Abstract
Original language  English 

Qualification  Doctor of Philosophy 
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Supervisors/Advisors 

Award date  23 Oct 2012 
Place of Publication  Eindhoven 
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Print ISBNs  9789038631837 
DOIs  
Publication status  Published  2012 
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Twodimensional blockbased reception for differentially encoded OFDM systems : a study on improved reception techniques for digital audio broadcasting systems. / Houtum, van, W.J.
Eindhoven : Technische Universiteit Eindhoven, 2012. 170 p.Research output: Thesis › Phd Thesis 1 (Research TU/e / Graduation TU/e)
TY  THES
T1  Twodimensional blockbased reception for differentially encoded OFDM systems : a study on improved reception techniques for digital audio broadcasting systems
AU  Houtum, van, W.J.
PY  2012
Y1  2012
N2  Digital audio broadcast (DAB), DAB+ and TerrestrialDigital Multimedia Broadcasting (TDMB) systems use multicarrier modulation (MCM). The principle of MCM in the DABfamily is based on orthogonal frequency division multiplexing (OFDM), for which every subcarrier is modulated by p 4 differentially encoded quaternary phase shift keying (DEQPSK). In DAB systems convolutional codes and interleaving are used to enable DAB receivers to perform error correction. The objective of the work, described in the thesis, is to improve reception techniques for DAB, DAB+, and TDMB systems. In the thesis, twodimensional (2D) blockbased reception for differentially encoded OFDM systems is investigated. The blocks are based on the time and frequency dimension. Commonly used DAB receivers perform noncoherent twosymbol differential detection (2SDD) with softdecision Viterbi decoding. It is wellknown that 2SDD can be improved if the detection is based on more than two received symbols as, e.g., in noncoherent multisymbol differential detection (MSDD). For improving the performance of the demodulation procedures of DABlike streams, demodulation based on 2D blocks of received symbols with a decomposed demodulation trellis is proposed in the thesis. Peleg and Shamai [58] demonstrated that iterative techniques could increase the performance of the demodulation procedures of DEQPSK streams even further. In the thesis, their approach is generalized to the 2D setting where again the decomposed demodulation trellis is used. In this way a problem connected to the small lengths of the trellises for each subcarrier is solved. The application of these iterative decoding techniques in DAB receivers is only feasible if their complexity can be drastically reduced. A significant complexity reduction is obtained by iterating only in a dominant subtrellis of the decomposed demodulation trellis. In this way, a realtime and bittrue DAB receiver based on iterative decoding techniques is realized In Chapter 2, simulationmodels are introduced. These models are later applied to evaluate the proposed reception methods. The Additive White Gaussian Noise (AWGN) channel model with an input power constraint and the channel model for Mlevel PSK are first discussed. In addition, the TU6 (Typical Urban 6 taps) channel model defined in COST207 [1] is introduced. This channelmodel is commonly used to assess the performance of DAB, DAB+, or TDMB transmission. Finally, the basic elements of a DAB transmitter and a standard receiver are described. In Chapter 3 of the thesis, the state of the art in noniterative detection and decoding techniques for DEQPSK streams with convolutional encoding is described. First, as a reference, coherent detection of DEQPSK with softdecision Viterbi decoding is studied. Then it is demonstrated that 2SDD of DEQPSK with softdecision Viterbi decoding degrades the performance. This noncoherent differential detection scheme can be improved by, for example, MSDD, which is a maximum likelihood procedure for finding a block of information symbols after having observed a block of received symbols. For large numbers of observations, the performance of MSDD approaches the performance of coherent detection of DEQPSK. Since reference symbols (pilots) are lacking for DAB systems, detection based on observing multiple received symbols is a technique that could lead to reception improvement for DAB receivers. By applying this technique, as will be shown later, a DAB receiver approaches the performance of a receiver that performs coherent detection of p 4 DEQPSK with softdecision Viterbi decoding. In Chapter 4, aposteriori symbol probabilities and loglikelihood ratios (LLRs) for coherently detected p 4 DEQPSK are studied. It is demonstrated, as an extension to the results known in the literature, that an approximation of maximum aposteriori (MAP) symbol detection, based on selecting dominant exponentials, leads to MAP sequence detection. To improve the performance towards MAP symbol detection, a better approximation is proposed. This approximation relies on piecewiselinear fitting of the logarithm of the hyperbolic cosine and results in a performance