Hệ thống 3G và mạng không dây thông minh P3
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Hệ thống 3G và mạng không dây thông minh P3
Adaptive beamforming wasinitially developed in the 1960s for the military applications of sonar andradar, in order to remove unwanted noise and jamming from output. The related the literature of the past 40 years is extremely rich [2012371 and since this book is mainly concerned with the networking aspects of wireless systems, rather than with specific antenna array designs, here we will restrict our discussionson the topic to a rudimentaryoverview.
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 ThirdGeneration Systems and Intelligent Wireless Networking J.S. Blogh, L. Hanzo Copyright © 2002 John Wiley & Sons Ltd ISBNs: 0470845198 (Hardback); 0470847816 (Electronic) Intelligent Antenna Arrays and Beamforming 3.1 Introduction Adaptive beamforming wasinitially developed in the 1960s for the military applications of sonar andradar, in order to remove unwanted noise and jamming from output. The related the literature of the past 40 years is extremely rich [2012371 and since this book is mainly concerned with the networking aspects of wireless systems, rather than with specific antenna array designs, here we will restrict our discussionson the topic to a rudimentaryoverview. The first fully adaptive array was conceived in 1965 by Applebaum [238], which was designed to maximise the SignaltoNoise Ratio (SNR)at the array’s output. An alternative approach to cancelling unwanted interference is the Least Mean Squares (LMS) error algo rithm of Widrow [239]. While a simple idea, satisfactory performance can be achieved under specific conditions. Further work onthe LMS algorithm, by Frost [240] and Griffiths [241J, introduced constraints to ensure that the desired signals were not filtered out along with the unwanted signals. The optimisation process takes place as before, but the antenna gain is maintained constant in the desired direction. For stationary signals, both algorithms con verge to the optimum Wiener solution [3,240,242]. A different technique was proposed in 1969 by Capon [243] using a MinimumVariance Distortionless Response (MVDR) or the Maximum Likelihood Method (MLM).In 1974, Reed et d . demonstrated the power of the SampleMatrix Inversion (SMI) technique, which determines the adaptive antennaarray weights directly [244]. Unlikethe algorithms of Applebaum [238]and Widrow [239], which may suffer from slow convergence if the eigenvalue spread the received sample of correlation matrix is relatively large, the performance of the SMI technique is virtually independent of the eigenvalue spread. In recent years the tight frequency reuse of cellular systems has stimulated renewed re search interests in the field [3,6,242,245]. In this book we will attempt to review the recent literature and highlight the most important research issues for UMTS, HiperLAN and WATM applications, while providing some performance results. We commence in Section 3.2 by 123
 124 CHAPTER 3. INTELLIGENT AND ANTENNA ARRAYS BEAMFORMING reviewing beamformingand its potential benefits, then we provide a genericsignal model in Section 3.2.3 and we describe the processes of element and beam space beamforming. In Section 3.3 we highlight a range of adaptive beamforming algorithmsand consider the less commonly examined downlink scenario Section 3.3.5. Lastly in Section 3.3.6 we provide in some performanceresults and outline our future work. 3 2 Beamforming . The signals induced in different elements of an antenna array are combined to form a sin gle output of the array. This process of combining the signals from the different elements is known as beamforming. Thissection describes the basic characteristics of an antenna, the ad vantages of using beamforming techniques a mobile in radio environment [3,6], and a generic signal model foruse inbeamforming calculations. For further details on the associated issues the reader isreferred to [3,6,8,238242,2442501. 3.2.1 AntennaArrayParameters Below we provide a few definitions used throughout this report in order to describe antenna systems: Radiation Pattern The radiation pattern of an antenna is the relative distribution of the radiated power as a function of direction in space. The radiation pattern of an antenna array is the product of the element pattern and the array factor, both of which are defined below. If f ( O , $ ) is the radiation pattern of each antenna element andF(O,$) is the array factor, then the array's radiation pattern, G(8, d), which is also referred to as the beam pattern, is given by G(O,$) = f(8,$ ) F ( @4). , (3.1) Figure 3.1 gives an example of a stylised antenna element response, array factor of an an 8 element linear array with an element spacingof A/2 steered at 0" and the radiation pattern, which results from combiningthe two. Array Factor The array