RBF-Equalized Adaptive Modulation Having considered the concepts of RBF-assisted channel equalization in Chapter 8, we are now ready to amalgamate these concepts with the AQAM philosophy detailed in Part I of the book. Although it is advantageous for the reader to consult Part I of the book, before delving into Part I1 dedicated to RBF-assisted arrangements, there is sufficient background information in this part of the book for the reader to be able to dispense with reading Part I. Here we will commence by providing a brief introduction to the state-of-the-art in AQAM transmissions over both narrow-band, as well as wide-band channels and then we will refer back to Part I of the book in more detail with the objective of establishing a link betwen the two parts. Based on the foundations of the previous chapter, in this chapter the concept of RBF equalizers is extended to Burst-by-Burst (BbB) Adaptive QAM (AQAM) schemes. As dis- cussed in Part I of the book, BbB AQAM schemes employ a higher-order modulation mode in transmission bursts, when the channel quality is favourable, in order to increase the through- put and conversely, a more robust but lower-order modulation mode is utilized in those trans- mission bursts, where the instantaneous channel quality drops. The modem mode switching regime will be detailed in more depth during our further discourse. We will show that this RBF-AQAM scheme naturally lends itself to accurate channel quality estimation. We will provide an outline of our various assumptions and the description of the simulation model, leading to our RBF-AQAM performance studies. This scheme is shown to give a significant improvement in terms of the mean BER and bits per symbol (BPS) performance compared to that of the individual fixed modulation modes. Let us now commence with a brief background on adaptive modulation in both narrow- and wide-band fading channel environments. 385 Adaptive Wireless Tranceivers L. Hanzo, C.H. Wong, M.S. Yee Copyright © 2002 John Wiley & Sons Ltd ISBNs: 0-470-84689-5 (Hardback); 0-470-84776-X (Electronic) 386 CHAPTER 9. RBF-EOUALIZED ADAPTIVE MODULATION 9.1 Background to Adaptive Modulation in a Narrowband Fading Channel We summarise here the principles of adaptive modulation in a narrow-band Rayleigh fading channel environment. In a narrow-band channel, as a result of channel fading, the short-term SNR can be severely degraded. This typically degrades the short-term BER at the receiver. Again, the concept of adaptive modulation is to employ a higher modulation mode, when the channel quality is favourable, in order to increase the throughput and conversely, a more robust modulation mode is employed, in order to provide an acceptable BER, when the chan- nel exhibits a deep fade. Thus, adaptive modulation is not only used to combat the fading effects of a narrow-band channel, but it also attempt to maximise the throughput. This idea is somewhat reminiscent of invoking a coarse power control scheme although without the detri- mental effects of inflicting increased interferences upon other system users due to powering up during the intervals of low channel quality. In our work we used a variable number of modulation levels and again, we refer to this scheme as AQAM, while maintaining a constant transmitted power. Adaptive modulation can only be invoked in the context of duplex transmissions, since some method of informing the transmitter of the quality of the link as perceived by the re- ceiver is required unless an explicit feedback control channel is provided by the system. More explicitly, in adapting the modulation mode, a signalling regime has to be implemented in order to harmonise the operation of the transmitter and receiver with regards to the adap- tive modem mode parameters. The range of signalling options is summarized in Figure 9.1 for both so-called open-loop and closed-loop signalling. For example, adaptive modulation can be applied in a time division duplex (TDD) arrangement, where the uplink and down- link transmissions are time-multiplexed onto the same carrier as depicted in Figure 9.2. If the channel quality of the uplink and downlink can be considered similar, an open-loop signalling system can be implemented, where the modulation mode can be adapted at the transmitter based on the information about the channel quality acquired during its receiving mode. This open-loop system is portrayed in Figure 9.l(a). The specific modem mode invoked has to be explicitly signalled by the transmitter to the receiver along with the reverse-direction in- formation and it must be strongly protected against transmission errors, in order to avoid catastrophic BER degradations in case of modem mode signalling errors. By contrast, if the above