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Smart Antenna2


Zeina Kittaneh

on 6 January 2013

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Transcript of Smart Antenna2

Smart Antenna Prepared by: Shouq Mohaisen
Yaman Salem
Zeina Kittaneh Submitted To: Dr. Allam Mousa What is smart antenna ?
Types of Smart Antennas.
Why smart antenna ?
Forms of smart antenna technology.
Architecture of smart antenna.
Steering the Smart antenna (DOA).
The key technology of smart antenna (adaptive Beamforming).
Matlab Simulation.
Conclusion. Outline Switched beam & adaptive algorithms LMS adaptive Beamforming fixed the space between elements to 0.5 lamda
and tuned the number between elements N A Smart Antenna is an antenna system which dynamically reacts to its environment by using signal processing to provide better signals and frequency usage for wireless communications. What is Smart Antenna?
Increasing in Range & number of users.
More Secure.
Less Interference and more bandwidth. Why smart antenna? MIMO: In wireless communication systems it is used to increase spectral efficiency for a given total transmit power.

SIMO: Used to minimize errors and optimize data speed.
MISO: Aims to improve the transmission distance. Forms of smart antenna technology It has fixed beams covering a designated angular area, by dividing the sector into many narrow beams; each beam can be treated as an individual sector serving an individual user or a group of users. Types Of Smart Antennas They are able to dynamically react to the changing RF environment. it is controlled by signal processing which scans the radiation beam towards a desired mobile user. Types/ Cont: Switched Vs Adaptive The number of array elements should be relatively low to avoid high complexity.
the radio unit, which consists of down-conversion chains and analogue-to-digital conversion (A/D). Architecture of smart antenna. A reverse process of the reception part. The radio unit consists of (D/A) converters and the up-converter chains. Usually no smart antennas applied to the user terminals Architecture\ cont: Steering Smart Antenna It is provides the necessary phase shift for a linear antenna array. According to following following equation:

∆θ=±(2k−1) π/2N K∈[1,N] Begin by scanning the target region to determine direction produces the largest output power to estimate the desired signal’s direction.

Where: Adaptive Beamforming Used to form multiple beams towards desired users by adding the phases of the signals in the direction of the desired targets, while nulling the interferers through the adjustment of the beam-former's weight vectors. A non blind algorithm, Aims to adaptively produce weights that minimizes (MMSE) between a desired signal and the arrays output, In order to maximize reception in the direction of the desired signal. Matlab Simulation: parameters affecting smart antenna performance( design process ) With number of array = 16 and space between elements is variable LMS Simulation smart antenna uses (improved LMS )
Error figures: µ =.15 µ =.32 Currently Jawwal not using smart antenna , still sector antenna but there is a plan to implement it in the future.

Smart used for data transmissions and for 3 G, 4G, LTE technologies (in Palestine 2.75 G - EDGE)

Smart antenna correlated with the widely spreading of smart phones and the development of new services everyday. Jawwal Meeting Smart antenna is the best solution compared with traditional antenna(isotropic or directional), it increase the gain and reduces the interference, etc.

Using special techniques and algorithms : DOA, adaptive (Butler) or switched (Bartlet) beamforming algorithms.

Types of smart antenna switched and adaptive.

The effect of changing 2 parameters N,d on the performance of smart antenna.

In Palestine still not used. Conclusion The Bartlett Method (Adaptive Type (DOA estimation) The Butler Method (For Switched Type:) H is the conjugate transpose and w(n+1) = w(n) + µx(n)e*(n) Switched Beam Systems: Adaptive Array Systems: The Receiver Part: The Transmitter Part: w(n+1) = w(n) + x(n)e*(n) Any Question µ is variable , as we increase µ the error will be increase ,lead to faster convergence, less stable system 2nd trial The best result which achieves a good performance
N around 16,
d=.5 lamda d(n) training signal is sent by the transmitter to the receiver during the training period.
Beamformer in the receiver uses this information to compute new complex weight. Ex: LMS

Doesn't need any training sequence to update its complex vector. These algorithms use some of the known properties of the desired signal. Ex: Spectral self-Coherence Restoral (SCORE) Non-Blind adaptive algorithm: Blind adaptive algorithm
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