factor, F ( @4), is the farfield radiation pattern of an array of , isotropically radiating elements, where 8 is the azimuth angleand 4 is the elevation angle. Main Lobe The main lobe of an antenna radiation pattern is the lobe containingthe direc tion of maximum radiated power. Sidelobes Sidelobes are lobes of the antenna radiation pattern, which do not constitute the mainlobe. They allow signals to be received in directions other than that of the main lobe and hence they are undesirable, but they are also unavoidable. Beamwidth The beamwidthof an antenna is the angular width of the main lobe. The 3 dB beamwidth is the angular width between the points on the main lobe that are 3 dB below the peak of the main lobe. A smaller beamwidthresults from an array of a greater aperture size, which is the distance betweenthe two farthest elements of the array. Antenna Eficiency Antenna efficiency is the ratio of the total power radiated by the an tenna to the total power input to the antenna. Grating Lobes When the distance between the antenna array elements, d, exceeds A/2, spatial undersampling of the received radio frequency carrier wave takes place, causing sec ondary maxima [2,247], referred to as grating lobes, to appear in the radiation pattern, which
 3.2. BEAMFORMING 125 Radiation pattern, G(&4) ..... Array factor, F(0, 4) Element pattern, f(0, 4)  6 0 1 ' " ' ' " " ' ' 0 30 60 90 120 150 180 210 240 270 330 300 : D Angle, @(degrees) Figure 3 1 The array factor of an eight element linear array with an element spacing of X/2 steered at .: 0".the response of each antenna element and the radiation pattern resulting from combining the two. can be clearly seen in Figure 3.2. The spatial undersampling results in ambiguities in the directions of the arriving signals, which manifests itself as copies of the main lobe in un wanted directions. The grating lobe phenomenonin spatial sampling is analogous to the well known aliasing effect in temporal sampling [247]. Therefore, the distance, d, between adja cent sensorsin the array must be chosen to be less than or equal to A/2, if grating lobes are to be avoided [247,251]. However, an interelement spacing of greater than A/2 improves the spatial resolution of the array [2], i.e. reduces the 3 dB beamwidth as shown in Figure 3.2, and reducesthe correlation between the signals arriving at adjacent antenna elements. 3.2.2 Potential Benefitsof Antenna Arrays in Mobile Communications 3.2.2.1 Multiple Beams [6] The formation of multiple beams,or sectorisation, uses multiple antennaeat the base station in order to form beams that cover the whole cell site [251]. For example, three beams, each with a beamwidth 120" may cover the entire 360" as seen in Figure 3.3. The coverage area of of each beam may be regarded as a separate cell, with frequency assignmentand handovers between beams performed in the usual manner [252]. No intelligence is required to locate a subscriber within a beam and to connect that beam to a radio channel unit. The use of multiple beams results in a reduction of the cochannel interference. In the uplink scenario, the signal received fromthe mobile station constitutes interference at only two base stations, and additionally in only one sector. In the downlink, the situation is similar, only now the sectors which can interfere with the user in the central cell are the images of the interfering
 126 CHAPTER 3. INTELLIGENT AND ANTENNA ARRAYS BEAMFORMING Element spacing = X/2 Element spacing = 3N2 60 0 30 60 90 120 15 .0 180 210 240 270 300 360 330 Angle (degrees) Figure 3.2: The array factor of an eight element uniform linear array with element spacing of X/2 and 3X/2. The grating lobes associated with the spatial undersamplinginduced secondary maxima of the radiated carrier wave are clearly visible for the case when the element spac ing is 3X/2. sectors on the uplink [19], again, as shown in Figure 3.3. 3.2.2.2 Adaptive Beams [6] The combined antenna array is used to find the location of each mobile, and then beams are formed, in order to cover different mobiles or groups of mobiles [20,253]. Each beam having its own coverage area may be considered as a cochannel cell, and thus be able to use the same carrier frequency [7,251]. In conventional sectorisation the location of the beams is fixed, while the adaptive system allows the beams to cover specific areas of the cell within which users are located [l”]. In intelligent nearfuture systems the beams may follow the mobiles, which benefit from the concentrated transmission power, with interbeam handovers occurring as necessary. 3.2.2.3 Null Steering [6,254] In contrast to steering beams towards mobiles, null steering creates spatial radiation nulls towards cochannel mobiles [38]. The realisation of true nulls or zero response is not possible due to practical considerations, such as the isolation of the radio frequency components.
