The maximum amount of multipath delay that can be exploited in a rake receiver is usually limited, and is determined by the power delay profile. As an example, for a city like New York, it lies in the range of 0.25 — 2.5 ms. Thus, in UMTS W-CDMA, where the chip rate is 3.84 Mc/s, the delay is about 1 — 10 chips. Although multipath diversity is a property of all CDMA systems, it is only W-CDMA that provides multipath diversity for small cells (that is, the micro and pico cells). To see this, consider IS-95 where the carrier bandwidth is 1.25 MHz. In this case, because the chip rate is 1.2288 Mc/s and because the delay must be at least one chip long to achieve multipath diversity, the difference in path lengths must be at least 244 meters. On the other hand, for W-CDMA with 5 MHz bandwidth, the chip rate is 3.84 Mc/s, and so this path differ- ence is reduced to 81 meters. The multipath diversity employed in a rake receiver leads to an improvement in performance. For example, the value of E b /N 0 required to ensure a bit error rate of 10 Ϫ3 on a fading channel is about 10 dB, assuming BPSK modulation, a 4-branch rake receiver, and equal gain combining. The required E b /N 0 for the same bit error rate is 14 dB with two branches and about 24 dB with one branch, that is, without any multipath diversity [21]. The maximal ratio com- bining has the best performance. If most of the signal energy is con- tained in only one branch, a conventional receiver will perform better than a rake receiver that uses equal gain combining [33] because, in this case, branches with very little signal power will only add to the noise. Multiuser Detection Consider the uplink transmissions in UMTS. Here, the user data on various physical channels (such as dedicated physical data channels, dedicated physical control channels, and so on) is first spread with a channelization code, and then scrambled with a user-specific PN code. Because channelization codes are mutually orthogonal and thus more resistant to multiuser interference, the physical channels can be correctly separated at the receiver with a high probability. The Chapter 3 98 scrambling codes, on the other hand, are generally nonorthogonal. This is not a problem in a synchronous system, such as IS-95, because here, all transmissions are synchronized to a systemwide time reference. Thus, signals from multiple users arrive at the BS with relatively small delays. Consequently, the cross-correlation between the signals is quite small. In contrast, because UMTS W- CDMA is an asynchronous system, these delays are random as shown in Figure 3-27, and may be comparable to the bit period. As a result, the cross-correlation between the received signals from mul- tiple users is no longer negligible and, if ignored, causes significant errors in soft decision decoding. Besides, very often the power control is not perfect. Even when a mobile is adjusting its transmitter power at 1,500 Hz on command from the BS, this closed-loop power control algorithm does not work well for mobile velocities of 100 km/h or more. Thus, the amplitude of the desired signal may at times be quite small compared to interfer- ing signals. So, the performance of a matched filter followed by a sim- ple decision circuit is not optimum anymore. Multiuser detection attempts to overcome this problem by detecting the desired user sig- nal in the presence of interference from all other users in some opti- mum way. A number of multiuser detection algorithms have been suggested [21]. One of them is based on the Viterbi algorithm with soft decision 99 Principles of Wideband CDMA (W-CDMA) T 2 3 τ User 1 2 3 τ Figure 3-27 Signals received at a BS from multiple users. In an asynchronous system, the time offsets shown as t 2 and t 3 with respect to the desired signal from, say, user 1 are significant. decoding. The ideas here are similar to those discussed in connection with the maximum likelihood decoding of convolutional codes [22], [23]. The received signal, after demodulation, is multiplied by the scrambling code of each user, integrated over a symbol period using a matched filter, and applied to a soft decision decoder. The output of the matched filter corresponding to any desired user depends upon the cross-correlation between the signal from that user and signals from all other users over three consecutive symbol periods. Over a given symbol length, the soft decision decoder considers all combi- nations of symbols from multiple users, and using a channel model together with the observed outputs of the matched filter, estimates the likelihood