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MIMO channel parameter extraction

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abhishek

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labview mimo

Hi,

I am looking to extract MIMO channel parameters namely Correlation at transmitter and receiver using ray tracing simulations. If anyone knows anything in this regard it will be of great help to me.

Thanks in advance
Abhishek
 

mimo labview

Thanks for your help. The above link is just basic information about MIMO which I already have. I am looking for something more specific. If anyone knows it please let me know. I really need this information asap.

thanks
Abhishek
 

differentiate multiple and simple extraction

COMPLETE MIMO-OFDM SIMULATION IN LABVIEW INCLUDING CHANNEL ESTIMATION ALGORITHMS


[b]MIMO-OFDM Design using LabVIEW[/b]


https://www.ece.utexas.edu/~jandrews/molabview.html


Orthogonal Frequency Division Multiplexing (OFDM) is one of the most promising physical layer technologies for high data rate wireless communications due to its robustness to frequency selective fading, high spectral effciency, and low computational complexity. OFDM can be used in conjunction with a Multiple-Input Multiple-Output (MIMO) transceiver to increase the diversity gain and/or the system capacity by exploiting spatial domain. Because the OFDM system effectively provides numerous parallel narrowband channels, MIMO-OFDM is considered a key technology in emerging high-data rate systems such as 4G, IEEE 802.16, and IEEE 802.11n.

MIMO communication uses multiple antennas at both the transmitter and receiver to exploit the spatial domain for spatial multiplexing and/or spatial diversity.

Spatial multiplexing has been generally used to increase the capacity of a MIMO link by transmitting independent data streams in the same time slot and frequency band simultaneously from each transmit antenna, and differentiating multiple data streams at the receiver using channel information about each propagation path.

In contrast to spatial multiplexing, the purpose of spatial diversity is to increase the diversity order of a MIMO link to mitigate fading by coding a signal across space and time so that a receiver could receive the replicas of the signal and combine those received signals constructively to achieve a diversity gain.



LabVIEW Resources for MIMO and OFDM simulation

LabVIEW MIMO-OFDM simulator with variable pilot-to-data power ratio (PDPR)

In MIMO-OFDM systems, channel state information (CSI) is essential at the receiver in order to coherently detect the received signal and to perform diversity combining or spatial interference suppression. The channel is very important to the performance of diversity schemes, and more variable channels give more diversity. Thus, in order to attain accurate CSI at the receiver, pilot-symbol-aided or decision-directed channel estimation must be used to track the variations of the frequency selective fading channel. Among the various resources in MIMO multicarrier systems the power assignment is related to the accuracy of the channel estimation. Pilot symbols facilitate channel estimation, but in addition to consuming bandwidth, they reduce the transmitted energy for data symbols per OFDM symbol under a fixed total transmit power condition. This suggests a tradeoff between the system capacity and the accuracy of the channel estimation in MIMO-OFDM systems according to the power allocation when the total transmit power is fixed.

In order to model the MIMO-OFDM system in a graphical and fast simulation, we have developed the MIMO-OFDM simulator in the LabVIEW simulation package from National Instruments. By using this simulator, one can see the bit errror rate (BER) performance of the system and the channel capacity lower bound according to a given PDPR with three different types of pilot patterns.

Click here to download the LabVIEW library (mimoofdm.llb). You can access the tutorial (pdf version) of this LabVIEW simulator by clicking here. The simulation library contains about 20 sub VI's which can be reused for similar applications.

This MIMO-OFDM simulator was developed under the guidance of Dr. Jeffrey G. Andrews by Taeyoon Kim.



Types of VIs contained in the simulation library are briefly explained:

* Pilot Sequence Generator: Three types of pilot patterns generator for MIMO-OFDM systems is implemented. To guarantee the orthogonality between channels, pilot symbols should be orthogonal in either time, frequency, or code. This generator is fixed for 4 pilot symbols per an OFMD symbol, however, it can be changed to other numbers by simple modification.
*
Random Bit Generator and symbol mapper/demapper: Simple VI's which generate random bit according to the input value and mapping bits to BPSK/QPSK symbols and vice versa.
*
Pilot-to-data Power Ratio (PDPR) VIs: Vi's which generate optimal PDPR value and pilot/data tone power according to the PDPR for various MIMO-OFDM system configurations are developed.
*
Subcarrier Allocator: The VI is used to allocate pilot and data symbols for three different pilot patterns with given pilot power and data power.
* MIMO-OFDM Transmitter: The VI generates MIMO-OFDM symbols in either time and frequency domain according to a given pilot pattern and PDPR.
* Channel and Noise: The VI is used to generate multipath Rayleigh fading channel and AWGN noise according to input values such as the number of channel taps and SNR.
* MIMO-OFDM Receiver: The MMSE receiver VI for MIMO-OFDM systems. It also includes the part which can calculate the channel capacity lower bound with channel estimation error. Thus, this VI shows the BER performance and the channel capacity lower bound.
* MMSE Channel Estimator: The VI is used to estimate MIMO-OFDM channel in a MMSE way according to three different types of pilot patterns (independent, scattered, and orthogonal pilot patterns).
* 2D-DFT Matrix Generator: Simple VI which generates 2D-DFT matrix of any size according to input values.



Other LabVIEW resources for MIMO and OFDM systems

There are some other LabVIEW simulation toolkits for MIMO and OFDM systems.

You can download the LabVIEW MIMO toolkit develped by Prof. Heath's research group. This tool kit offers a flexible tool to simulate MIMO systems.

Also, there is an IEEE 802.16a simulator developed by Prof. Evans' research group. It provides a graphical user interface and basic functionality of an IEEE 802.16a 256-subcarrier OFDM system. It is a discrete baseband simulation of the necessary modulation and demodulation functions, that operate over the Stanford University Interim (SUI) fixed broadband wireless access channel models. You can find more information from the link. [/i]
 

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