 3 2 BEAMFORMING .. 127 Interfering sectors Mobde Station Figure 3.3: An example of sectorisation, using three sectors per base station, showing the reduced levels of interference with respectto an omnidirectional base station antenna scenario. D1 Figure 3.4: Switcheddiversity combining. The formation of spatial radiation nulls in the antenna response towards cochannel mobiles reduces the cochannel interference both on the uplink and the downlink [2,253]. 3.2.2.4 Diversity Schemes [6,255] The simplest and most commonly used diversity scheme is switcheddiversity. In this scheme the system switches between antennae, such that only one is in use at any one time [ 1,2561, as shown in Figure 3.4. The switching criterion is often the loss of received signal level at the antenna beingused. The switchingmay be performed at the Radio Frequency (RF) stage, avoiding the need for a downconverter for each antenna. Selection diversityis a moresophisticated version of switched diversity, where the system can monitor the signal level on all of the antennae simultaneously, and select the specific
 128 CHAPTER 3. INTELLIGENT BEAMFORMING ANTENNA ARRAYS AND Envelope 0 Demod. Figure 3.5: Selectivediversity combining. branch exhibiting the highest SNR at any given time, thus requiring an RF frontend for each antenna in the system [l], as seen in Figure 3.5. In a Rayleigh fading environment, the fading at each branch can be assumedto be inde pendent provided that the branches are sufficiently far apart. If each branch has an instanta neous SNR of 71, the probability density function of y~is given by [3] where r denotes the mean SNR at each branch. The probability that a single branch has a SNR less than some threshold y is given by [3] Therefore, theprobability that all the branches fail to achieve an SNR higher than y is [3]: pL(Y)=p[Yl,Y2,...,YLIYl=(l eF)L, (3.4) from which the probability density function of the fading magnitude in conjunction with selection diversity can be obtained, leading to the average SNR, 7, selection diversity assisted Rayleigh fading channels as [3]: of
 3.2. BEAMFORMING 129 Envel   n 1 V Cophasing = Demod. > Cophasing Figure 3 6 Optimal Combining. .: In maximal ratio combining, which is also often referred to as optimaldiversity combin ing, thesignal of each antennais weighted by its instantaneous SignaltoNoise Ratio (SNR). The weighted signals are then combined for forming a single output, as shown in Figure 3.6. It has been shown that the maximal ratio combining technique is optimal, if the diversity branch signals are uncorrelated and follow a Rayleigh distribution [21], provided that the noise has a Gaussian distribution and a zero mean. If each branch has a gain, 91, the output of the combiner is [3] L l= 1 and if each branch has the noise power, a, the total noise powerat the output ofthe combiner : is [3]: L Therefore, theSNR at the output of the combineris given by It can be easily shown that Y L is maximised, when g1 = $/U:, which is the SNR in each
 130 CHAPTER 3. INTELLIGENT AND ANTENNA ARRAYS BEAMFORMING branch. The expansion Equation 3.9 is thus of (3.10) As 7~ has a chisquareddistribution [3], the probability density function of y~ is [3]: (3.11) The probability that YL is less than the threshold, 7 , is [3] (3.12) The expectationof Equation 3.12, ? L , is the average SNR at the output of the combiner: L YL = Er = m , (3.13) 1=1 where is the mean SNR at each branch. Optimal combining processes the signals received from an antenna array such that the contribution from unwanted cochannel sources reduced, whilst enhancing that of the de is sired signal. The explicit knowledge of the directions of the interferences is not necessary, but some characteristics of the desired signal are required in order to protect it from cancellation as if it were an unwanted cochannel source [ 6 ] . A popular technique is to use a reference signal, such as achannel sounding sequence, which must be correlated with the desired sig nal. The scheme then phasecoherently combines all the signals that are correlated with the reference signal, whilst simultaneously