Tài liệu Adaptive WCDMA (P6) doc

6 Power control 6.1 ALGORITHMS In Chapter 8, we will show that the Code Division Multiple Access (CDMA) network capacity depends significantly on the so-called near–far effect. From the very beginning, theory and practice of CDMA were aware of this fact. All practical systems use Power control (PC) to reduce this effect. PC is more efficient in the system optimized for speech, such as IS-95. In a multimedia network such as Universal Mobile Telecommunication Sys- tem (UMTS) in which different signals levels are used for different data rates, additional solutions like multiuser detectors are used. In IS-95, every mobile station attempts to adjust its transmission power so that signals received at a base station are at the same, minimum level at which good quality communi- cation can still be provided. Both the closed and open loop methods are used. The closed- loop includes two different loops, that is, a relatively fast inner and a slow outer loop. In addition to the data signals, every base station transmits a so-called pilot signal, which is an unmodulated signal [1] used at the mobile stations for PC, synchronization and demod- ulation as a power level, phase, frequency and time reference. In the open loop method, a mobile station measures the average received total power and adjusts its transmission power to be inversely proportional to the received power. In the initial phase of the call, the average received pilot signal power is measured. The open loop algorithm is presented in Reference [2]. The mobile station transmission power is a certain constant divided by the received total power. The constant value used depends on several base station param- eters, such as antenna gain, the number of active users, transmission power, required signal-to-interference ratio (SIR) and interference caused by other base stations. The base station informs the mobile stations before transmission about the value of that constant. Open loop PC can be nonlinear [3]. The purpose of nonlinearity is to allow fast response (maximum control speed of 10 dB ms −1 ) for negative corrections, but slow response (maximum control speed of 1 dB ms −1 ) for positive corrections. When attenuation is suddenly decreased, the mobile station quickly decreases the transmission power in order not to cause additional interference to other users. The extra interference Adaptive WCDMA: Theory And Practice. Savo G. Glisic Copyright ¶ 2003 John Wiley & Sons, Ltd. ISBN: 0-470-84825-1 148 POWER CONTROL would diminish the system capacity. Since the separation of the reverse and forward-link frequency bands far exceeds the coherence bandwidth, Rayleigh fades in different links correlate poorly with each other. Since the open loop method cannot estimate reverse-link fading, open loop PC cannot be accurate. Its inaccuracy is as much as 10 dB. In order to compensate for reverse-link fading, a closed-loop method is required. In the closed-loop method, a base station measures (measurement time 1.25 ms) the average received power [1] or the SIR and compares it to a threshold. As a result of the com- parison, the base station sends a power-control command to the mobile station, the size of which is nominally 0.5 to 1.0 dB, by puncturing one data bit every 1.25 ms. The bit rate in the feedback is then 800 bps. The closed loop employs delta modulation (DM), that is, after a control delay of about 1.25 ms, the power-control command adjusts the previous transmission power of the mobile station up or down by a fixed step. PC com- mands are thus extracted and integrated at the mobile station. The part of the closed-loop method discussed above is called an inner loop and will be discussed in detail in the next section. In an outer loop, a base station measures the frame-error rate (FER) of each mobile station, according to which it adjusts the threshold so that the FER is maintained in the required region (e.g. smaller than 1%). The outer loop algorithm is presented in Reference [4]. The outer loop acts more slowly than the inner loop since its updates are once per every 20 ms frame. The outer loop algorithm discussed above is a fixed-step variable threshold algorithm, which uses fixed-size steps in adjusting the target threshold. The improved variable-step variable threshold method is proposed in Reference [5]. Final PC is completed when closed-loop control commands are added to open loop PC. The dynamic range of the received power can be reduced, and thus facilitate the task of PC, by using a diversity