The objective of this thesis is to develop tools for the analysis and optimization of an iterative receiver. These tools can be applied to most soft-in soft-out (SISO) receiver components. For illustration purposes we consider a multi-user DS-CDMA system with forward error correction that employs iterative multi-user detection based on soft interference cancellation and single user decoding. Optimized power levels combined with adaptive scheduling allows for efficient utilization of receiver resources for heavily loaded systems.¶ Metric transfer analysis has been shown to be an accurate method of predicting the convergence behavior of iterative receivers. EXtrinsic Information (EXIT), fidelity (FT) and variance (VT) transfer analysis are well-known methods, however the relationship between the different approaches has not been explored in detail. We compare the metrics numerically and analytically and derive functions to closely approximate the relationship between them. The result allows for easy translation between EXIT, FT and VT methods. Furthermore, we extend the $J$ function, which describes mutual information as a function of variance, to fidelity and symbol error variance, the Rayleigh fading channel model and a channel estimate. These $J$ functions allow the \textit{a priori} inputs to the channel estimator, interference canceller and decoder to be accurately modeled. We also derive the effective EXIT charts which can be used for the convergence analysis and performance predictions of unequal power CDMA systems.¶ The optimization of the coded DS-CDMA system is done in two parts; firstly the received power levels are optimized to minimize the power used in the terminal transmitters, then the decoder activation schedule is optimized such that the multi-user receiver complexity is minimized. The uplink received power levels are optimized for the system load using a constrained nonlinear optimization approach. EXIT charts are used to optimize the power allocation in a multi-user turbo-coded DS-CDMA system. We show through simulation that the optimized power levels allow for successful decoding of heavily loaded systems with a large reduction in the convergence SNR.¶ We utilize EXIT chart analysis and a Viterbi search algorithm to derive the optimal decoding schedule for a multi component receiver/decoder. We show through simulations that decoding delay and complexity can be significantly reduced while maintaining BER performance through optimization of the decoding schedule.

Doctor of Philosophy(PhD) / In this thesis, we propose and investigate promising approaches for interference mitigation in multiple input multiple output (MIMO) and code division multiple access (CDMA) systems. Future wireless communication systems will have to achieve high spectral efficiencies in order to meet increasing demands for huge data rates in emerging Internet and multimedia services. Multiuser detection and space diversity techniques are the main principles, which enable efficient use of the available spectrum. The main limitation for the applicability of the techniques in these practical systems is the high complexity of the optimal receiver structures. The research emphasis in this thesis is on the design of a low complexity interference suppression/cancellation algorithm. The most important result of our research is the novel design of interference cancellation receivers which are adaptive and iterative and which are of low computational complexity. We propose various adaptive iterative receivers, based on a joint adaptive iterative detection and decoding algorithm. The proposed receiver can effectively suppress and cancel co-channel interference from the adjacent antennas in the MIMO system with a low computation complexity. The proposed adaptive detector, based on the adaptive least mean square (LMS) algorithm, is investigated and compared with the non-adaptive iterative receiver. Since the LMS algorithm has a slow convergence speed, a partially filtered gradient LMS (PFGLMS) algorithm, which has a faster convergence speed, is proposed to improve the convergence speed of the system. The performance and computational complexity of this receiver are also considered. To further reduce the computational complexity, we apply a frequency domain adaptation technique into the adaptive iterative receivers. The system performance and complexity are investigated. It shows that the computational complexity of the frequency domain based receiver is significantly lower than that of the time domain based receiver with the same system performance. We also consider applications of MIMO techniques in CDMA systems, called MIMO-CDMA. In the MIMO-CDMA, the presence of the co-channel interference (CCI) from the adjacent antennas and multiple access interference (MAI) from other users significantly degrades the system performance. We propose an adaptive iterative receiver, which provides the capability to effectively suppress the interference and cancel the CCI from the adjacent antennas and the MAI from other users so as to improve the system performance. The proposed receiver structure is also based on a joint adaptive detection and decoding scheme. The adaptive detection scheme employs an adaptive normalized LMS algorithm operating in the time and frequency domain. We have investigated and compared their system performance and complexity. Moreover, the system performance is evaluated by using a semi-analytical approach and compared with the simulation results. The results show that there is an excellent agreement between the two approaches.

Iterative processing has been shown to be very effective in multiuser space-time block coding (STBC) systems. The complexity and efficiency of an iterative receiver depend heavily on how the log-likelihood ratios (LLRs) of the coded bits are computed and exchanged at the receiver among its three major components, namely the multiuser detector, the maximum a posterior probability (MAP) demodulators and the MAP channel decoders. This thesis first presents a method to quantitatively measure the system complexities with floating-point operations (FLOPS) and a technique to evaluate the iterative receiver's convergence property based on mutual information and extrinsic information transfer (EXIT) charts.<p>Then, an integrated iterative receiver is developed by applying the sigma mappings for M-ary quadrature amplitude modulation (M-QAM) constellations. Due to the linear relationship between the coded bits and the transmitted channel symbol, the multiuser detector can work on the bit-level and hence improves the convergence property of the iterative receiver. It is shown that the integrated iterative receiver is an attractive candidate to replace the conventional receiver when a few receive antennas and a high-order M-QAM constellation are employed.<p> Finally, a more general two-loop iterative receiver is proposed by introducing an inner iteration loop between the MAP demodulators and the MAP convolutional decoders besides the outer iteration loop that involves the multiuser detection (MUD) as in the conventional iterative receiver. The proposed two-loop iterative receiver greatly improves the iteration efficiency. It is demonstrated that the proposed two-loop iterative receiver can achieve the same asymptotic performance as that of the conventional iterative receiver, but with much less outer-loop iterations.