of each sequence of symbols. Appendix C presents a brief description of this algorithm. Although the performance of this receiver is optimum, it is not very practical because the number of real-time computations required increases as 2 n , where n is the number of users to be detected. A number of authors have proposed suboptimum receiver structures where these computational require- ments are less stringent. Another technique suggested for multiuser detection involves suc- cessive cancellation of interference from the received signal [24] — [28]. Here, the receiver first extracts the strongest signal of all users and subtracts it from the received signal. Next, the second strongest signal is detected from the remaining signal, and subtracted from this latter signal, and so on, until signals from all users have been detected. The idea is illustrated in the block diagram of Figure 3-28. Because the performance of the receiver depends on the accuracy with which the strongest interference is detected in the first stage, reference [24] suggests using a multipath-combining receiver for detecting the strongest interference. 9 The detected data of this user is then passed through a channel model to regenerate a signal, which approximates as closely as possible the received signal from this user. The output of the channel model is subtracted from the received input. The result is used to derive the second strongest sig- nal in the same way. Conventional receivers may be used in the sec- ond and subsequent stages. Chapter 3 100 9 For this to be possible, it is necessary that the signal bandwidth be much greater than the coherence bandwidth of the channel. Because of the complexity involved, multiuser detection is more amenable to implementation at a BS. Moreover, because a mobile station is only concerned with detecting the signal from a single user, multiuser detection is really not necessary at a mobile station. In UMTS W-CDMA, both long and short scrambling codes may be used on uplinks. However, short codes are generally more suitable for multiuser detection [41]. Long codes are handled better by the algorithm based on the successive cancellation of interference. Smart Antennas In a previous chapter, isotropic and directional antennas were dis- cussed. An isotropic antenna is one that radiates energy equally in all directions in any horizontal or vertical plane. Practical antennas, however, are not isotropic. For example, with an omnidirectional antenna, such as a vertically mounted, half-wave dipole, or a short monopole, the signal strength at any given distance from the antenna is distributed equally in all directions in the horizontal plane. In the vertical plane, however, the signal strength at any point depends on its location with respect to the vertical axis. This is shown in Figure 3-29(a). The power density is 0 along the vertical axis and increases as the angle u increases, attaining a maximum value on a horizontal plane through the antenna such that u ϭ 90 degrees. As discussed in Chapter 2, the signal strength decreases at points further and further away from the transmitter antenna. An example of an omnidirectional antenna is the antenna at a mobile station or a center-excited BS. 101 Principles of Wideband CDMA (W-CDMA) Strongest User Data + - - + Received Signal Multipath Combining Receiver Channel Model Conventional Receiver Channel Model 2nd Strongest User Data o o o Figure 3-28 Multiuser detection using successive cancellation of interference As the name implies, a directional antenna radiates most of its energy only in a certain direction, transmitting the signal in the form of a beam in the direction of the antenna. The radiation pattern for a vertically mounted directional antenna is shown in Figure 3-29 (b). Notice how the signal strength varies even in a horizontal plane. Depending upon the design, the energy in the back lobe is usually very small. Directional antennas are used to provide coverage on highways and in corner-excited, 3-sector cell sites, where each sector has an angular width of 120 degrees. Clearly, there are many advan- tages of a directional antenna. For example, with a given transmit- ter power, it extends the coverage area, decreases the probability of the far-near problem that was discussed before, reduces interference to a given mobile due to other active users on the same frequency, and thus increases the system capacity (such as the number of users in a CDMA system). In 3-sector cells, a sector may be covered by a number of narrow- beam antennas as shown in Figure 3-30. The beams formed by