receiver. In Reference [6], functioning of PC is analyzed when a mobile station is in a soft handoff region. In soft handoff, the mobile station is connected simultaneously to several base stations, and it can use lower transmission power. The mobile station transmission power is increased only when all the base stations request it. Otherwise, the transmission power is reduced. The performance of the CDMA system can also be improved by interleaving and channel coding [7,8]. PC and interleaving are complementary methods since with low velocities interleaving is not efficient but PC performs accurately. With high velocities, it is difficult for PC to compensate for the channel effects while, on the other hand, interleaving operates more effectively. In delay insensitive data traffic, in addition to channel coding, an automatic repeat request (ARQ) protocol can be used to achieve a very low bit error rate (BER) value [9]. In Reference [10], a CDMA system with soft PC is proposed, in which the processing gain and code rate are controlled according to the variation of the channel. Since the proposed adaptive processing gain and code rate technique equivalently control the received signal- to-noise ratio (SNR) per bit to the constant value, the conventional PC, which adjusts the received carrier-to-interference ratio (CIR) to be constant, is no longer needed. In Reference [11], a convolutionally coded hybrid DS/SFH (direct sequence/slow frequency hopping) CDMA system using PC is presented. It is shown using simulations that much less accurate PC is required when the DS/SFH CDMA, instead of the pure DS/CDMA system, is employed. The reason for this is that the hybrid system is less susceptible to the near–far problem than the DS/CDMA system. The hybrid system, with selection diversity and without PC, is even better suited to solve the near–far problem than a ALGORITHMS 149 DS/CDMA system with accurate PC and an even higher order of diversity [12]. The near–far self-resistant CDMA network concept is discussed in Chapter 15 of this book. Field tests have been carried out for IS-95 DS/CDMA system in varying environments [7]. The performance of PC in particular has been examined. It appeared that mobile stations in the CDMA system used, on the average, 20 to 30 dB lower transmission power than mobile stations in the analog American mobile phone system (AMPS). The inaccuracy of PC was observed to approximate a lognormal distribution with a standard deviation of about 2.5 dB when normal mobile station velocities and small enough FER values (smaller than 1%) are used [13,14]. The details of power-control implementation, IS-95 will be discussed in Chapter 17 and can be seen in Reference [15]. In Reference [16], the influence of average PC, voice activity detection and micro- and macrodiversity to cellular DS/CDMA systems were studied. The performance of PC of the cellular CDMA system when the channel model includes propagation loss and Rayleigh fading is discussed in Reference [17]. The mobile station transmission power was proportional to the fourth power of the distance. The capacity of the microcellular CDMA system was evaluated using simulations in Reference [18] when IS-95 type, fixed-step adjustment, closed-loop PC – FSAPC (only inner loop, i.e. no FER measurement), was used. The channel model included long-term attenuation and Rayleigh fading. Furthermore, in Reference [19] simulation results for single-cell and multicell DS/CDMA systems employing FSAPC were combined with coding bounds to obtain quasi-analytic estimates of the reverse-link capacity, over both frequency-nonselective and frequency-selective fading channels. Ariyavisitakul and Chang simulated the performance of closed-loop PC (only inner loop) in both fixed (FSAPC) and variable-step (VSAPC) cases over a Rayleigh fading multipath channel [20]. The variable-step was implemented by removing a hard quantizer in the step-generation process. The bit rate of PC commands was assumed to be at least 10 times the Doppler frequency in order for PC to function effectively (see also Reference [21]). In the single user case, they realized that the performances of the FSAPC and VSAPC were approximately equal when a diversity order of two was used. The same conclusion with the performance comparison between FSAPC and VSAPC was also drawn in Reference [22], especially when the number of tap coefficients in the RAKE receiver was greater than two. In Reference [22], bit rates of FSAPC and VSAPC were equal. That is, in the variable-step scheme, the