quite close to that of MAP symbol detection. For the coded case, where the symbols are produced by convolutional encoding and Gray mapping, the LLRs are investigated. Again a simple approximation based on selecting dominant exponentials and an improved approximation relying on piecewiselinear fits, is proposed. As in the uncoded case, the improved approximation gives a performance quite close to ideal. These improved approximations are also of interest for DAB systems, as will be shown later, if 2D and trellisbased detection is considered as a reception technique. Peleg et al. [56][57][58] and Chen et al. [18] demonstrated that iterative decoding techniques developed by Benedetto et al. [9] for serially concatenated convolutional codes lead to good results for the concatenation of convolutional and differential encoding, also referred to as TurboDPSK. In Chapter 5 the iterative decoding procedures corresponding to these serially concatenated codes are explained. In this chapter also parallel concatenated systems, turbocodes, first described by Berrou et al. [11] are considered. The iterative decoding procedures for the serially concatenated codes as well as for the turbocodes are based on modified versions of the BCJR algorithm [4]. The approach taken in Chapter 5 to explain these iterative decoding procedures, is similar to the approach Gallager [32] followed to investigate iterative procedures for decoding lowdensity paritycheck (LDPC) codes. This way of explaining iterative decoding procedures for the serially concatenated codes as well as for the turbocodes does not appear in the literature. It is wellknown that iterative (turbo) decoding procedures approach channel capacity, e.g., in the AWGN setting. For that reason, in Chapter 6 and Chapter 7, iterative decoding techniques for DABlike streams are studied. At the time that the DAB standard was proposed, the results of Berrou et al. [11] on turbocodes were not available. As a consequence, it is not a common practice to use iterations in DAB receivers. In Chapter 6, motivated by encouraging results on TurboDPSK, trellis decoding and iterative techniques for DAB receivers are investigated. Specifically, the usage of 2Dblocks and trellis decomposition in decoding is considered. Each 2Dblock consists of a number of adjacent subcarriers of a number of subsequent OFDM symbols. Focussing on 2Dblocks was motivated by the fact that the channel coherencetime is typically limited to a small number of OFDM symbols, and that DABtransmissions use timemultiplexing of services, which limits the number of OFDM symbols in a codeword. Extension in the subcarrier direction is required then to get reliable phase estimates. The trellisdecomposition method allows for an estimation of the unknown channel phase, since this phase relates to subtrellises. Aposteriori subtrellis probabilities are determined, and these probabilities are used for weighting the aposteriori symbol probabilities resulting from all the subtrellises. Alternatively, a dominant subtrellis can be determined from the aposteriori subtrellis probabilities and the aposteriori symbol probabilities corresponding to this dominant subtrellis can be used. This dominant subtrellis approach results in a significant complexity reduction, which is the subject of Chapter 7. In the first part of Chapter 7, complexity reduction of the inner decoder is investigated. This complexity reduction is realized by choosing, based on aposteriori subtrellis probabilities, in two different ways a dominant subtrellis. In the first approach, a method is investigated that is based on finding, at the start of a new iteration, the dominant subtrellis first and then do the forwardbackward processing for demodulation only in this dominant subtrellis. The second approach involves choosing the dominant subtrellis only once, before starting with the iterations. In the second part of Chapter 7, an implementation of a MAP channelphase estimator based on the second dominant subtrellis approach is described. In addition, an implementation of a channelgain estimator based on the received symbols within a 2Dblock is discussed. Finally, a realtime and bittrue DABreceiver is sketched. This DAB receiver operates according to the proposed 2Dblock based iterative decoding procedure within a dominant subtrellis obtained by the second method. The performance improvements of this DAB receiver are evaluated for various numbers of iterations, blocksizes, and Dopplerfrequencies. The main conclusions can be found in Chapter 8. For the noniterative 2Dcase, investigations show that the performance of noncoherent detection based on trellisdecomposition is very close to the performance of coherent detection of DEQPSK. The gain of 2D trellisdecomposition is modest compared to the standard 2SDD technique. Iterative 2D procedures result in a significantly larger gain. In this context, it needs to be emphasized that part of this gain comes from the 2Dprocessing. The dominant subtrellis approach appears to be crucial for achieving an acceptable complexity reduction.