these antennas are fixed, each of which may be used to cover users con- centrated in certain directions. In this case, the BS must be able to track each user and switch the beams appropriately as a mobile sta- tion moves from the coverage area of one beam to another. A disad- vantage of the fixed beam approach is that if the traffic pattern changes from the one for which the beams were originally designed, the system may not operate at the same level of performance. Chapter 3 102 Main Lobe y z x z y Power Density = k sin 2 (a) (b) (b) Back Lobe θ θ Figure 3-29 Radiation patterns of two antennas: (a) Omnidirectional antenna, (b) Directional antenna Because each mobile station has a unique physical location, the signal received from each can be processed in real time and sepa- rated from the signals of all other users even though they may over- lap in the time or frequency domain. Signal processing required to perform this function is called spatial filtering or filtering in the space domain. This technique is also called by some authors space- division multiple access (SDMA) because this enables multiple users to be distinguished even though they may occupy the same fre- quency or time slot. Clearly, sectorization of cells with directional antennas and use of fixed beams may be considered as a form of spatial filtering. Another way to implement spatial filtering is to use an adaptive antenna array where the signal received from each element of the array is multiplied by a gain coefficient, called a weight, summed together, and then processed using digital signal processing tech- niques so as to maximize the system performance according to some criteria. The weights are adjusted dynamically using an adaptation algorithm that tries to achieve some design objectives. For example, an objective may be the formation of a beam in a desired direction so that the signal is maximized in that direction and minimized or even reduced to a null in other directions, say, in the direction of co- channel sources. This is called digital beam forming. Another objec- tive may be the minimization of bit error rates for users located in a certain geographical area where the error rate would otherwise be excessively high due to clutter or other conditions. The term smart antennas refers to both switched beam antennas and adaptive antenna arrays. 103 Principles of Wideband CDMA (W-CDMA) y x λ /2 Figure 3-30 Fixed beams formed by narrow- beam antennas Fundamental to the operation of adaptive antennas is the ability to estimate the angle of arrival of signals from different users and, based on the estimate, steer the beams on downlink channels. The arrival angle is generally quite well defined in rural areas, but not so in microcells or indoors. Because for large cells, the angle of arrival varies much more slowly than the instantaneous fading signal, mea- surements from mobile stations may also be used in the adaptation algorithm. The concept and theory of adaptive antennas may be found in References [35], [36]. Various authors have investigated the appli- cation of adaptive antennas to mobile communications systems [37] — [39], [42]. Reference [40] discusses the possibility of extending the capacity of an existing cellular system so as to serve areas of high traffic density by using smart antennas. Possible benefits of using smart antennas in 3G systems have been studied under the auspices of the Technology in Smart Antennas for Universal Advanced Mobile Infrastructure (TSUNAMI) project in Europe [41], and include the following: ■ Extending the range or coverage area in a desired direction with beamforming ■ Increasing the system capacity in areas with dense traffic (that is, hot spots) ■ Dynamically adjusting the coverage area (say, from 120 to 45 degrees) ■ Creating nulls to/from co-channel interferers so as to minimize the co-channel interference ■ Tracking individual mobile stations using separate, narrow beams in their direction ■ Reducing multipath fading In this section, we will explain briefly how beam forming is accom- plished by adaptive antennas. Figure 3-31(a) shows a functional block diagram of a system where adaptive antennas are being used to maximize the signal for a given user. Beam forming in a desired direction or creating a null (from co-channel interferers or various multipaths in a TDMA system) as shown in Figure 3-32 is similar in principle. Signals Chapter 3 104 TEAMFLY Team-Fly ® from various sensors in an antenna array are converted into digi- tal forms, multiplied by weights W i , summed together, and after coherent