logic pattern of many successive stored command bits was taken into consideration when adjusting the mobile station’s transmission power. FSAPC was not very sensitive to control command errors occurring in the feedback channel [20,22]. In the case of no diversity, the performance of VSAPC was noticed to be superior to that of FSAPC according to Reference [19]. The effect of feedback delay on FSAPC was simulated in Reference [23]. The influence of the delay was diminished by estimating the received power by a linear predictor based on the recursive least-squares (RLS) algorithm. The performance with high (>50 km h −1 ) mobile station velocities, using estimation based on the RLS algorithm, was better than with conventional PC with power measurement by straight averaging. In cellular systems, the interference power received at the base station was noticed to be larger in the cases of FSAPC and ideal PC (tracks fading accurately) than with ideal average PC [20]. This is due to the effects of power command errors and/or the interference peaking caused 150 POWER CONTROL by the perfect tracking of deep fades. The use of fast PC is, however, reasonable since interleaving is inefficient if the average PC employed is slow. Performances of FSAPC and adaptive fuzzy proportional-plus-integral (PI) PC were simulated and compared in Reference [24]. Parameter P in fuzzy PI control extends the bandwidth improving response to changes, and it also prevents the system from becoming unstable. Term I attempts to force the steady-state error to zero. Fixed-step adjustment control is a slight modification of the integral (I) control. Fuzzy PI PC was observed to achieve a shorter rise time, smaller overshoot and smaller rms tracking error. Chang and Wang modified the rule base to also take into account a control delay [25]. The drawback of fuzzy PC is that the channel behavior has to be estimated in advance when constructing the rule base. In neural network-based PC, the channel behavior can be learned adaptively on line during the control process; these algorithms will be discussed later in this chapter. The optimal PC in the multimedia CDMA system, in which many kinds of information (e.g. voice, image and data) are transferred simultaneously, is analyzed in Reference [26]. Data rate and required communication quality, and thus the PC of each media, depend on transmitted information. A method is proposed by which increasing (decreasing) the transmission power of media with high (low) transmission rates or small (large) processing gains attempts to improve the BER. Data service is bursty in nature. This makes its PC more difficult than the PC of voice calls since channel conditions change between consecutive packets and are difficult to predict. Fortunately, the capacity is more sensitive to the power-control errors of voice service than those of data service. Zhuang has derived an upper bound for the BER for the packetized multimedia CDMA system using optimal PC, diversity and convolutional coding with ARQ protocol for delay insensitive traffic [9]. Using a fixed-rate channel coder and PC in a CDMA system can be seen as one solution for performing unequal error protection (UEP) for different traffic types [27]. 6.2 CLOSED-LOOP POWER CONTROL IN DS-CDMA CELLULAR SYSTEM: PROBLEM DEFINITION Closed-loop PC is a topic covered to a great extent by the control theory. For this reason, in this book we will limit ourselves to the problem definition and literature survey, rather than going into details of the control theory itself, which is available in numerous textbooks. The general block diagram of the closed-loop PC used for this application is shown in Figure 6.1. Let us start from the point in the loop marked by P t n , representing the mobile unit transmit power at the sampling instant with index n. In the loglinear model, presented in Figure 6.1, the received power R n will be equal to the sum of channel losses A n and P t n . The base station will be estimating R n in order to find out what kind of correction is needed. This estimation will be incorrect and the estimation error power is N n .All together B such samples will be averaged out in order to remove the impact of noise on the overall process. After that, the result is compared with ‘the desired received power’ P ∗ n and a sample of error signal is created. Different ways of generating reference level P ∗ n will be discussed later. This error is transmitted on the downlink and after propagation delay of D samples the error signal CLOSED-LOOP