AB  Digital audio broadcast (DAB), DAB+ and TerrestrialDigital Multimedia Broadcasting (TDMB) systems use multicarrier modulation (MCM). The principle of MCM in the DABfamily is based on orthogonal frequency division multiplexing (OFDM), for which every subcarrier is modulated by p 4 differentially encoded quaternary phase shift keying (DEQPSK). In DAB systems convolutional codes and interleaving are used to enable DAB receivers to perform error correction. The objective of the work, described in the thesis, is to improve reception techniques for DAB, DAB+, and TDMB systems. In the thesis, twodimensional (2D) blockbased reception for differentially encoded OFDM systems is investigated. The blocks are based on the time and frequency dimension. Commonly used DAB receivers perform noncoherent twosymbol differential detection (2SDD) with softdecision Viterbi decoding. It is wellknown that 2SDD can be improved if the detection is based on more than two received symbols as, e.g., in noncoherent multisymbol differential detection (MSDD). For improving the performance of the demodulation procedures of DABlike streams, demodulation based on 2D blocks of received symbols with a decomposed demodulation trellis is proposed in the thesis. Peleg and Shamai [58] demonstrated that iterative techniques could increase the performance of the demodulation procedures of DEQPSK streams even further. In the thesis, their approach is generalized to the 2D setting where again the decomposed demodulation trellis is used. In this way a problem connected to the small lengths of the trellises for each subcarrier is solved. The application of these iterative decoding techniques in DAB receivers is only feasible if their complexity can be drastically reduced. A significant complexity reduction is obtained by iterating only in a dominant subtrellis of the decomposed demodulation trellis. In this way, a realtime and bittrue DAB receiver based on iterative decoding techniques is realized In Chapter 2, simulationmodels are introduced. These models are later applied to evaluate the proposed reception methods. The Additive White Gaussian Noise (AWGN) channel model with an input power constraint and the channel model for Mlevel PSK are first discussed. In addition, the TU6 (Typical Urban 6 taps) channel model defined in COST207 [1] is introduced. This channelmodel is commonly used to assess the performance of DAB, DAB+, or TDMB transmission. Finally, the basic elements of a DAB transmitter and a standard receiver are described. In Chapter 3 of the thesis, the state of the art in noniterative detection and decoding techniques for DEQPSK streams with convolutional encoding is described. First, as a reference, coherent detection of DEQPSK with softdecision Viterbi decoding is studied. Then it is demonstrated that 2SDD of DEQPSK with softdecision Viterbi decoding degrades the performance. This noncoherent differential detection scheme can be improved by, for example, MSDD, which is a maximum likelihood procedure for finding a block of information symbols after having observed a block of received symbols. For large numbers of observations, the performance of MSDD approaches the performance of coherent detection of DEQPSK. Since reference symbols (pilots) are lacking for DAB systems, detection based on observing multiple received symbols is a technique that could lead to reception improvement for DAB receivers. By applying this technique, as will be shown later, a DAB receiver approaches the performance of a receiver that performs coherent detection of p 4 DEQPSK with softdecision Viterbi decoding. In Chapter 4, aposteriori symbol probabilities and loglikelihood ratios (LLRs) for coherently detected p 4 DEQPSK are studied. It is demonstrated, as an extension to the results known in the literature, that an approximation of maximum aposteriori (MAP) symbol detection, based on selecting dominant exponentials, leads to MAP sequence detection. To improve the performance towards MAP symbol detection, a better approximation is proposed. This approximation relies on piecewiselinear fitting of the logarithm of the hyperbolic cosine and results in a performance quite close to that of MAP symbol detection. For the coded case, where the symbols are produced by convolutional encoding and Gray mapping, the LLRs are investigated. Again a simple approximation based on selecting dominant exponentials and an improved approximation relying on piecewiselinear fits, is proposed. As in the uncoded case, the improved approximation gives a performance quite close to ideal. These improved approximations are also of interest for DAB systems, as will be shown later, if 2D and trellisbased detection is