scholarly journals A Tradeoff between Rich Multipath and High Receive Power in MIMO Capacity

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
Zimu Cheng ◽  
Binghao Chen ◽  
Zhangdui Zhong
Keyword(s):  
Channel Capacity ◽  
Channel Model ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Mimo Channel ◽  
Channel Condition ◽  
Multiple Input ◽  
Two Factors ◽  
Input Multiple Output ◽  
Interesting Discussion

A discussion about which of the two factors, rich multipath (in NLOS) or signal-to-noise ratio (SNR) (usually in LOS), affects the Multiple-Input Multiple-Output (MIMO) channel capacity more is presented in this paper. This interesting discussion is investigated by performing simulations using simple circle scatterer model and WINNER II channel model. And the simulation shows that these two factors behave differently as the channel condition varyies. When the scatterer number in channel is low, the high receive SNR is more important to capacity. The multipath richness will have greater influence when the scatterer number exceeds a certain threshold. However, the channel capacity will not change much as the scatterers continue to increase.

scholarly journals Use Hierarchical Codebook to Improve the Primary User Detection in the Cognitive Radio’s Cooperative Spectrum Sensing

2021 ◽  
Vol 5 (6) ◽  
pp. 22-28
Author(s):  
Hoai Trung Tran
Keyword(s):  
Spectrum Sensing ◽  
Channel Model ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Primary User ◽  
Mimo Channel ◽  
High Signal ◽  
Secondary Users ◽  
Input Multiple Output

Currently, the cognitive network is receiving much attention due to the advantages it brings to users. An important method in cognitive radio networks is spectrum sensing, as it allows secondary users (SUs) to detect the existence of a primary user (PU). Information of probability of false detection or warning about the PU is sent to a fusion center (FC) by the SUs, from which the FC will decide whether or not to allow the SUs to use the PU spectrum to obtain information. The transmission of information with a high signal to noise ratio (SNR) will increase the FC's ability to detect the existence of the PU. However, researchers are currently focusing on probabilistic formulas assuming that the channel is known ideally or there is nominal channel information at the FC; moreover, one model where the FC only knows the channel correlation matrix. Furthermore, studies are still assuming this is a simple multiple input – multiple output (MIMO) channel model but do not pay much attention to the signal processing at the transmitting and receiving antennas between the SUs and the FCs. A new method introduced in this paper when combining beamforming and hierarchical codebook makes the ability to detect the existence of the PU at the FC significantly increased compared to traditional methods.

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 PENGARUH PENYUSUNAN POLARISASI PADA SISTEM ANTENA MIMO TERHADAP KAPASITAS KANAL

2020 ◽  
Vol 5 (1) ◽  
pp. 13
Author(s):  
Abdurrahman Rizki ◽  
Alloysius Adya Pramudita ◽  
Trasma Yunita
Keyword(s):  
Circular Polarization ◽  
Channel Capacity ◽  
Mimo System ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Antenna System ◽  
Mimo Antenna ◽  
Left Hand ◽  
Multiple Input ◽  
Input Multiple Output

Multiple Input Multiple Output (MIMO) system is a technology that has the potential to be developed to increase channel capacity. The increase in channel capacity in the MIMO system is not only determined by the number of antennas, but is determined by the characteristics and arrangement of the antenna concept. This study identifies the effect of circular polarization on the MIMO antenna system on channel capacity. Co-polarization consists of a Left Hand Circular Polarization (LHCP) and Right Hand Circular Polarization (RHCP) configuration, while cross-polarization consists of an RHCP-LHCP configuration. The co-polarization of the antenna with the LHCP configuration results in an estimated channel capacity of 11,578 bps / Hz when it is at the lowest Signal to Noise Ratio (SNR) is 5 dB

scholarly journals Capacity Analysis of Multiple-input-multiple-output System Over Rayleigh and Rician Fading Channel

2019 ◽  
Vol 3 (2) ◽  
pp. 70-74
Author(s):  
Yazen Saifuldeen Mahmood ◽  
Ghassan Amanuel Qasmarrogy
Keyword(s):  
Channel Capacity ◽  
Transmission Rate ◽  
Mimo System ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Ergodic Capacity ◽  
Rician Fading ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Water Filling Algorithm