channel quality predicability is not applicable - for example due to the presence of co- channel interference, etc. - the closed-loop based signalling system shown in Figure 9.l(b) can be implemented. This would be typical in a frequency division duplex (FDD) based sys- tem, where the uplink and downlink transmission frequency bands are different. Explicitly, the receiver has to instruct the remote transmitter concerning the modem mode to be used for meeting the receiver’s target integrity requirements. The modem mode side-information signalling requirement is the same for both of the above signalling scenarios. For example, two bits per transmission burst are required to signal four different modem modes. However, the channel quality information will be based on a more obsolete channel quality estimate in the dissimilar uplinWdownlink scenario, when the receiver instructs the remote transceiver concerning the modem mode to be used for meeting the receiver’s BER target. It was shown in the context of a Kalman-filtered DFE block turbo coded AQAM scheme that it is feasible to refrain from explicitly signalling the modem modes upon invoking blind mode detection and hence increase the associated throughput [215]. 9.1. BACKGROUND TO ADAPTIVE MODULATION IN A NARROWBAND FADING CHANNEL 387 I Uplink I * MS ._____.__ _________ BS Evaluate perceived Evaluate perceived channel quality and channel quality and decide the transmission decide the transmission Downlink mode of local TX Signal modem modes used by MS + 1 Signal modem modes \ mode of local TX _._____ ~~~.___ ___ used by BS (a) Open-loop based signalling MS Evaluate perceived channel quality and signal the requested transmission mode to the BS TX Signal modem modes Evaluate perceived to be used by BS channel quality and signal the requested Downlink transmission mode - to the MS TX Signal modem modes to be used by MS (b) Close-loop based signalling Figure 9.1: Closed- and open-loop signalling regimes for AQAM, where BS represents the Base Sta- tion, MS denotes the Mobile Station and the transmitter is represented by TX. Having discussed briefly the principle of adaptive modulation and the associated sce- narios, where it can be applied, we can now explore the methology used for choosing the appropriate number of modulation levels. Torrance [ 1451 used the instantaneous received power as the channel quality measure. The estimated instantaneous received power was used to select the suitable modulation mode by comparing the received power against a set of switching thresholds, l,, n = 1, . . . ,4, as de- picted in Figure 9.3. These switching thresholds govern the tradeoff between the mean BER and the BPS performance of the system. If low switching thresholds are used, the probability of employing a high-order modulation mode increases, thus yielding a better BPS perfor- mance. Conversely, if high switching thresholds are used, a low-order modulation mode is employed more frequently, resulting in an improved mean BER performance. In his efforts to derive upper-bound performance bounds Torrance [ 1451 assumed perfect channel quality estimation and compensation, perfect knowledge of the modulation mode at the receiver and perfect estimation of the expected received power prior to transmission. 388 CHAPTER 9. RBF-EOUALIZED ADAPTIVE MODULATION Mobile Station Mobile Station I- receives -1- transmits -1 < QAM symbols QAM symbols TDD frames I _ -_ -_ QAM symbols QAM symbols ~~ i- ~ delay ~ Propagation Base Station A Base Station receives , transmits :- The channel quality required +: I to be approximately constant I Figure 9.2: The TDD framing structure used in our AQAM system. Short Term SNR Time p, 64QAM W BPSK No Transmission (NO TX) Figure 9.3: Stylised profile of the short-term received SNR, which is used to choose the next modula- tion mode of the transmitter in TDD mode. 9.2. BACKGROUND ON ADAPTIVE MODULATION IN A WIDEBAND FADING CHANNEL 389 Figure 9.4: Decision-feedback equalizer schematic. Ik - + Webb and Steele [4] used the received signal strength and the BER as channel quality measures in a flat Rayleigh-fading environment. The signal to co-channel interference ratio and the expected delay spread of the channel was used by Sampei, Komaki and Morinaga [59] as the criteria to switch amongst the modulation modes and the legitimate modulation rates. They used ;-rate QPSK, ;-rate QPSK, QPSK, 16-QAM, 64-QAM in a narrow-band channel environment. Sampei, Morinaga and Hamaguchi utilized the signal to noise ratio and the normalized delay spread as the channel quality measure. For a review of other work that has been conducted using adaptive modulation, the reader is referred to the previous chapters. 