General Design Procedure

Term paper onSmart antenna system 1Elements of Smart Antenna SystemIn this section we will be dealing with some of the basic principles behind smart antennas.Smart Antenna ReceiverThe 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:

ContFigure Smart antenna receiver

ContThe 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.ContSwitched 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 TransmitterThe 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:ContFigure - Transmission part of smart antenna system

ContFigure - Transmission part of smart antenna system

ContThese 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.AntennaAntenna 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 DesignThe 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-not-of-interest (SNOIs). However, this brings two main disadvantages:Increased cost and complexity of the hardware implementationIncreased convergence time for the adaptive algorithms, thereby reducing valuable bandwidthThus, a careful network analysis is required to resolve these issues.

Linear ArrayIt 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.

ContFor M number of identical array elements, the array factor(AF) for the above linear array can be calculated as:

Which can be simplified to:

ContWhere:

- Phase excitation of the individual elements - Amplitude excitation of the individual elements d - The spacing between two consecutive array elements

ContThe 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 ArrayIt 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 y-plane is given below:ContFigure Planar array with uniformly spaced components

ContThe 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 Beamforming

General functions of smart antenna system:The direction of arrival of all the incoming signals are estimated using DOA algorithmThe 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 by constantly updating the complex weights.

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The 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 signalsTo determine the appropriate weights to ideally steer the maximum radiation of the antenna pattern toward the SOI and to place nulls toward the SNOI.

2121Direction 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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Time delay of planner array

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Illustration of DOA estimation based on time delay information.

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This clearly shows that the DOA can be determined from the knowledge of the time delay between the two elements.

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DOA estimation techniques

The techniques can be categorized into two. Conventional methodsSubspace-based methods

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Conventional methodsThe 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 signalThey have poor resolution i.e. the width of the main beam and the height of the side lobes limits its ability to separate closely spaced signals. 27Cont

Subspace Based MethodsThese 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., signal-subspace and noise-subspace. Assuming that noise in each channel is highly uncorrelated.28Cont

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 to estimate the DOA.

29Adaptive Beam forming

Adaptive algorithm process the information of DOA algorithm to ideally steer the maximum radiation of the antenna 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.30Cont

Illustration of the basic concept of how the weights are computed to satisfy certain requirements of the pattern.

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First the output y(t) of the array due to the desired signal p(t) is: y(t) = Pej0t ( w1 + w2)

w1 + w2 = 1On 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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Thus, the above values of w1 and w2 are the optimum weights that guarantee the maximum signal-to interference ratio (SIR) for a desired signal at 0 = 0 and an interferer at 1 = 30.

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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 when the cost function is minimized, the quality of the signal is maximized at the array output.36Cont

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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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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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.

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General Design ProcedureChoose 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).

41ContDetermine 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.

42Advantages 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.

43ContDisadvantages 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.

44Thank You !!!45