This paper aims to analyze the channel capacity in terms of spectral efficiency of a multiple-input-multiple-output (MIMO) system when channel state information (CSI) is known using water-filling algorithm and unknown at the transmitter side which it has been shown that the knowledge of the CSI at the transmitter enhancing the performance, the random Rayleigh and Rician channel models are assumed. Ergodic capacity and outage probability are the most channel capacity definitions which are investigated in this study. MATLAB code is devised to simulate the capacity of MIMO system for different numbers of antenna nodes versus different signal-to-noise ratio (SNR) values. In addition, the outage capacity probabilities for vary transmission rate and SNR are discussed.

scholarly journals Capacity of Magnetic-Induction MIMO Communication for Wireless Underground Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Song Li ◽  
Yanjing Sun ◽  
Wenjuan Shi
Keyword(s):  
Sensor Networks ◽  
Channel Capacity ◽  
Magnetic Induction ◽  
Channel Model ◽  
Multiple Input Multiple Output ◽  
Promising Alternative ◽  
Mimo Communication ◽  
Single Output ◽  
Multiple Input ◽  
Input Multiple Output

In underground sensor networks, electronic magnetic waves undergo severe fading due to the challenging environment. Magnetic-induction (MI) communication is a promising alternative physical layer technique for underground sensor networks. In this paper, we solve the intercoil crosstalk in magnetic-induction multiple-input multiple-output (MI MIMO) communication and investigate the channel capacity for underground MI MIMO wireless communication. Firstly, considering mutual induction between each two coils, we analyze the capacity of magnetic-induction channel. Secondly, the channel model of magnetic-induction multiple-input single-output (MISO) is introduced and a novel coil deployment method is proposed to reduce the crosstalk in MI MISO communication. Finally, the capacity of MI MISO communication and MI MIMO communication is deduced by the proposed coil deployment method. Simulation shows that the channel capacity would increase significantly in high SNR regime for underground MI MIMO communication.

scholarly journals MIMO Fading Emulator Development with FPGA and Its Application to Performance Evaluation of Mobile Radio Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Yoshio Karasawa ◽  
Katsuhiro Nakada ◽  
Guijiang Sun ◽  
Rikako Kotani
Keyword(s):  
Channel Model ◽  
Multiple Input Multiple Output ◽  
New Developments ◽  
Performance Limit ◽  
Stage Scheme ◽  
Mobile Radio Systems ◽  
Multiple Input ◽  
Field Programmable ◽  
Input Multiple Output ◽  
Radio Systems

We present four new developments for a multiple-input multiple-output (MIMO) over-the-air measurement system based on our previous studies. The first two developments relate to the channel model for multipath environment generation. One is a further simplification of the circuit configuration without performance degradation by reducing the number of delay generation units, which dominate the performance limit when implementing the circuit on a field-programmable gate array (FPGA). The other is to realize spatial correlation characteristics among the input ports on the transmission side, whereas the previously proposed channel model did not consider this correlation. The third development involves the details of implementing the MIMO fading emulator on an FPGA as a two-stage scheme. The fourth is the demonstration of application examples of the developed system.

scholarly journals Channel capacity and performance evaluation of precoded MIMO-OFDM system with large-size constellation

2019 ◽  
Vol 9 (6) ◽  
pp. 5024
Author(s):  
Hussein A. Leftah ◽  
Huda N. Alminshid
Keyword(s):  
Fading Channels ◽  
Channel Capacity ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Ofdm System ◽  
Large Size ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Ofdm ◽  
And Performance

<p>Multiple input-multiple output (MIMO) is a multipath diversity exploring approach which is emerged with orthogonal frequency division multiplexing (OFDM) to produce MIMO-OFDM that is widely used in wireless communications. This paper presents a discrete Hart-ley transform (DHT) precoded MIMO-OFDM system over multipath frequency-selective fading channel with large-size quadrature amplitude modulation (16-QAM, 64-QAM and 256-QAM). A mathematical models for the BER and channel capacity over mutlipath fading channels are also derived in this paper. Average Bit-error-rate (BER) and channel capacity of the presented system is considered and compared with that of the traditional MIMO-OFDM. Simulation results shows that the transmission performance and channel capacity of the proposed schemes is better than that of the traditional MIMO-OFDM without a pre-coder.</p>

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