9.2 Background on Adaptive Modulation in a Wideband Fading Channel In this section we will initially extend the AQAM concept to wideband fading channel envi- ronments by employing conventional channel equalization. We will briefly summarise, how the performance of the equalizer and the AQAM scheme can be jointly optimized. As expected, the AQAM switching criteria of the narrow-band scenario mentioned in Section 9.1 has to be modified for the wideband channel environment. In Torrance’s paper [l451 for example, the quality of the channel was determined on the basis of the short-term SNR, which was then used as a metric in order to choose the appropriate modulation mode for the transmitter. However, in a wideband environment, the SNR metric is not reliable in quantifying the quality of the channel, where the existence of the multipath components in the wideband channel produces not only power attenuation of the transmission burst, but also intersymbol interference, as discussed in Section 8.1. Even when the channel SNR is high, QAM transmissions over wideband Rayleigh fading channels are subjected to error bursts due to 1%. Consequently, the metric required to quantify the channel quality has to be redefined, in order to incorporate the effects of the wideband channel. Wong and Hanzo [32,296] approached this problem by formulating a two-step method- ology to mitigate the effects of the dispersive wideband channel. The first step employed a conventional Kalman-filtering based DFE, in order to eliminate most of the ISI. In the second 390 CHAPTER 9. RBF-EQUALIZED ADAPTIVE MODULATION step, the signal to noise plus residual interference ratio at the output of the equalizer was calculated based on the channel estimate. This ratio was referred to as the pseudo SNR, since it exhibited a Gaussian-like distribution and it was used as a metric to switch the modulation mode. Again, in [32,296], Wong used the conventional Kalman-filtering based DFE depicted in Figure 9.4. If the IS1 due to past detected symbols is eliminated by the feedback filter, then the wanted signal power, the residual IS1 signal power and the effective noise power can be expressed as follows [ 1051: Wanted Signal Power = E [lq01,1~] , (9.1) Residual IS1 Signal = c E [lqkln-k12] , (9.2) -1 k=-K1 0 Effective Noise Power = NO c (cj 12, (9.3) j=-K, 72 = -00,. . . ,m, (9.4) where qk = xj=-KI cj fk-3, cj, j = -K1, . . . , 0 are the feedforward tap coefficients, cj, j = 1, . . . , K2 are the feedback tap coefficients, fk is the kth impulse response tap of the channel and NO is the noise power. Therefore, the pseudo SNR output of the DFE, TDFE, can be calculated as follows: 0 The calculated pseudo SNR output of the DFE, ?DE, is then compared against a set of switch- ing threshold levels, l,, stored in a lookup table. The pseudo SNR output of the DFE, TDFE, is used for invoking the appropriate modem mode as follows [296]: NO TX if YDFE II BPSK if 11 < YDFE < 12 Modulation Mode = 4-QAM if 12 < YDFE < 13 (9.6) 16-QAM if 13 < TDFE < 14 1 64-QAM if YDFE > 14, where I,, n = 1, . . . ,4 are the pseudo-SNR thresholds levels, and Powell’s Multi-dimensional Line Minimization technique [297] was used to optimize the switching levels I, in [32]. 9.3 Brief Overview of Part I of the Book In Part I of this monograph we commenced by analysing the performance of the DFE using multi-level modulation schemes, when communicating over static multi-path Gaussian chan- nels as shown in Figure 2.10. These discussions were further developed in the context of a multi-path fading channel environment, where the recursive Kalman algorithm was invoked in order to track and equalize the received linearly distorted data, as evidenced by Figure 3.16. Explicitly, an adaptive CIR estimator and DFE were implemented in two different re- ceiver structures, as shown in Figure 3.14, while their performances were compared in Figure 9.3. BRIEF OVERVIEW OF PART I OF THE BOOK 391 2.10. In this respect, Structure 1, which utilized the adaptive CIR estimator provided a better performance, when compared to that of Structure 2, which involved the adaptive DFE, as evidenced by Table 3.10. Furthermore, the complexity of Structure 2 was higher than that of Structure 1, which was studied in Section 3.4. However, these experiments were conducted in a fast start-up environment, where adaptation was restricted to the duration of the training se- quence length. By contrast, if the adaptation was invoked over the entire transmission frame using a decision directed scheme, the complexity advantage of Structure 1 was eroded, as discussed in Section 3.5. The application of these fast adapting and accurate CIR estimators was crucial in a wideband AQAM scheme, where the CIR variation across the transmission frame was slow. In these