smart antenna presentation
TRANSCRIPT
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Elements of Smart Antenna System
In this section we will be dealing with some of the
basic principles behind smart antennas.
Smart Antenna Receiver The purpose of the receiver in smart antenna system is
to combine the received signals into one signal which is used as an input to the rest of the receiver components(such as the channel decoding unit for instance). It basically consists of four parts:
Array of antennas, Radio unit, Beam forming unit, and Signal processing unit.
These parts are illustrated in the figure below:
Cont
Figure Smart antenna receiver
Cont The radio unit consists of down conversion chains and
analog-to-digital converters (A/D). In this part down conversion of received signals, from each elements of the array antenna, takes place. Based on the received signals, the signal processing unit calculate the complex weights with which the received signal from each of the array elements is multiplied. Depending on the optimization criterion, the weight calculating mechanisms may differ.
Cont
Switched beam(SB):- the receiver will test all the pre-defined weight vectors (corresponding to the beam set) and choose the one giving the strongest received signal level. Adaptive approach:- is concerned with maximization of the SIR(Signal to Interference Ratio). This is done by computing the optimum weight vector using algorithms such as optima combining, for instance.
Smart Antenna Transmitter The transmission part of the smart antenna system is
schematically very similar to the reception part. Here a single input signal is split into many branches, according to the number of array elements. This is clearly shown in the following figure:
Cont
Figure - Transmission part of smart antenna system
Cont
Figure - Transmission part of smart antenna system
Cont These split signals will then be weighted with the
complex weights, which are calculated by the signal processing unit, in the beam forming unit. The weights are used to decide the radiation pattern in the downlink direction. In the radio unit D/A and uplink conversions take
place.
Antenna Antenna elements are one of the essential components
of a smart antenna system. They convert electromagnetic waves into electrical impulses. They have important role in shaping and scanning the radiation pattern and constraining the adaptive algorithm used by the digital signal processing unit.
Array Design The main beam of a larger array can resolve
the signals-of-interest (SOIs) more accurately and allows the smart-antenna system to reject more signals-notof-interest (SNOIs). However, this brings two main disadvantages:
Increased cost and complexity of the hardware implementation Increased convergence time for the adaptive algorithms, thereby reducing valuable bandwidth
Thus, a careful network analysis is required to resolve
these issues.
Linear Array It is an array with a group of radiating elements
configured in a straight line. A linear array of M even elements with uniform spacing placed along the y axis is shown below.
Figure - linear array with elements along the Y axis.
Cont For M number of identical array elements, the array
factor(AF) for the above linear array can be calculated as:
Which can be simplified to:
Cont Where:
- Phase excitation of the individualelements - Amplitude excitation of the individual elements d - The spacing between two consecutive elements
array
Cont The amplitude coefficients control the shape of the
pattern and the major-to-minor lobe level. The phase excitations control the scanning capabilities of the array. Therefore, an antenna designer can choose different amplitude distributions to conform to the application specifications.
Planar Array It is an array configuration that is well suited for
mobile communication. The planar arrays are more attractive, specially for mobile devices, because of their ability to scan in3-D space. It can scan the main beam in any direction of (elevation) and (azimuth). A planar array of M x N identical elements with uniform spacing positioned symmetrical in the x yplane is given below:
Cont
Figure Planar array with uniformly spaced components
Cont The array factor(AF) for this planar array with its maximum
along 0, 0, for an even number of elements in each direction can be calculated as:
where:
- amplitude excitation of each individual elements
Antenna BeamformingGeneral functions of smart antenna system: The direction of arrival of all the incoming signals are
estimated using DOA algorithm The desired user signal is identified and separated from
the rest of the unwanted incoming signals. A beam is steered in the direction of the desired signal
while placing nulls at interfering signal directions byconstantly updating the complex weights.20
ContThe information obtained by antenna arrays is applied via algorithms processed by (DSP). DSP has two objectives: To estimate the direction of arrival (DOA) of all
impinging signals To determine the appropriate weights to ideally steer the
maximum radiation of the antenna pattern toward the SOIand to place nulls toward the SNOI.21
Direction of Arrival (DOA) Algorithms The DOA algorithm determines the directions of all
incoming signals based on the time delays of incoming signals in all directions received by the antenna array. These time delays depend on the antenna geometry,
number of elements, and inter element spacing.
