulation Results ◽  
Mimo Downlink ◽  
To Receive

Spatial multiplexing in the multi-user MIMO downlink allows each user in the system to receive multiple data subchannels simultaneously using the same time and spectral resources. In this paper, a successive iterative optimal algorithm based on signal-to-leakage-and-noise-ratio (SLNR) maximization algorithm is proposed, which make use of the unused subspace of some known users to improve the space gain of the other users and has no strict constraint on transmit and receive antennas numbers. According to the simulation results, the proposed algorithm outperforms the original SLNR algorithm, and has a considerable improvement in the system performance.

scholarly journals Combining Alamouti Scheme with Block Diagonalization Beamforming precoding for 5G Technology over Rician Channel

2019 ◽  
pp. 22-28
Author(s):  
Cebrail Ciflikli
Keyword(s):  
System Performance ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Block Code ◽  
Spatial Diversity ◽  
Block Diagonalization ◽  
Combined System ◽  
Alamouti Scheme ◽  
Input Multiple Output ◽  
Rician Channel

Wireless communication faces a number of adversities and obstacles as a result of fading and co-channel interference (CCI). Diversity with beamformer techniques may be used to mitigate degradation in the system performance. Alamouti space-time-block-code (STBC) is a strong scheme focused on accomplishing spatial diversity at the transmitter, which needs a straightforward linear processing in the receiver. Also, high bit-error-rate (BER) performance can be achieved by using the multiple-input multiple-output (MIMO) system with beamforming technology. This approach is particularly useful for CCI suppression. Exploiting the channel state information (CSI) at the transmitter can improve the STBC through the use of a beamforming precoding. In this paper, we propose the combination between Alamouti STBC and block diagonalization (BD) for downlink multi-user MIMO system. Also, this paper evaluates the system performance improvement of the extended Alamouti scheme, with the implementation of BD precoding over a Rayleigh and Rician channel. Simulation results show that the combined system has performance better than the performance of beamforming system. Also, it shows that the combined system performance of extended Alamouti outperforms the combined system performance without extended Alamouti. Furthermore, numerical results confirm that the Rician channel can significantly improve the combined system performance.

scholarly journals Impact of Hardware Impairment Analysis on Channel Capacity Bounds of MIMO Antenna Configurations

2020 ◽  
Vol 9 (3) ◽  
pp. 1981-1985
Keyword(s):  
Channel Capacity ◽  
System Performance ◽  
Communication Systems ◽  
Mimo Systems ◽  
Mimo System ◽  
Mimo Antenna ◽  
Hardware Impairments ◽  
Hardware Impairment ◽  
The Impact ◽  
Capacity Performance

with the increasing demand f the higher data reates the utilization of the MIMO system have exponentially increased in the cellular communication systems. There are many reasons due to which the performance of the MIMO systems degrades in real time. The major challenge is the any kind of noise or erro in the system due to hardware issues and problems. The any kind of hardware error is called as hardware impairment in the systems. These impairments are represented by Kapa values in the systems. Paper is primarily focused to define and evaluate the impact of the hardware impairment on the system performance of MIMO. The paper first defines the basic MIMO systems antenna configurations and then the channel capacity performance is compared with and without hardware impairments. the antenna configurations depends on the number of input and output antenna in the system. As the number of antennas increases the probability of having hardware impairment also increases. This may reduce the capacity performance significantly. New channel capacity formulation is given for antenna configurations. Paper evaluated the performance under the different channel sizes on the capacity. Finally the capacity of the channel is plotted as the function of the different Signal to noise ratios. It is concluded the MIMO system performance is degraded under the presence of the hardware impairments.