experiments valuable insights were obtained with regards to the de- sign of the equalizer and to the characteristics of the adaptive algorithm itself. This provided a firm foundation for the further investigation of the proposed wideband AQAM scheme. Following our introductory chapters, in Chapter 4 the concept of adaptive modulation cast in the context of a narrow-band environment was introduced in conjunction with the application of threshold-based power control. In this respect, power control was applied in the vicinity of the switching thresholds of the AQAM scheme. The associated performance was recorded in Table 4.4, where the trade-off between the BER and BPS performance was highlighted. The relative frequency of modulation mode switching was also reduced at the cost of a slight BER degradation. However, the complexity of the scheme increased due to the implementation of the power control regime. Moreover, the performance gains portrayed at this stage represented an upper-bound estimate, since perfect power control was applied. Consequently, the introduction of threshold-based power control in a narrow-band AQAM did not offer an attractive complexity versus performance gain trade-off. The concept of AQAM was subsequently invoked in the context of a wideband channel, where the DFE was utilized in conjunction with the AQAM modem mode switching regime. Due to the dispersive multi-path characteristics of the wideband channel, a metric based on the output SNR of the DFE was proposed in order to quantify the channel’s quality. This ensured that the wideband channel effects were mitigated by the employment of AQAM and equalization techniques. Subsequently a numerical model based on this criterion was established for the wideband AQAM scheme, as evidenced by Figures 4.16 and 4.17. The wideband AQAM switching thresholds were optimised for maintaining a certain target BER and BPS performance, as shown in Figure 4.3.5. The wideband AQAM BPS throughput performance was then compared to that of the constituent fixed modulation modes, where BPS/SNR gains of approximately 1 - 3dB and 7 - 9dB were observed for target BERs of 1% and 0.01%, respectively. However, as a result of the assumption made in Section 4.3.1, these gains constituted an upper bound estimate. Nevertheless, the considerable gains achieved provided further motivation for the research of wideband AQAM schemes. The concept of wideband coded AQAM was presented in Chapter 5, where turbo block coding was invoked in the switching regime for different wideband AQAM schemes. The key characteristics of these four schemes, namely those of the FCFI-TBCH-AQAM, FCVI- TBCH-AQAM, P-TBCH-AQAM and VR-TBCH-AQAM arrangements, were highlighted in Table 5.10 in terms of the respective turbo interleaver size and the coding rate utilized. The general aim of using turbo block coding in conjunction with a high code rates was to increase the effective BPS transmission throughput, which was achieved, as shown in Table 5.1 1 for the arrangement that we referred to as the Low-BER scheme. In this respect, all the schemes produced gains in terms of their BER and BPS performance, when compared to the uncoded 392 CHAPTER 9. RBF-EQUALIZED ADAPTIVE MODULATION AQAM scheme, which was optimised for a BER of 0.01%. This comparison was recorded in Table 5.1 1 for the four different turbo coded AQAM schemes studied. The FCFI-TBCH-AQAM scheme exhibited a better throughput gain, when compared to the other schemes. This was achieved as a result of the larger turbo interleaver used in this scheme, which also incurred a higher delay. The size of the turbo interleaver was then varied, while retaining identical coding rate for each modulation mode, resulting in the FCVI-TBCH-AQAM scheme, where burst-by-burst decoding was achieved at the receiver. The BPS throughput performance of this scheme was also compared to that of the constituent fixed modulation modes, which utilized different channel interleaver sizes, as shown in Fig- ure 5.1 1. SNR gains of approximately 1.5 and 5.0dB were achieved by the adaptive scheme for a target BERs of 0.01%, when compared to the fixed modulation modes using the small- and large-channel interleavers, respectively. By contrast, for a target BER of 1% only modest gains were achieved by the wideband AQAM scheme. These apparently low gains were the consequence of an ’unfair’ comparison, since sibnificantly larger turbo interleaver and chan- nel interleaver sizes were utilized by the fixed modulation modes. Naturally, his resulted in a high transmission delay for the fixed modulation modes. By contrast, the FCVI-TBCH- AQAM scheme employed low-latency instantaneous burst-by-burst decoding, which is im- portant in real-time interactive communications. The