cancelling waveforms that are not correlated with the this signal, resulting in the removal of cochannel interferences. A base station using an optimal combining antenna array may adjust the array weights during the receive cycle, in order to enhance the signal arriving from a desired mobile. A system using the same frequency for receiving transmitting the signals in different time and slots, such as in the Time Division Duplex (TDD) Digital European Cordless Telephone (DECT) [257,258] system may be able to use the complex conjugateof these weights during the transmit cycle in order to preprocess the transmit signal and to enhance the signal re ceived at the desired mobile,whilst suppressing this signal at the other mobiles. This process relies on the fact that the weights were adjusted during receive cycle to reduce cochannel the interference, thus placing nulls in the directions of cochannel mobiles [ 6 ] . Therefore, by employing the complex conjugate of these weights during the transmit cycle, the same an tenna pattern may be produced, resulting in no energy transmitted towards the cochannel mobiles [6].
 3.2. BEAMFORMING 131 Mobile ation Figure 3.7:A cell layout showing how an antenna array can support many users on the same carrier fre quency and timeslot with the advent of spatial filtering or Space Division Multiple Access (SDMA). 3.2.2.5 Reduction in Delay Spread and Multipath Fading Delay spread is caused by multipath propagation, where a desiredsignal arriving from dif ferent directions is delayed due to the different distances travelled [17]. In transmit mode an intelligent antenna is able to focus the energy in the required direction, assisting in re ducing the multipath reflections and thus delay spread. In receive mode the antenna array is able to perform optimal combining delay compensation the multipath signals incident after of upon it [l]. Those signals whose delays cannot be compensated formay be cancelled by the formation of nulls in their directions [ 181. The directive nature of an antenna array also results in a smaller spreadof Doppler fre quencies encountered at the mobile [259]. For an omnidirectional antennaat both the base station, and at the mobile the DirectionOfArrival (DOA) at the mobile is uniformly dis tributed. Hence the Doppler spectrumis given by Clarke's model [21] as: (3.14) where A, is the mean power transmitted and f m = v/X is the maximum Doppler shift, where W is the velocity ofthe mobile andX is the carrier wavelength. However, if a directional antenna is used at the base station then the Doppler power spectral density is given by [259]: (3.15)
 132 CHAPTER 3. INTELLIGENT AND ANTENNA ARRAYS BEAMFORMING Base station x 47J Direction of motion of the mobile Mobile station Line Of Sight (LOS) component Figure 3.8: Illustration of the Line Of Sight (LOS) component arriving at the mobile from the base station showing the direction of motion of the mobile, where &, as shown in Figure 3.8, is the directionof motion of the mobile with respect to the direction of the base station from themobile and fe () is the PDFof the DOA ofthe multipath components at the mobile, as given by [259]: e1 B 5 el < 1’ 5 (3.16) I ’ e2 < 0 5 where I = 2R2(7r+ 01  0,) + 4 D s i n ( a ) d R 2  D2sin2((cu). (3.17) Furthermore, 2a is the beamwidth of the socalled idealised ‘flattop’ directional antenna, which has zero gain except over the angular spread of 2a, where the gain is 1, R is the radius of the circular area containing all the scatters and D is the separation distance be tween the base station and the mobile. Finally, 01 and 8 2 are constants calculatedusing 0 = cosp1 I$$ sin2(a) * R cos(a) 1 R2  D2 sin2(a) . Figure 3.9 shows examples ofthe Doppler spectra forbeamwidths of 2 , 10 and 20 degrees for a mobile moving at angles of 0, 45 and 90 degrees with respect to the main LOS component, with a base station to mobile distance of 3 km, where the scatterers are all located within a circle of 1 km radius of the mobile. 3.2.2.6 Reduction in COchannelInterference An antenna array allows the implementation of spatial filtering, as shown in Figure 3.7, which may be exploited in both transmitting as well as receiving modes in order to reduce cochannel interferences [ 1,2, 14, 1.51. When transmitting, the antenna is used to focus the radiated energy in order to form a directive beam in the area, where the receiver is likely to