POWER CONTROL IN DS-CDMA CELLULAR SYSTEM: PROBLEM DEFINITION 151 A n N n R n E n S n S n = ∑ δ n − iB P t n P ∗ n d( n − B ) d( n − D ) Desired received Estimate error Channel loss Averaging Transmitted power Received power Delay Delay Zero-order hold Sampling waveform otherwise0 1 x = 0 0 … 1/ B 1 B − 1 0 B − 1 d x = i = 0 ∞ Figure 6.1 Loglinear power-control model [19]. Reproduced from Chockalingam, A., Dietrich, P., Milstein, L. B. and Rao, R. R. (1998) Performance of closed loop power control in DS-CDMA cellular systems. IEEE Trans. Veh. Technol., 47(3), 774–789, by permission of IEEE. E n−D will be added to P t n to generate a new power level at the mobile transmitter. P t n+1 = P t n + E n−D (6.1) One can see that delay B, due to signal processing, is known to both mobile and base station and will be compensated in the signal processing. Delay D due to propagation will not be compensated, which will cause performance degradation depending on the Doppler rate. A simplified model from Figure 6.1 is presented in Figure 6.2. Some of the results of the analysis of the loop behavior are shown in Figures 6.3 to 6.6. First of all, the received signal power covariance function will be changed dramatically − … A n N n R n E n d( n − B ) d( n − D ) Desired received power Estimate error Channel loss Averaging Transmitted power Received power Delay Delay 0 1/ B B − 1 P t n P ∗ n Figure 6.2 Simplified loglinear power-control model [19] Reproduced from Chockalingam, A., Dietrich, P., Milstein, L. B. and Rao, R. R. (1998) Performance of closed loop power control in DS-CDMA cellular systems. IEEE Trans. Veh. Technol., 47(3), 774–789, by permission of IEEE. 152 POWER CONTROL 50 150100 200 250 0 −5 0 5 10 15 20 25 30 Bit lag Received power auto covariance No power control B = 35 B = 20 B = 5 Figure 6.3 Effect of averaging interval B on the received power autocovariance for f d = 25 Hz and D = 5 [19]. Reproduced from Chockalingam, A., Dietrich, P., Milstein, L. B. and Rao, R. R. (1998) Performance of closed loop power control in DS-CDMA cellular systems. IEEE Trans. Veh. Technol., 47(3), 774–789, by permission of IEEE. 10 20 30 40 50 0 60 −4 −2 0 2 4 6 8 10 12 Received power auto covariance Solid: analysis Dotted: simulation Bit lag Figure 6.4 Comparison of received power autocovariance functions as predicted by analysis and simulation for f d = 25 Hz, B = 20, E b /N 0 = 10 dB, D = 5andT b = 1/8000 s [19]. Reproduced from Chockalingam, A., Dietrich, P., Milstein, L. B. and Rao, R. R. (1998) Performance of closed loop power control in DS-CDMA cellular systems. IEEE Trans. Veh. Technol., 47(3), 774–789, by permission of IEEE. CLOSED-LOOP POWER CONTROL IN DS-CDMA CELLULAR SYSTEM: PROBLEM DEFINITION 153 10 15 20 25 30 35 1 0 2 3 4 5 6 f d = 25 Hz, E b / N 0 = 10 dB, D = 5 Solid: analysis Dashed: simulation Averaging interval B Received power standard derivation Figure 6.5 Comparison of received power standard derivation as predicted by analysis and simulation for f d = 25 Hz, B = 20, E b /N 0 = 10 dB, D = 5andT b = 1/8000 s [19]. Reproduced from Chockalingam, A., Dietrich, P., Milstein, L. B. and Rao, R. R. (1998) Performance of closed loop power control in DS-CDMA cellular systems. IEEE Trans. Veh. Technol., 47(3), 774–789, by permission of IEEE. Bit lag Received power auto covariance f d = 25 Hz f d = 75 Hz Dotted: no power control Solid: with power control E b / N 0 = 10 dB, B = 10, D = 5 0 50 100 150 200 250 −5 0 5 10 15 20 25 30 Figure 6.6 The effect on the received power autocovariance function as a result of increasing Doppler frequency, f d (Hz). B = 10, D = 5, E b /N 0 = 10 dB and T b = 1/8000 s [19]. Reproduced from Chockalingam, A., Dietrich, P., Milstein, L. B. and Rao, R. R. (1998) Performance of closed loop power control in DS-CDMA cellular systems. IEEE Trans. Veh. Technol., 47(3), 774–789, by permission of IEEE. 154 POWER CONTROL for different B and f d . No power control curve corresponds to the Jack’s channel model. This will bring a new problem to channel estimation algorithms that require knowledge of the channel correlation coefficients like Wiener or Kalman estimator. The received signal power standard deviation is shown in Figure 6.5 and these results can be used later as a rough indication of the power-control error. From Figure 6.6 one can see that for larger Dopplers the difference in received signal power statistics between the controlled and uncontrolled signal is reduced. In order to analyze some additional issues, a system with the following set of parameters is assumed: 1. The simulated system has an information rate of 8 kbps, such that a B value of 20 corresponds to a 400-Hz update rate, 10 corresponds to 800 Hz, 5 corresponds to 1.6 kHz and so on. 2. D value of 20 corresponds to a loop delay of 2.5 ms, 10 corresponds to 1.25 ms, and so on. The P ∗ value is set to provide the desired E b /N 0 . 