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 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 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>

Channel capacity evaluation for a multiple-input-multiple-output terminal in the presence of user's hand

2007 ◽  
Vol 1 (6) ◽  
pp. 1137 ◽  
Author(s):  
T. Zervos ◽  
K. Peppas ◽  
F. Lazarakis ◽  
A.A. Alexandridis ◽  
K. Dangakis ◽  
...  
Keyword(s):  
Channel Capacity ◽  
Multiple Input Multiple Output ◽  
Output Terminal ◽  
Capacity Evaluation ◽  
Multiple Input ◽  
Input Multiple Output

scholarly journals Gaussian MIMO relay channel with orthogonal channel components

2020 ◽  
Vol 71 (3) ◽  
pp. 222-226
Author(s):  
Zouhair Al-qudah
Keyword(s):  
Channel Model ◽  
Multiple Input Multiple Output ◽  
Relay Channel ◽  
Numerical Examples ◽  
Mimo Relay ◽  
Multiple Input ◽  
Communication Devices ◽  
Input Multiple Output ◽  
Theoretical Results

AbstractThe Gaussian multiple-input multiple-output (MIMO) orthogonal relay channel (ORC) is investigated. The transmission from source to relay is done over a channel that is orthogonal to source-destination and relay-destination channels. Practically, this assumption is made such that many communication devices from different technologies are exploited in relaying the source’s signal into its destination. For this channel model, the capacity is initially derived. Thereafter, we propose a transmission algorithm to achieve the derived capacity. Further, to support our theoretical results, many numerical examples are presented.

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