size of the turbo interleaver and the coding rate was then varied according to the modulation mode, in order to ensure burst-by-burst decoding at the receiver. This resulted in the P-TBCH-AQAM scheme, which also incorporated un-coded modes for the sake of increasing the achievable throughput. Finally, the VR-TBCH-AQAM scheme activated dif- ferent code rates in conjunction with the different modulation modes. These schemes pro- duced a higher maximum throughput due to the utilization of higher code rates. However, the SNR gains in terms of both the BER and BPS performance degraded, when compared to the FCFI-TBCH-AQAM scheme as a result of the reduced-size turbo interleaver used. Further- more, the utilization of higher code rates for the VR-TBCH-AQAM arrangement resulted in a higher decoding complexity. Once again, these comparisons are recorded in Table 5.7. Similar characteristics were also observed in the context of the High-BER candidate scheme and in conjunction with the near-error-free schemes. However, the performance gains of the High-BER schemes were less than those of the Low-BER schemes. This was primarily due to the lower channel coding gain achieved at higher BERs and due to the smaller turbo interleaver size used. The advantages of burst-by-burst decoding were also exploited in the context of blindly detecting the modulation modes. In this respect, the channel coding information and the mean square phasor error was utilized in the hybrid SD-MSE modulation mode detection algorithm of Section 5.6.2 characterized by Equation 5.6. Furthermore, concatenated m- sequences [ 1691 were used in order to detect the NO TX mode while also estimating the channel’s quality. The performance of this algorithm was shown in Figure 5.16, where a modulation mode detection error rate (DER) of lop4 was achieved at an average channel SNR of 15dB. However, the complexity incurred by this algorithm was high due to the multiple channel decoding processes required for each individual modulation mode. Turbo convolutional coding was then introduced and its performance using fixed modu- lation modes was compared to that of turbo block coding, as shown in Figure 5.23. A BER versus SNR degradation of approximately 1 - 2dB was observed for the turbo convolutional coded performance at a BER of However, the complexity was significantly reduced, 9.3. BRIEF OVERVIEW OF PART I OF THE BOOK 393 namely by a factor of seven, when compared to the previously studied turbo block coded schemes. Turbo convolutional coding was then incorporated in our wideband AQAM scheme and its performance was compared to that of the turbo block coded AQAM schemes, where the results were similar, as evidenced by Figure 5.24. Consequently the complexity versus performance gain trade-off was more attractive for our turbo convolutional coded AQAM schemes. In our continued investigations of coded AQAM schemes, turbo equalization was invoked where BPS/SNR gains of approximately 1 - 2dB were achieved by our AQAM scheme. In achieving this performance, iterative CIR estimation was implemented based on the LMS algorithm, which approached the perfect CIR estimation assisted AQAM performance, as shown in Figure 5.3 1. However, the implementation of this scheme was severely hindered by the high complexity incurred, which increased exponentially in conjunction with higher-order modulation modes and longer CIR memory. The chapter was concluded with a system design example cast in the context of TCM, TTCM and BICM based AQAM schemes, which were studied under the constraint of a sim- ilar implementational complexity. The BbB adaptive TCM and TTCM schemes were inves- tigated when communicating over wideband fading channels both with and without channel interleaving and they were characterised in performance terms over the COST 207 TU fading channel. When observing the associated BPS curves, adaptive TTCM exhibited up to 2.5 dB SNR-gain for a channel interleaver length of four transmission bursts in comparison to the non-interleaved scenario, as it was evidenced in Figure 5.40. Upon comparing the associated BPS curves, adaptive TTCM also exhibited up to 0.7 dB SNR-gain compared to adaptive TCM of the same complexity in the context of System 11, while maintaining a target BER of less than 0.01 %, as it was shown in Figure 5.44. Finally, adaptive TCM performed better, than the adaptive BICM benchmarker in the context of System I, while the adaptive BICM- ID scheme performed marginally worse, than adaptive TTCM in the context of System 11, as it was discussed in Section 5.1 1.5. In Chapter 6 following a brief introduction to several fading counter-measures, a general model was used for describing various adaptive modulation schemes employing