3. One should be aware that the inverse algorithm implementations need additional band- width on the return channel to carry the power-control step size, in addition to the power up/down command. BER for such a system is presented in Figure 6.7. The set of parameters is shown in the figure itself. One can see that inverse control, which assumes that a precise analogue value of error E n is transmitted, is the best. One should be aware that this would require additional bandwidth to transmit such information. Figure 6.8 demonstrates how, for a fixed Doppler, the BER reduces with increasing the PC updating rate. The impact of vehicular speed is shown in Figure 6.9. The larger the 0.0001 0.001 0.01 0.1 1 Adaptive delta mod. Inverse PC update rate = 800 Hz D = 5, p r = 0.0 (control command error) Veh. speed = 30 km h −1 E b / N 0 (dB) Bit error rate 0 2 4 6 8 10121416182022 Fixed (1 dB step size) Figure 6.7 Comparison of the BER performance of fixed-step size, adaptive delta modulation, and reverse algorithm, flat Rayleigh fading, P ∗ = E b /N 0 . Update rate = 800 Hz [19]. Reproduced from Chockalingam, A., Dietrich, P., Milstein, L. B. and Rao, R. R. (1998) Performance of closed loop power control in DS-CDMA cellular systems. IEEE Trans. Veh. Technol., 47(3), 774–789, by permission of IEEE. CLOSED-LOOP POWER CONTROL IN DS-CDMA CELLULAR SYSTEM: PROBLEM DEFINITION 155 speed, the less effective the PC and larger the bit error rate. Bit error rate will be larger if delay D is larger as shown in Figure 6.10 because the correction term becomes less and less relevant. The impact of the correction command error p r is shown in Figure 6.11. One can see that even the error of the order of 10% can be tolerated. 0 2 4 6 8 10 12 14 16 18 20 22 0.0001 0.001 0.01 0.1 1 E b / N 0 (dB) Bit error rate AWGN only PC update rate = 1.6 kHz = 800 Hz = 400 Hz = 200 Hz No power control Flat fading (no power control) AWGN D = 0, p r = 0.0 Veh. speed = 30 Figure 6.8 Bit error rate versus E b /N 0 as a function of power-control update rate, flat Rayleigh fading, P ∗ = E b /N 0 ,  = 1 dB [19]. Reproduced from Chockalingam, A., Dietrich, P., Milstein, L. B. and Rao, R. R. (1998) Performance of closed loop power control in DS-CDMA cellular systems. IEEE Trans. Veh. Technol., 47(3), 774–789, by permission of IEEE. 0 2 4 6 8 101214161820 22 0.0001 0.001 0.01 0.1 1 E b / N 0 (dB) Bit error rate AWGN only Veh. speed = 5 km h −1 = 10 km h −1 = 30 km h −1 = 60 km h −1 = 120 km h −1 No power control AWGN D = 5, p r = 0.05 PC update rate = 800 Hz Flat fading (no power control) Figure 6.9 Bit error rate versus E b /N 0 as a function of vehicle speed, flat Rayleigh fading, P ∗ = E b /N 0 ,  = 1 dB, update rate = 800 Hz [19]. Reproduced from Chockalingam, A., Dietrich, P., Milstein, L. B. and Rao, R. R. (1998) Performance of closed loop power control in DS-CDMA cellular systems. IEEE Trans. Veh. Technol., 47(3), 774–789, by permission of IEEE. 156 POWER CONTROL 0 2 4 6 8 10 12 14 16 18 20 22 0.0001 0.001 0.01 0.1 1 E b / N 0 (dB) Bit error rate AWGN only Delay, D = 0 bits = 5 bits = 10 bits = 20 bits = 40 bits No power control AWGN Veh. speed = 30 km h −1 , p r = 0.05 PC update rate = 800 Hz Flat fading (no power control) Figure 6.10 Bit error rate versus E b /N 0 as a function of return channel delay, flat Rayleigh fading, P ∗ = E b /N 0 ,  = 1 dB, update rate = 800 Hz [19]. Reproduced from Chockalingam, A., Dietrich, P., Milstein, L. B. and Rao, R. R. (1998) Performance of closed loop power control in DS-CDMA cellular systems. IEEE Trans. Veh. Technol., 47(3), 774–789, by permission of IEEE. 0.0001 0.001 0.01 0.1 1 E b / N 0 (dB) Bit error rate p r = 0.00 = 0.01 = 0.05 = 0.10 Veh. speed = 30 km h −1 , D = 0 PC update rate = 800 Hz 0246810121416182022 Figure 6.11 Bit error rate versus E b /N 0 as a function of return channel error rate (p r ), flat Rayleigh fading, P ∗ = E b /N 0 ,  = 1 dB, update rate = 800 Hz [19]. Reproduced from Chockalingam, A., Dietrich, P., Milstein, L. B. and Rao, R. R. (1998) Performance of closed loop power control in DS-CDMA cellular systems. IEEE Trans. Veh. Technol., 47(3), 774–789, by permission of IEEE. 6.3 REFERENCE POWER LEVEL Since the measurement of the average received power in practice is very difficult, power- control based on SIR (the effect of noise is assumed to be negligible) is preferable [20]. [...]