 32 BEAMFORMING .. 133 0 h 5  m 0 x . c 10 3 15  n E 20 44 U & 25 Lo E 0 30 35 40 100 80 M 40 20 0 20 40 M 80 I0 O 100 80 M 40 20 0 20 40 M 80 IW Doppler frequency (Hz) Doppler frequency (Hz) (a) Mobile's direction, = 0'. (b) Mobile's direction, &, = 45'. 0 BW=Zdegrees B 5 0 BW = IO degrees s BW = 20 degrees xI0 44 .M ' Clarke model m 8 I5 g 3 20 Lo g 25 g a 30 35 100 40 M 0 l 10 0 20 40 60 80 100 Doppler frequency(Hz) (c) Mobile's direction, = 90'. Figure 3.9: Doppler spectra at the mobile, when using a directional antenna at the base station, and an omnidirectional antenna at the mobile, is compared with Clarke's model. R = lkm, D = 3km, f n l = 100 Hz.
 134 CHAPTER 3. INTELLIGENT AND ANTENNA ARRAYS BEAMFORMING be. This in turn means that there is less interference in the other directions, where the beam is not pointing. The cochannelinterference generated in transmit mode may be further reduced by forming beams exhibiting nulls in the directions of other receivers [6,16]. This scheme deliberately reduces the transmitted energy the direction of cochannel receivers and hence in requires prior knowledge of their positions. The employment of antenna arrays for reducing cochannel interference in the receive mode has been reported widely [ 1,2,6,16181. It does not require knowledge of the co channel interference, but must have some information concerning the desired signal, such as the direction of its source, a reference signal, such as a channel sounding sequence, or a signal that is correlated with the desired signal. 3.2.2.7 Capacity Improvement and Spectral Efficiency The spectral efficiency of a network refers to the amount of traffic a given system with a cer tain spectral allocation could handle. An increase in the number of users of the mobile com munications system without a of performance increases the spectral efficiency. Channel loss capacity refers to the maximum data rate a channel of a given bandwidth can sustain. An improved channel capacityleads to an ability to support more users of a specified data rate, implying a better spectral efficiency. The increased quality of service that results from the reduced COchannel interference and reduced multipath fading[ 18, 191 upon using smart an tennae may be exchanged for an increased numberof users [2,20]. 3.2.2.8 Increase in Transmission Efficiency An antenna array is directive in nature, having a high gainin the direction where the beam is pointing. This property may be exploited in order to extend the range of the base station, resulting in a larger cell size or may be used toreduce the transmitted power of the mobiles. The employmentof a directive antenna allowsthe base station to receive weaker signals than an omnidirectional antenna. This implies the mobile can transmitat a lowerpower and that its battery life becomes longer, or it would be able to use a smaller battery, resulting in a smaller size and weight, which is important for handheld mobiles. corresponding reduc A tion in the power transmitted from the base station allows the use of electronic components having lower power ratings and therefore, lower cost. 3.2.2.9 ReductioninHandovers When the amount of traffic in a cell exceeds the cell’s capacity, cell splitting is often used in order to create new cells [2], each with its own base station and frequency assignment. The reduction in cell size leads to an increase in the number of handovers performed. By using antenna arrays to increase the capacity of a cell [l] the number of handovers required may actually be reduced. Since each beam tracks a mobile [2], no handover is necessary, unless different beams usingthe same frequencycross each other. 3.2.3 Signal Model Consider an array of L omnidirectional antenna elementssituated in the far field of a sinu soidal point source, as shown inFigure 3.10. Given that thearray element separation is d and
