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) [...]... standards for third-generation (3G) wireless systems [1], [2], [5], [7] These systems include cdma2 000, Universal Mobile Telecommunications System (UMTS) Wideband CDMA (W -CDMA) FDD, UMTS WCDMA TDD, and Time Division Multiple Access (TDMA) system known as Universal Wireless Communication-136 (UWC-136) The purpose of this chapter is to describe cdma2 000 One of the fundamental requirements of 3G standards... Telephone Speech and Wideband Audio,” IEEE Comm Mag., Vol 28, No 1, pp 10— 19, January 1990 [45] P Vary, et al., “Speech Codec for the European Mobile Radio System,” Proc ICASSP ‘88, pp.227—230, April 1988 [46] J Makhoul, “Linear Prediction: A Tutorial Review,” Proc IEEE, Vol 63, pp 561—80, April 1975 CHAPTER 4 cdmaOne and cdma2 000 Copyright 2002 M.R Karim and Lucent Technologies Click Here for Terms of... requirements of 3G standards is to allow for the graceful evolution of current, 2G wireless networks In fact, cdma2 000 is an evolution of the present North American CDMA system called cdmaOne Thus, we shall begin with a brief description of cdmaOne cdmaOne Spectrum Allocation Present CDMA systems in the United States, which are known as cdmaOne, are based upon IS-95 standards [6], [7] The spectrum allocation... 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 cdma2 000 123 Mobiles Figure 4-1 The spectrum allocation in IS-95: (a) Cellular (b) PCS A A" 824 Base Stations A' B 825 835 845 Base Stations B' A" 849 846.5 869 Mobiles A A' B 870 880 890 B' 894 MHz 891.5... so that each mobile station receives a satisfactory signal level from the base station In this case, the algorithms are usually closed loop where each mobile station measures the received signal on the forward channel cdmaOne and cdma2 000 133 and, based upon the measurements, requests the base station to adjust its transmit power Handoff in IS-95 As we have indicated elsewhere, when a mobile station... 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 Boston: Artech House, 1997 [22] S Verdu, “Minimum Probability of Error for Asynchronous Gaussian Multiple-Access Channels,” IEEE Trans Inform Theory, Vol IT-32, pp 85—96, January 1986 [23] S Verdu and H.V Poor, “Abstract Dynamic... 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) in Europe operating at 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... Because the randomizer output is 307.2 kc/s and the chip rate is 1.2288 Mc/s, each bit is spread by a factor of 4 The resulting output is divided into two sequences, the I and Q sequences, which are spread by a zero-offset, I and Q pilot pseudonoise (PN) sequences of period 215 Ϫ 1 (chips) To minimize the outof-band energy, the resulting outputs are passed through a low-pass cdmaOne and cdma2 000 127... far-near problem in a cellular system BTS d1 UE1 d2 UE2 3 Notice that in a CDMA system, the interfering signal for UE1 is the transmitted signal from UE2 as well as all other stations Similarly, the interference to UE2 is caused by the transmitted signal from UE1 and all other mobiles cdmaOne and cdma2 000 131 relative distances d1 and d2, the stronger signal may swamp out the weaker signal Furthermore,... [36] R.T Compton, Adaptive Antennas—Concepts and Performance New Jersey: Prentice Hall, 1996 [37] S.C Swales, et al., “The Performance Enhancement of Multibeam Adaptive Base Station Antennas for Cellular Land 120 Chapter 3 Mobile Radio Systems,” IEEE Trans Veh Technol., Vol VT39, No 1, pp 56—67, February 1990 [38] S Anderson, et al., “An Adaptive Array for Mobile Communications System,” IEEE Trans Veh . s 1 1j2R 21 1 02 s 1 1j ϩ 12R 21 1ϪT2ϩ p ϩ n 2 1t2 R 12 1jT2ϭ 1 T Ύ 1jϭ12T jT y 1 1t2y 2 1t ϭ jT ϭ t2dt 1 T Ύ 1jϩ12T jT y 1 1t2y 1 1t2dt ϭ 1 115 Principles of Wideband CDMA (W -CDMA) Band Pass Filter Matched. s 2 (j Ϯ 3), and so on, are ignored because it r o1 1jT2ϭ s 1 1j2ϩ s 2 1j Ϫ 12R 12 1T2ϩ s 2 1j2R 12 1 02 s 2 1j ϩ 12R 12 1ϪT2ϩ p ϩ n 1 1t2 Chapter 3 114 X Symbol Mapper x Data from User 1 (PN. by the channel. Similarly, {s 2 (i)}, y 2 (t), A 2 , ␾ 2, ␶ 2 113 Principles of Wideband CDMA (W -CDMA) and n 2 (t) are the corresponding parameters for user 2, and so on. The channel noise is