scholarly journals A Survey on Multi-Layer Mimo for Lte/Lte-Advanced

2018 ◽  
Vol 7 (3.34) ◽  
pp. 234
Author(s):  
Anjana Devi.J ◽  
Dr R. Dhaya ◽  
Dr R. Kanthavel
Keyword(s):  
System Performance ◽  
Massive Mimo ◽  
Mimo System ◽  
Spatial Diversity ◽  
Multiple Streams ◽  
Key Technology ◽  
Main Design ◽  
Lte Advanced ◽  
Lower Complexity ◽  
Mimo Technology

The primary intention of the paper is to explore on various Multi-Layer MIMO approaches for the higher system performance. MIMO technique is said to be the key technology in LTE-A to achieve the spatial diversity in the system. Multi-Layer MIMO is the enhancement to the MIMO technology where multiple streams of data could be transferred to different layers for optimization with increased capacity in the network in high SNR condition. In a massive MIMO system, the cell interference hinders the system performance due to high channel dimensionality. The main design objective of the Multi-Layer MIMO techniques studied is to reduce the Cell Interference with lower complexity.  

On the Performance and Analysis of Massive MIMO for 5G Wireless Systems

2021 ◽  
Author(s):  
◽  
Callum Thomas Neil
Keyword(s):  
Spatial Correlation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Wireless Systems ◽  
Technical Solution ◽  
Channel Models ◽  
Channel Matrix ◽  
Wide Range ◽  
Processing Techniques

<p>A novel technical solution, and paradigm shift, envisioned to achieve the significant spectral efficiency enhancements required for Fifth Generation (5G) wireless systems is massive multiple-input-multiple-output (MIMO). Massive MIMO systems scale up the number of transmit (TX) and receive (RX) antennas by at least an order of magnitude relative to conventional multi-user MIMO systems, which have been a key feature in current wireless standards, such as Long Term Evolution. Thus, massive MIMO leverages the spatial dimension by providing significant increases in all the virtues of conventional MIMO systems but on a much larger scale. Namely, data rate, link reliability, energy efficiency, and multiplexing gains can all be increased with massive MIMO systems, while simultaneously reducing inter-user interference through digital processing techniques. Further motivating the surge in research of massive MIMO systems are the additional channel properties which occur when operating with large dimensions. These properties arise as a result of random matrix theory asymptotics and under these conditions random variables become deterministic, simplifying analysis and allowing simple processing techniques to become (near) optimal. These idealistic properties, however, are based on the assumptions of an independent and identically distributed channel matrix with an infinite number of TX antennas.  Physical contraints typically prohibit the deployment of large numbers of TX antennas. It therefore seems natural to determine the number of TX antennas required for large MIMO systems to begin to exhibit these favourable asymptotic properties. Analytically deriving the first and second moments of the composite Wishart channel matrix and numerically defining three convergence metrics, the rate of channel convergence is examined. Limiting matched-filter (MF) and zero-forcing precoding signal-to-interference-plus-noise-ratio (SINR) performances are then analytically derived and rate of convergence shown. Coordinated distributed MIMO systems can mitigate the detrimental effects of spatial correlation relative to a colocated MIMO system. The instantaneous and limiting MF SINR performance of a distributed massive MIMO system is derived, allowing clear insights into the effects of imperfect channel state information, spatial correlation, link gains and number of antenna clusters. The wide bandwidths vacant at millimeter-wave (mmWave) frequency bands are suitable for 5G wireless systems since they occupy regions of uncongested spectrum which enable large contiguous bandwidth carriers. Spatial correlation of an arbitrary antenna array topology is analytically derived for a mmWave channel model. Numerically, the effects of mutual coupling amongst antenna elements is then shown on the effective spatial correlation, eigenvalue structure and user rate of different antenna topologies.   Channel models and measurements across a wide range of candidate bands for 5G wireless systems are then considered, motivated by the different propagation and spatial characteristics between different bands and different channel models within the same band. Key channel modelling and spatial parameter differences are identified and, in turn, their impact on various antenna topologies investigated, in terms of system sum rate, channel eigenvalue structure, effective degrees of freedom and massive MIMO convergence properties.</p>

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