considered as a reception technique. Peleg et al. [56][57][58] and Chen et al. [18] demonstrated that iterative decoding techniques developed by Benedetto et al. [9] for serially concatenated convolutional codes lead to good results for the concatenation of convolutional and differential encoding, also referred to as TurboDPSK. In Chapter 5 the iterative decoding procedures corresponding to these serially concatenated codes are explained. In this chapter also parallel concatenated systems, turbocodes, first described by Berrou et al. [11] are considered. The iterative decoding procedures for the serially concatenated codes as well as for the turbocodes are based on modified versions of the BCJR algorithm [4]. The approach taken in Chapter 5 to explain these iterative decoding procedures, is similar to the approach Gallager [32] followed to investigate iterative procedures for decoding lowdensity paritycheck (LDPC) codes. This way of explaining iterative decoding procedures for the serially concatenated codes as well as for the turbocodes does not appear in the literature. It is wellknown that iterative (turbo) decoding procedures approach channel capacity, e.g., in the AWGN setting. For that reason, in Chapter 6 and Chapter 7, iterative decoding techniques for DABlike streams are studied. At the time that the DAB standard was proposed, the results of Berrou et al. [11] on turbocodes were not available. As a consequence, it is not a common practice to use iterations in DAB receivers. In Chapter 6, motivated by encouraging results on TurboDPSK, trellis decoding and iterative techniques for DAB receivers are investigated. Specifically, the usage of 2Dblocks and trellis decomposition in decoding is considered. Each 2Dblock consists of a number of adjacent subcarriers of a number of subsequent OFDM symbols. Focussing on 2Dblocks was motivated by the fact that the channel coherencetime is typically limited to a small number of OFDM symbols, and that DABtransmissions use timemultiplexing of services, which limits the number of OFDM symbols in a codeword. Extension in the subcarrier direction is required then to get reliable phase estimates. The trellisdecomposition method allows for an estimation of the unknown channel phase, since this phase relates to subtrellises. Aposteriori subtrellis probabilities are determined, and these probabilities are used for weighting the aposteriori symbol probabilities resulting from all the subtrellises. Alternatively, a dominant subtrellis can be determined from the aposteriori subtrellis probabilities and the aposteriori symbol probabilities corresponding to this dominant subtrellis can be used. This dominant subtrellis approach results in a significant complexity reduction, which is the subject of Chapter 7. In the first part of Chapter 7, complexity reduction of the inner decoder is investigated. This complexity reduction is realized by choosing, based on aposteriori subtrellis probabilities, in two different ways a dominant subtrellis. In the first approach, a method is investigated that is based on finding, at the start of a new iteration, the dominant subtrellis first and then do the forwardbackward processing for demodulation only in this dominant subtrellis. The second approach involves choosing the dominant subtrellis only once, before starting with the iterations. In the second part of Chapter 7, an implementation of a MAP channelphase estimator based on the second dominant subtrellis approach is described. In addition, an implementation of a channelgain estimator based on the received symbols within a 2Dblock is discussed. Finally, a realtime and bittrue DABreceiver is sketched. This DAB receiver operates according to the proposed 2Dblock based iterative decoding procedure within a dominant subtrellis obtained by the second method. The performance improvements of this DAB receiver are evaluated for various numbers of iterations, blocksizes, and Dopplerfrequencies. The main conclusions can be found in Chapter 8. For the noniterative 2Dcase, investigations show that the performance of noncoherent detection based on trellisdecomposition is very close to the performance of coherent detection of DEQPSK. The gain of 2D trellisdecomposition is modest compared to the standard 2SDD technique. Iterative 2D procedures result in a significantly larger gain. In this context, it needs to be emphasized that part of this gain comes from the 2Dprocessing. The dominant subtrellis approach appears to be crucial for achieving an acceptable complexity reduction.
U2  10.6100/IR734135
DO  10.6100/IR734135
M3  Phd Thesis 1 (Research TU/e / Graduation TU/e)
SN  9789038631837
PB  Technische Universiteit Eindhoven
CY  Eindhoven
ER 