various con- stituent modulation modes, such as PSK, Star QAM and Square QAM, as one of the attractive fading counter-measures. In Section 6.3.3.1, the closed form expressions were derived for the average BER, the average BPS throughput and the mode selection probability of the adap- tive modulation schemes, which were shown to be dependent on the mode-switching levels as well as on the average SNR. In Sections 6.4.1, 6.4.2 and 6.4.3 we reviewed the existing techniques devised for determining the mode-switching levels. Furthermore, in Section 6.4.4 the optimum switching levels achieving the highest possible BPS throughput were studied, while maintaining the average target BER. These switching levels were developed based on the Lagrangian optimization method. Then, in Section 6.5. l the performance of uncoded adaptive PSK, Star QAM and Square QAM was characterised, when the underlying channel was a Nakagami fading channel. It was found that an adaptive scheme employing a Ic-BPS fixed-mode as the highest throughput constituent modulation mode was sufficient for attaining all the benefits of adaptive mod- ulation, while achieving an average throughput of up to Ic - 1 BPS. For example, a three- mode adaptive PSK scheme employing No-Tx, l-BPS BPSK and 2-BPS QPSK modes at- tained the maximum possible average BPS throughput of 1 BPS and hence adding higher- throughput modes, such as 3-BPS 8-PSK to the three-mode adaptive PSK scheme resulting 394 CHAPTER 9. RBF-EQUALIZED ADAPTIVE MODULATION in a four-mode adaptive PSK scheme did not achieved a better performance across the 1 BPS throughput range. Instead, this four-mode adaptive PSK scheme extended the maximum BPS throughput achievable by any adaptive PSK scheme to 2 BPS, while asymptotically achieving a throughput of 3 BPS, as the average SNR increases. On the other hand, the relative SNR advantage of adaptive schemes in comparison to fixed-mode schemes increased as the target average BER became lower and decreased as the fading became less severe. More explicitly, less severe fading corresponds to an increased Nakagami fading parameter m, to an increased number of diversity antennas, or to an in- creased number of multi-path components encountered in wide-band fading channels. As the fading becomes less severe, the average BPS throughput curves of our adaptive Square QAM schemes exhibit undulations owing to the absence of 3-BPS, 5-BPS and 7-BPS square QAM modes. The comparisons between fixed-mode MC-CDMA and adaptive OFDM (AOFDM) were made based on different channel models. In Section 6.5.4 it was found that fixed-mode MC- CDMA might outperform adaptive OFDM, when the underlying channel provides sufficient diversity. However, a definite conclusion could not be drawn since in practice MC-CDMA might suffer from MU1 and AOFDM might suffer from imperfect channel quality estimation and feedback delays. systems were investigated in Section 6.5.5. The coded schemes reduced the required average SNR by about 6dB-7dB at a throughput of 1 BPS, achieving near error-free transmission. It was also observed in Section 6.5.5 that increasing the number of transmit antennas in adap- tive schemes was not very effective, achieving less than 1dB SNR gain, due the fact that the transmit power per antenna had to be reduced in order to limit the total transmit power for the sake of a fair comparison. The practical issues regarding the implementation of the advocated wideband AQAM scheme was analysed in Chapter 7. The impact of error propagation in the DFE was high- lighted in Figure 7.2, where the BER degradation was minimal and the target BERs were achieved without any degradation to the transmission throughput performance. The impact of channel quality estimation latency was also studied, where the sub frame based TDDRDMA system of Section 7.2. l was implemented. In this system, a channel quality estimation delay of 2.3075ms was imposed and the channel quality estimates were predicted using a linear pre- diction technique. In this practical wideband AQAM scheme, SNR gains of approximately 1.4dB and 6.4dB were achieved for target BERs of 1% and 0.01%, when compared to the per- formance of the constituent fixed modulation modes. This was shown graphically in Figure 7.11. CC1 was then subsequently introduced in Section 7.3, where in terms of channel quality estimation, the minimum average SIR that can be tolerated by the wideband AQAM scheme was approximately lOdB, as evidenced by Figure 7.14. In order to mitigate the impact of CC1 on the demodulation process, the JD-”SE-BDFE scheme using an embedded con- volutional encoder was invoked, where the performance was shown in Figure 7.21 and 7.22 for the fixed modulation modes and for the wideband AQAM scheme, respectively. The per- formance gains achieved by the wideband AQAM scheme were approximately 2 - 4dB and 7 - 9dB for the target BERs of 1% and 0.01%, when compared to the performance of the as- sociated fixed modulation modes. However, these gains constituted an upper bound estimate, since perfect channel estimation of the reference user and the interferer was assumed. Concatenated space-time block coded and turbo convolutional-coded adaptive multi-carrier [...]