demodulation, despread in the usual way using local copies of orthogonal Walsh codes and long user codes. The output 105 Principles of Wideband CDMA (W-CDMA) Soft Decision Decoding Output Matched Filter BPF, RF & IF Amplifier 1 W BPF, RF & IF Amplifier 2 W Antenna 1 Antenna 2 o o Adaptation Controller o o Coherent Demodulator Despreader Long Code Channelization Code BPF, RF & IF Amplifier 3 W Antenna 3 D/A D/A D/A ∫ + Tn nT )1( Σ (a) Figure 3-31 A CDMA system using an adaptive antenna array: (a) Beamforming is done at the IF stage. (b) Beamforming is done at the baseband. Decision Circuit Output Matched Filter BPF, RF & IF Amplifier 1 W BPF, RF & IF Amplifier 2 W Antenna 1 Antenna 2 Adaptation Controller Coherent Demodulator Despreader PN Codes BPF, RF & IF Amplifier 3 W Antenna 3 Coherent Demodulator Despreader Coherent Demodulator Despreader Matched Filter Matched Filter Reference Signal Σ (b) Towards Cochannel Interferers x User 1 User 2 Figure 3-32 Beamforming and steering nulls toward certain directions using adaptive antennas of the matched filter is decoded in a decision circuit. The resulting output is also used by the adaptation controller to adjust the weights so as to maximize the signal-to-interference ratio for the given user in much the same way as a rake receiver, discussed previously. In this approach, because signals are being weighted and summed at the RF stage, the scheme suffers from the disadvantage that its accuracy is rather limited and that its implementation may become quite complex, particularly when there are many elements in the array. A scheme that performs beamforming at the baseband was shown in Figure 3-31(b). Because signal processing is now being done at the baseband, it is possible to use 16-bit arithmetic compared to a 5- or 6-bit operation that is usual for RF beamforming. The improvement in performance with adaptive antennas depends upon the antenna type — linear, planar, or circular—the number of elements in the array, and the spacing between adjacent elements. This spacing is usually one half of the carrier wavelength. The improvement in signal-to-interference ratios is about 3 dB with two elements, 6 dB with four elements, 7.75 dB with six elements, and 9 dB with eight elements [42]. Summary In this chapter we have presented fundamental principles of CDMA and more specifically W-CDMA. The various functional components of a BS transmitter have been discussed in some detail. The receiver structure, soft decision decoding of convolutional codes, methods of multiuser detection at a BS, and smart antennas have been described. In some cases, for the convenience of readers, details have been moved to the following appendices. Chapter 3 106 Appendix A — Viterbi Decoding of Convolutional Codes The Viterbi algorithm performs sequential decoding using principles of dynamic programming [9], [11]. The algorithm is based on the fact that if at any instant t k , there is a sequence of m information bits for which the decoder performance is optimum, then those m bits will be the first m bits of a sequence that optimizes the performance at any later instant t l Ͼ t k . Given a sequence of outputs from the matched filter over a desired observation period, a sequence of bits is chosen at each stage as the most likely transmitted sequence. To continue with the algorithm, suppose that R is a sequence of samples of the matched filter output (which are analog voltages as mentioned before). At each symbol period, the number of samples read by the decoder equals the number of output bits generated by the encoder for each input bit. That is, for a rate 1 / 2 encoder, there are two samples to the input of the decoder at the end of each symbol period. Furthermore, each of these samples is defined by one of the quantization levels R. The maximum likelihood decision theory states that X is the code that was most likely transmitted if the prob- ability of R (assuming X) is maximum, that is, if To use this algorithm, then, it is first of all necessary to determine the probability of occurrence of each quantization level of the decoder inputs at each symbol period assuming that a transmitted bit is 0. Similarly, the probability of occurrence of each quantization level of the decoder inputs at each symbol period, assuming that a transmitted bit is 1, is determined in the same manner. Because these probabilities will be used at each step for sequential decoding, P1R 0 X2 is maximum. 107 Principles of Wideband CDMA (W-CDMA) [...]