 3 2 BEAMFORMING .. 135 M 1 2 3 L Figure 3.10: Reception by a uniformly spaced linear antenna array. the plane wavefront impinging upon the array at an angleof 8 with respect to the array nor is + mal, the wavefront arrives at the l l t helement beforearriving at the lth element. Again,as seen in Figure 3.10, the extra distance that the wavefront must travel to reach the Zth element relative to the l + lthelement is d sin 8. However, for an arbitrary array of L elements the relative delays, assuming that the point of zero delayis the origin, are given by tl(f4= X L sin 8 + yl cos 8 , 1 = l ,. . . , L (3.18) C where c is the speed of wave propagation, i.e.the speed of light, while x1 and y~ are the x and ycoordinates of the lth element with respect to the origin located at (0,O). The extra cosine term is due to the potential yoffset from the xaxis of the array elements which is zero, and thus omitted, fromthe example shown in Figure 3.10. The signal, xl,i(t), induced in the lth element dueto the ith source canbe expressed as Zl,i(t) =m(t) Jtr(Q), p (3.19) with mi(t> denoting the complex modulating function. This expression is based upon the narrowband assumption for array signal processing, which assumes that the bandwidth of the signal is sufficiently small, so that the weighting coefficients maintain a constant phase variation across all of the antenna array elements. Assuming M directional sources and isotropic background noise, the total signal at the P h element is (3.20)
 136 CHAPTER 3. INTELLIGENT AND ANTENNA ARRAYS BEAMFORMING Figure 3.11: A beamformer sums the weighted antenna element signals, yielding the received signal Y(t) = c,"=, Wl'Zl(t). where 121 ( t )is a random noise component on lth antenna array element, which includes the background noise andelectronic noise. It is assumed to be white noise with a mean of zero and a variance of g. : The array factor, F ( 0 ) which was introduced in Section 3.2.1may be calculated thus as: l, 1=1 where W Iis the complex weighting applied the lth element to steer the antenna beam inthe to direction of 00. The maximum value of F ( @ ) will occur when 8 = 00, as shown previously in Figure 3.1. Consider the narrowband receiving beamformer, shown in Figure 3.1 l , where signals from each element are multiplied by a complex weight, wl, = 1,. . . , L and summed, in Z order to form the array output. The array output, y(t) in Figure 3.1l, at time t is given by (3.22) where * denotes the complex conjugate, ~ ( tis ) signal arriving from the lth element of the the array, and WI is the weight applied to the Zth element. Representing the weights of the beamformer of Figure 3.11 as: and the signals induced in all elements as (3.24) the output of the beamformer receiver in Figure 3.1 1 becomes (3.25)
 3.2. BEAMFORMING 137 where the superscripts T and H , respectively, denote the transpose and complex conjugate transpose of a vector ormatrix. Let R define the LbyL correlation matrix of the signal received by the L elements: where the superscript H denotes Hermitian transposition (i.e., transposition combined with complex conjugation). The correlation matrix R may be expressed in the expanded form: r R= Q) r(1) r(0) . . . r ( L  1) 1 ... r ( L  2) 1 (3.27) The element r ( 0 ) on the main diagonal is always realvalued. For complexvalued data, the remaining elements of R assume complex values. The correlation matrix of a stationary discretetime stochastic process is Hermitian [247], i.e. RH = R. Alternatively, this may be written as r (  k ) = r * ( k ) ,where r ( k ) is the autocorrelation function of the stochastic process for a lag of IC. Therefore, Equation 3.27 may be rewritten as r(0) r(1) ... r ( L  1) R=[ r* : (1) r(0) ... r(L2) (3.28) r * ( L  1) ?*(L2 )  ... r(0) The elementsof the matrix, R, denote the correlation between the output signals of the vari ous antenna elements of Figure 3.1 1. For example, Rij denotes the correlation between the i t h and the j t h elements of the array. Given that the steering vector associated with the direc si tion B i , or the i t h source, can be described by an Ldimensional complex vector as [242], si = [exp(jutl(e,)),. . . , e x p ( j u t ~ ( ~ i ) ) ] ~ , (3.29) where L is the number of elements in the antenna array, and ti is the time delay taken by a plane wave arriving from the ith source, located in the direction B i , and measured from the element at the origin, then the correlation matrix, R, of the array elements’ outputsin Figure 3.1 l may be expressed as [242]: M (3.30) i= 1 where pi is the power of the i t h source, 0 is the noise power and I is the identity matrix. :