... 10p2 For the adaptive scheme, which did not incorporate transmission blocking, the performance of adaptive modulation was better or equivalent to the performance of BPSK in terms of the mean BER and mean BPS forthe SNR range betweenOdB and 9dB.At the channel SNR 9dB, even though of the mean BER performance was equivalent for the adaptive scheme and the BPSK scheme, the mean BPS for the adaptive scheme... for an equivalent mean BER.The adaptive scheme that utilized transmission blocking achieved a mean BER below 1% the channel SNR of 12dB, even though the mean BER performance At was equivalent for the BPSK scheme and the adaptive scheme with transmission blocking, the mean BPS for the adaptive scheme improved by a factor of 2 As the SNR improved, the performance of the adaptive schemes both with and... SNR range of 9dB to 16dB, the adaptive scheme outperformed the 4-QAM scheme in terms of the mean BER performance At the channel SNR of 16dB, the mean BERs of both schemes are equivalent, although the mean BPS of the adaptive scheme is 2.7, resulting in a BPS improvement by a factor of 1.35, when compared to 4-QAM At the channel SNR of 26dB, the mean BPS improvement of the adaptive scheme isby a factor... per symbol increment upon using AQAM is higher than the relative bit error ratio increment, then the mean BER of the adaptive scheme will be improved Consequently the adaptive mean BER can be lower than that of BPSK The probability of encountering each modulation mode employed in the adaptive scheme based on the estimated short-term BER switching mechanism is shown in Figure 9.10 and Figure 9.1 1 for... 3, respectively) can only be achieved for the AQAM scheme with and without transmission blocking, if the channel SNR is in excess of about 22dB Thus, the advantage of using an adaptive scheme with transmission blocking 404 CHAPTER 9 RBF-EQUALIZED MODULATION ADAPTIVE BPSK BER AQAMDFE RBF 4 QAM BER - 0 16 QAM BER 64 QAM BER * AQAMDFE RBF - BPS: BER: TX blocking without TX blocking 0 * - TX blocking... proceeding, the section will present the assumptions next used, when we employ this scheme a wideband channel environment in CHAPTER 9 RBF-EQUALIZED ADAPTIVE MODULATION 398 9.4.3 Best-case PerformanceAssumptions In deriving the best-case performancethis joint adaptive modulation and RBF based equalof ization scheme, the following assumptions are made: 1 Perfect CIR estimation or channel state estimation... the SNR improved, the performance of the adaptive schemes both with and without transmission blocking con- 9.4 JOINT ADAPTIVE MODULATION AND RBF BASED EQUALIZATION 403 verged, since the probability of encountering high short-term BERs reduced The mean BER and mean BPS performance of both adaptive schemes converged to that of 64-QAM for high SNRs, where 64-QAM becomes the dominant modulation mode Similar... transmission, i.e for the lop4 target BER scheme in Figure 9.9(b) However, we note that for the SNR range between 8dB to 20dB, the mean BER of the adaptive scheme without transmission blocking was better, than that of BPSK This phenomenon was also observed in the narrowband adaptive modulation scheme of [l451 and in the wideband joint AQAM and DFE scheme of [32,296], which can be explained as follows The mean...9.4 JOINT ADAPTIVE MODULATION AND RBF BASED EQUALIZATION 395 Noise l I Burst Threshold Switching Short Term Probability of Bit Error of the Data Burst Look-up Table Figure 9.5: System schematic of the joint adaptive modulation and RBF equalizer scheme The concept of segmented wideband AQAM was then introduced,... for the BER = lo-’ and BER = lop4 schemes, respectively These are the points, where the performance of the adaptive schemes with and without transmission blocking converged, as demonstrated in Figure 9.9.We observed that the probabilities of the 4-QAM, 16-QAM and 64-QAM modes being utilized for the adaptive scheme with and without transmission blocking were fairly similar This is because introducing transmission . RBF-EOUALIZED ADAPTIVE MODULATION 9.1 Background to Adaptive Modulation in a Narrowband Fading Channel We summarise here the principles of adaptive modulation. Figure 5.44. Finally, adaptive TCM performed better, than the adaptive BICM benchmarker in the context of System I, while the adaptive BICM- ID scheme