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Cont Time delay of planner array
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Cont Illustration of DOA estimation based on time delay
information.
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Cont
This clearly shows that the DOA can be determined
from the knowledge of the time delay between the twoelements.25
DOA estimation techniques The techniques can be categorized into two. Conventional methods Subspace-based methods
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Cont Conventional methods
The DOA is determined from the peaks of the output
power spectrum obtained from steering the beam in all possible directions. Do not exploit the statistics of the signal They have poor resolution i.e. the width of the main beam
and the height of the side lobes limits its ability to separateclosely spaced signals.27
Cont
Subspace Based Methods These methods, unlike conventional methods, exploit the structure of the received data. MUltiple SIgnal Classification (MUSIC) algorithm and the Estimation of Signal Parameters via
Rotational Invariance Technique (ESPRIT). MUSIC deals with the decomposition of covariance matrix into two orthogonal matrices, i.e., signalsubspace and noise-subspace. Assuming that noise in each channel is highly uncorrelated.28
Cont ESPRIT is another DOA estimation technique, based on
the fact that in the steering vector, the signal at one element is a constant phase shift from the earlier element. The
advantage
of
subspace
based
methods
over
conventional methods is their high resolution ESPRIT has advantage of being computationally less
intensive, requires less storage and does not involve an
exhaustive search through all possible steering vectors toestimate the DOA.29
Adaptive Beam forming Adaptive algorithm
process the information of DOA
algorithm to ideally steer the maximum radiation of theantenna pattern toward the SOI and place nulls in the pattern toward the SNOIs. For reference (or training) based adaptive beam forming
algorithms, (LMS), the adaptive beam forming algorithm does not need the DOA information but instead uses the reference signal, or training sequence.30
Cont Illustration of the basic concept of how the weights are computed to satisfy certain requirements of the pattern.
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Cont First the output y(t) of the array due to the desired signal p(t) is: y(t) = Pej0t ( w1 + w2) w1 + w2 = 1 On the other hand, the output y(t) due to the interfering signal n(t) is given as: y(t) = Ne j (0 t/4) w1 + Ne j (0 t+/4) w2
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Cont
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Cont
Thus, the above values of w1 and w2 are the
optimum weights that guarantee the maximum signalto interference ratio (SIR) for a desired signal at 0 =
0 and an interferer at 1 = 30.
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Cont The plot of array factor obtained on the basis of the weights derived above.
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Optimal Beam Forming Algorithms In optimal beam forming techniques, a weight vector
that minimizes a cost function is determined. This cost function is inversely associated with the
quality of the signal at the array output, so that whenthe cost function is minimized, the quality of the
signal is maximized at the array output.
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Cont One of the most widely used cost function is mean square error (MSE) based function.
Where dk represents the desired signal, rxd is cross correlation and Rxx is covariance. To minimize the cost function:
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Cont
Solving in terms of the weights, w, yields:
Wopt represents optimal antenna array weight vector that minimizes the cost function.
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Least Mean Square (LMS) Algorithm It is an algorithm used to determine the optimal
weight vector values. Thus, the LMS algorithm computes the weights iteratively as:
Where is the step size for the iteration.
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Cont The following figure shows implementation of LMS
algorithm.
The advantage of LMS is: It is a low complexity
algorithm i.e. it requires no direct matrix inversion and no memory.40
General Design Procedure Choose a particular antenna element and design it. Designing an array that is going to be used in the
smart antenna. Selecting an adaptive algorithm that minimizes the
MSE (Mean Square Error).
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Cont Determine the complex weights that scan the beam
toward the direction of the SOI (signal of interest) and place the nulls toward the direction of the SNOIs.
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Advantages and DisadvantagesAdvantages Increase the useful received signal level and also lower the
interference level. Ability to focus energy toward the intended users which results
in increased range. Fulfills the security requirement in a better way.
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ContDisadvantages Requires separate transceiver chains for each of the array
antenna element as well as accurate real time calibration. Antenna beam forming requires intensive computation. pattern-adaptive capabilities and reasonable gain features
of the smart antenna requires array antenna elements.
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Thank You !!!
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