 138 CHAPTER 3. INTELLIGENT AND ANTENNA ARRAYS BEAMFORMING s ( t ) = Aej27r f t Figure 3.12: Example of a beamforming receiver problem with a wanted signal at 0" and interfering signal at 30" using an array element spacing of X/2. Using matrix notation, the correlation matrix, R, maybe expressed in the following form [242,260]: R = ASAH f a i l = U A U H , (3.31) where S = E[&] is the covariance matrix of the array elements' outputs in Figure 3.1 1, A = [zl, . . . ,sM] isthe L x M matrix of steering vectors. Furthermore, the diagonal sz, and matrix A =diag[X1, Xz, . . . , XL] is constituted by the real eigenvalues of R, while U contains the corresponding unitnorm eigenvectors R. of 3.2.4 A BeamformingExample Consider the antenna array shown in Figure 3.12, which consists of two omnidirectional antenna elements having a spacing of S. The desired unmodulated carrier signal, s ( t ) = Aej2"ft, arrives from the angle of 8,=0 radians. The interfering signal, i(t) = N e j z n f t , arrives from the direction of e,=: radians or 30". Both signals have the same frequency, f. The signal arriving from each antennaarray element is multiplied by a variable complex weight, and the weighted signals are then summed in order to form the array output. The array output dueto the desired signal is ys(t) = AejzTft(wl+W?). (3.32)
 32 BEAMFORMING .. 139 For the array output, y ( t ) in Figure 3.12, to be the desired signal s ( t ) , the following equation must be satisfied: which leads to %[W11 + %[W21 =1 (3.34) qw11 + %[W21 = 0. The interfering signal arrives at the second array element with a phase lead of relative to the first element, since their spacing is X/2 and the angle of incidence is 30". Therefore, the array output dueto the interfering signal is yi(t) = w l N e j a x f t + w z N e j ( 2 n f t + n / 2 ) . (3.35) For this to become zerowe require that: %[W11  %[W21 =0 (3.36) S[Wl] + S [ w 2 ] = 0. Solving the simultaneous Equations 3.34 3.36 yields and ~1 = 0.5  j0.5, ~2 = 0.5 + j0.5. (3.37) The beam pattern obtained using these weights is shown in Figure 3.13. The desired signal at 0" is attenuated by about 3 dB, but the unwanted interference at an angle of 30" is subjected to an attenuation of more than 30 dB. This example shows how beamforming and the cancellation of unwanted interferences may be accomplished. However, a practical beamformer does not require the information regarding the location, number and nature of the signal sources. 3.2.5 Analogue Beamforming An antenna array consists of a number of antenna elements, the outputs of which are com bined via an amplitude and phase network, in order to form a desired antenna beam [20]. control It is possible to perform analogue beamforming the RF stage [20], using phase at shifters and amplifiers, however, the high specification required of these devices renders them costly. An (IF) alternative solution is to downconvertthe RF signal to an Intermediate Frequency and to perform the beamforming at the IF stage [3]. The disadvantage this technique is that each of antenna must have its own RFtoIF receiver. Multiple beamformers must be used to form multiple beams,resulting in the distribution of the signal energy across all the formed beams. The output SNR is thus reduced,when the lower signal energy of the beams is combined with the increased noiseinjected by the increased numberof RF and IF stages. 3.2.6 Digital Beamforming The philosophy digital beamforming is similar to that of analogue beamforming that they of in both adjust the amplitude and phase the signal arriving from each antenna element, they of but