... 6.8 ADAPTIVE COMMUNICATIONS Previous discussion was focused on the problem of how the system capacity in CDMA network can be maximized by using adaptive PC This concept has been extended to the possibility of adapting other parameters of the system too, in order to maximize the system capacity This has attracted a significant interest of information theory too Recently, in Reference [87], the optimal adaptive. .. rule base Variable step size ∆p Defuzzification interface Forward link channel noise Control power increment Figure 6.18 Adaptive fuzzy power-control system for CDMA mobile radio channels, where z−1 denotes the delay operator [25] Reproduced from Chang, P R and Wang, B C (1996b) Adaptive fuzzy proportional integral power control for a CDMA system with time delay IEEE J Select Areas Commun., 14(9),... Reproduced from Chang, P R and Wang, B C (1996b) Adaptive fuzzy proportional integral power control for a CDMA system with time delay IEEE J Select Areas Commun., 14(9), 1818–1829, by permission of IEEE c11 2 c1 c13 Set point c23 1 c22 c2 Figure 6.22 Crossover points with six different index values [25] Reproduced from Chang, P R and Wang, B C (1996b) Adaptive fuzzy proportional integral power control... with increased energy, depending on whether the initial message estimate was correct The transmitter is thus not required to be adaptive to channel conditions Also, channel coding can benefit from the fed back channel state values For example, the code rate can be changed adaptively as a function of the channel state [72] A system was proposed in Reference [73], in which information is transmitted simultaneously... 1818–1829, by permission of IEEE m11 m12 m13 Response Set point m23 m22 m21 Time Figure 6.23 Maximum–minimum points with six different index values [25] Reproduced from Chang, P R and Wang, B C (1996b) Adaptive fuzzy proportional integral power control for a CDMA system with time delay IEEE J Select Areas Commun., 14(9), 1818–1829, by permission of IEEE 171 FUZZY LOGIC POWER CONTROL c2 2 : (e < 0 →... Table 6.1 as a control rule ∆e A3 A4 c2 m1 m2 A2 a e A1 c1 Figure 6.24 The mapping of the time domain response in phase plane (error state) space [25] Reproduced from Chang, P R and Wang, B C (1996b) Adaptive fuzzy proportional integral power control for a CDMA system with time delay IEEE J Select Areas Commun., 14(9), 1818–1829, by permission of IEEE 172 POWER CONTROL Table 6.1 Rule base frame for... m1 Received signal power (dB) Delayed Set point c1 c2 c1 c2 m2 A1 A2 A3 A4 A 1 A2 A3 A4 t Figure 6.25 The effects of deadtime for a fading process [25] Reproduced from Chang, P R and Wang, B C (1996b) Adaptive fuzzy proportional integral power control for a CDMA system with time delay IEEE J Select Areas Commun., 14(9), 1818–1829, by permission of IEEE Table 6.3 The modified control rule e LN e LP MP... dB fixed-step control when τ = 2Tp , m = 4, fD Tp = 0.05, and the desired mobile unit is initially placed at position that causes a 20-dB path loss [25] Reproduced from Chang, P R and Wang, B C (1996b) Adaptive fuzzy proportional integral power control for a CDMA system with time delay IEEE J Select Areas Commun., 14(9), 1818–1829, by permission of IEEE Table 6.6 Comparison of RMS tracking error achieved... probabilities against the number of users per cell achieved by fuzzy PI control and 1 dB fixed-step control when m = 2, τ = 2Tp , and SI Rth = −15 dB [25] Reproduced from Chang, P R and Wang, B C (1996b) Adaptive fuzzy proportional integral power control for a CDMA system with time delay IEEE J Select Areas Commun., 14(9), 1818–1829, by permission of IEEE 6.7 IMPERFECT POWER CONTROL IN CDMA SYSTEMS The... power and the SIR was exploited Simulations showed that the performance of this PC was better than with PC based on SIR only Su and Shieh [35] compared the performances of PC on the basis of DM, modified adaptive delta modulation (ADM) and differential pulse code modulation (DPCM) The performances of ADM and DPCM control, which use variable-step sizes, were better than that of DM control DPCM control, . to cause additional interference to other users. The extra interference Adaptive WCDMA: Theory And Practice. Savo G. Glisic Copyright ¶ 2003 John Wiley. be adaptive to channel conditions. Also, channel coding can benefit from the fed back channel state values. For example, the code rate can be changed adaptively