... Reception of Spread-Spectrum Multiple-Access Communications,” IEEE Trans Comm., Vol COM-35, No 11, pp 1189—1198, November 1987 [19] T Ojanpera and R Prasad (Ed.), Wideband CDMA for Third Generation Mobile Communications Boston: Artech House, 1998 [20] H Holma and A Toskala (Ed.), W-CDMA for UMTS New York: John Wiley, 2000 [21] S Glisic and B Vucetic, Spread Spectrum CDMA Systems for Wireless Communications... which are known as cdmaOne, are based upon IS-95 standards [6], [7] The spectrum allocation is shown in Figure 4-1 The allocation is 50 MHz for cellular systems and 120 MHz for Personal Communications Services (PCS) The spectrum is divided into a number of bands as shown in the fig- cdmaOne and cdma2000 123 Mobiles Figure 4-1 The spectrum allocation in IS-95: (a) Cellular (b) PCS A A" 824 Base Stations... overcome this limitation and, particularly, to be able to provide multimedia services, the International Telecommunications Union— Radio Communication Sector (ITU-R) published in 1999 a set of standards for third-generation (3G) wireless systems [1], [2], [5], [7] These systems include cdma2000, Universal Mobile Telecommunications System (UMTS) Wideband CDMA (W-CDMA) FDD, UMTS WCDMA TDD, and Time Division... 450 and 900 MHz bands The second-generation (2G) systems are based on IS-136, IS-95A, IS-95B, and GSM, and have the data transport capability, but only to a limited extent For example, GSM supports short messaging services (SMS) and user data at rates only up to 9.6 kb/s With IS-95B, it’s possible to provide data rates in the range of 64 to 115 kb/s in increments of 8 kb/s over a 1.25 MHz RF bandwidth... Milstein, and D L Schilling, “Spread Spectrum for Mobile Communications,” IEEE Trans Veh Technol., Vol 40, No.2, pp 313—322, May 1991 [8] A.J Viterbi, “Convolutional Codes and Their Performance in Communications Systems,” IEEE Trans Comm Tech., Vol COM-19, No 5, pp 751—772, October 1971 [9] J.A Heller and I.M Jacobs, “Viterbi Decoding for Satellite and Space Communication,” IEEE Trans Comm Tech., Vol COM-19,... period 215 Ϫ 1 (chips) To minimize the outof-band energy, the resulting outputs are passed through a low-pass cdmaOne and cdma2000 127 filter with a nominal bandwidth of about 740 kHz The filtered outputs are symbol-mapped and then modulate the carrier Notice that the Q-channel data, after spreading by the Q-channel pilot PN sequence, is delayed by Tc/2 before it is filtered, where Tc is the chip period... and cdma2000 Copyright 2002 M.R Karim and Lucent Technologies Click Here for Terms of Use Chapter 4 122 As mentioned in Chapter 1, “Introduction,” first-generation (1G) mobile telecommunication systems in the 1980s were analog, and consisted of cellular system TIA/EIA-553 in the United States operating around 850 MHz, and Total Access Communication System (TACS), and Nordic Mobile Telephone (NMT)... two terms of type (A-1) In other words, Pk ϭ p1rkl Ϳ xkl 2 ϫ p1rk2 Ϳ xkl 2 (A-2) It is, therefore, convenient to take the logarithm of expression (A-2) and, for ease of computation, transform the result into an integer using an appropriate expression This value can then be used as a metric for a path In this way, the branch metrics for all paths of the trellis diagram are computed For an encoder with... quantization level of 8 and assuming Gaussian noise [9] Referring to Figure 3-1 5, the value of Eb /N0 required for a bit -3 10 K=4 Bit Error Rate Figure 3-3 3 Bit error rate of convolutional codes with constraint length K ϭ 4 and K ϭ 8 The quantization level used is 8 [From paper by Heller and Jacobs (1971) © 1971 IEEE] -4 K=8 10 -5 10 3 3.5 4 4.5 Eb/No (dB) 5 5.5 Chapter 3 110 error rate of 10Ϫ4 for BPSK without... “Cancellation Techniques of Co-Channel Interference in Asynchronous Spread Spectrum Multiple Access Systems,” Trans IECE (Electronics and Communications in Japan), Vol 66, pp 416—423, May 1983 Principles of Wideband CDMA (W-CDMA) 119 [26] R.H Kohno, H Imai, M Hatori, and S Pasupathi, “Combination of an Adaptive Array Antenna and a Canceller of Interference for Direct-Sequence Spread-Spectrum Multiple Access . to Figure 3-1 5, the value of E b /N 0 required for a bit 109 Principles of Wideband CDMA (W-CDMA) 3 3.5 4 4.5 5 5.5 10 -5 10 -4 10 -3 E b /N o (dB) Bit Error Rate K=8 K =4 Figure 3-3 3 Bit error. codes y 1 (t) and y 2 (t) is given by (C-3) Similarly, the output of the matched filter for user 2 is: (C -4 ) Expressions (C-1) and (C -4 ) can be represented by a 2-tap delay line. Figure 3-3 9 shows. output of the wave-shaping filter does not have a con- stant amplitude all the time, it never goes through 0 (compare Fig- ure 3-3 4 and Figure 3-3 6), and is, therefore, more suitable for amplification