 140 CHAPTER 3. INTELLIGENT AND ANTENNA ARRAYS BEAMFORMING 60 ' 0 30 60 90 120 150 180 210 240 270 I 300 330 360 Angle (degrees) Figure 3.13: The beam pattern produced using Equation 3.21 for a two element array with an element spacing of A/2 and element weights of 0.5 f j 0 . 5 . The desired signal is at O", the inter ference is at 30°, while SNR=9.0 dB and INR=9.0 dB. use different techniques to reach the same objective. The digitisation of the signal received at [254]. each antenna element ensures a higher information processing accuracy The RFsignal received at each element is either digitised at RF or downconverted IF and then digitised to using an AnaloguetoDigital Convertor (ADC). The digital baseband signals then represent the amplitudes and phases of the signals received at each element of the array [254]. The process of beamforming weightsthese digital signals, thereby adjusting their amplitudes and phases, such that when added togetherthey form the desired beam [20]. The receivers used in a digital beamforming system need not be closely matched in phase and amplitude, as in an as analogue network, since a calibration process can be performed by the controlling software, and any discrepancies canbe removed by adjusting the weights appropriately [254]. 3.2.7 ElementSpace Beamforming The beamforming process described in Sections 3.2.33.2.6 is referred to as elementspace beamforming, where the digitised data signals, Q,l = 1,. . . , L, received from the array elements are directly multiplied by a set of weights, w 1 , l = 1, . . . , L , in order to form a beam at the desired angle, 6 k . By multiplying the received data signals, z1, . . . ,XL, by different sets of weights, W where l = 1,.. . , L, and k = 1,. . . , K , it is possible to ,!
 32 BEAMFORMING .. 141 Figure 3.14: An elementspace beamformer receiver with L antenna elements capable of forming K beams. form beams steered in any direction, 8 k , where, again k = 1,. . . ,K . More explicitly, by multiplying the signal received at each antenna elementby a given complexvalued weight, which may be different for each antenna element, desired signal may be recovered. Each the of the beamformers creates an independent beam, at an angle, 8 k , for receiving an arbitrary mobile’s signal, by applying independent weights, W:, E = 1,.. . , L, k = 1, . . . ,K , to the array signals, yielding: where g ( & ) is the output of the beamformer in the direction of source k, k = 1,.. . , K , which is located at the angle 8 k , x1 ( t )is a sample from the lth array element and W:, 1 = 1,. . . ,L represents the weights for forming a beam angle 8 k . This equation is at very similar to Equation 3.22, except for the addition of the superscript k, k = 1, . . . ,K denoting the kth beam. Figure 3.14 shows an elementspace beamformer with L antenna elements, capable of forming K independent beams for receiving mobiles’ signals. Each of the K beams may K independently reject sources of interference, whilst receiving the desired signal. 3.2.8 BeamSpace Beamforming In contrast to the method of elementspace beamforming, where the signals arriving from each of the L elements are weighted and summedto produce the desired output, the beam space technique forms multiple beams, using a fixed beamforming network, fixed which may be spatially orthogonal. The output each beamis thenweighted and resultant signals are of the combined to produce the desired output [3,242,246,247]. The signals from the beams, which are not used to supply the desired response may be used to cancel unknown interference [247]. Assuming that the outputs from each antenna element are equally weightedand have a uniform phase delay, the response of the array, the array factor F ( @ a ) in Equation 3.21, , produced by an incident plane wave arriving at the antenna array from direction 8, measured
 142 CHAPTER 3. INTELLIGENT AND ANTENNA ARRAYS BEAMFORMING A A Figure 3.15: A beamspace beamformer receiver with L antenna elements capable of forming K beams [ 3 ] .
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