Iterative processing has been shown to be very effective in multiuser space-time block coding (STBC) systems. The complexity and efficiency of an iterative receiver depend heavily on how the log-likelihood ratios (LLRs) of the coded bits are computed and exchanged at the receiver among its three major components, namely the multiuser detector, the maximum a posterior probability (MAP) demodulators and the MAP channel decoders. This thesis first presents a method to quantitatively measure the system complexities with floating-point operations (FLOPS) and a technique to evaluate the iterative receiver's convergence property based on mutual information and extrinsic information transfer (EXIT) charts.<p>Then, an integrated iterative receiver is developed by applying the sigma mappings for M-ary quadrature amplitude modulation (M-QAM) constellations. Due to the linear relationship between the coded bits and the transmitted channel symbol, the multiuser detector can work on the bit-level and hence improves the convergence property of the iterative receiver. It is shown that the integrated iterative receiver is an attractive candidate to replace the conventional receiver when a few receive antennas and a high-order M-QAM constellation are employed.<p> Finally, a more general two-loop iterative receiver is proposed by introducing an inner iteration loop between the MAP demodulators and the MAP convolutional decoders besides the outer iteration loop that involves the multiuser detection (MUD) as in the conventional iterative receiver. The proposed two-loop iterative receiver greatly improves the iteration efficiency. It is demonstrated that the proposed two-loop iterative receiver can achieve the same asymptotic performance as that of the conventional iterative receiver, but with much less outer-loop iterations.

Doctor of Philosophy(PhD) / In this thesis, we propose and investigate promising approaches for interference mitigation in multiple input multiple output (MIMO) and code division multiple access (CDMA) systems. Future wireless communication systems will have to achieve high spectral efficiencies in order to meet increasing demands for huge data rates in emerging Internet and multimedia services. Multiuser detection and space diversity techniques are the main principles, which enable efficient use of the available spectrum. The main limitation for the applicability of the techniques in these practical systems is the high complexity of the optimal receiver structures. The research emphasis in this thesis is on the design of a low complexity interference suppression/cancellation algorithm. The most important result of our research is the novel design of interference cancellation receivers which are adaptive and iterative and which are of low computational complexity. We propose various adaptive iterative receivers, based on a joint adaptive iterative detection and decoding algorithm. The proposed receiver can effectively suppress and cancel co-channel interference from the adjacent antennas in the MIMO system with a low computation complexity. The proposed adaptive detector, based on the adaptive least mean square (LMS) algorithm, is investigated and compared with the non-adaptive iterative receiver. Since the LMS algorithm has a slow convergence speed, a partially filtered gradient LMS (PFGLMS) algorithm, which has a faster convergence speed, is proposed to improve the convergence speed of the system. The performance and computational complexity of this receiver are also considered. To further reduce the computational complexity, we apply a frequency domain adaptation technique into the adaptive iterative receivers. The system performance and complexity are investigated. It shows that the computational complexity of the frequency domain based receiver is significantly lower than that of the time domain based receiver with the same system performance. We also consider applications of MIMO techniques in CDMA systems, called MIMO-CDMA. In the MIMO-CDMA, the presence of the co-channel interference (CCI) from the adjacent antennas and multiple access interference (MAI) from other users significantly degrades the system performance. We propose an adaptive iterative receiver, which provides the capability to effectively suppress the interference and cancel the CCI from the adjacent antennas and the MAI from other users so as to improve the system performance. The proposed receiver structure is also based on a joint adaptive detection and decoding scheme. The adaptive detection scheme employs an adaptive normalized LMS algorithm operating in the time and frequency domain. We have investigated and compared their system performance and complexity. Moreover, the system performance is evaluated by using a semi-analytical approach and compared with the simulation results. The results show that there is an excellent agreement between the two approaches.

Abstract Iterative receiver techniques, multiple-input – multiple-output (MIMO) processing, and orthogonal frequency division multiplexing (OFDM) are amongst the key physical layer technologies when aiming at higher spectral efficiency for a wireless communication system. Special focus is put on iterative detection, decoding, and channel estimation for a MIMO-OFDM system. After designing separately efficient algorithms for the detection, channel decoding, and channel estimation, the objective is to optimize them to work together through optimizing the activation schedules for soft-in soft-out (SfISfO) components. A list parallel interference cancellation (PIC) detector is derived to approximate an a posteriori probability (APP) algorithm with reduced complexity and minimal loss of performance. It is shown that the list PIC detector with good initialization outperforms the K-best list sphere detector (LSD) in the case of small list sizes, whereas the complexities of the algorithms are of the same order. The convergence of the iterative detection and decoding is improved by using a priori information to also recalculate the candidate list, aside from the log-likelihood ratios (LLRs) of the coded bits. Unlike in pilot based channel estimation, the least-squares (LS) channel estimator based on symbol decisions requires a matrix inversion in MIMO-OFDM. The frequency domain (FD) space-alternating generalized expectation-maximization (SAGE) channel estimator calculates the LS estimate iteratively, avoiding the matrix inversion with constant envelope modulation. The performance and computational complexity of the FD-SAGE channel estimator are compared to those of pilot based LS channel estimation with minimum mean square error (MMSE) post-processing exploiting the time correlation of the channel. A time domain (TD) SAGE channel estimator is derived to avoid the matrix inversion in channel estimation based on symbol decisions for MIMO-OFDM systems also with non-constant envelope modulation. An obvious problem, with more than two blocks in an iterative receiver, is to find the optimal activation schedule of the different blocks. It is proposed to use extrinsic information transfer (EXIT) charts to characterize the behavior of the receiver blocks and to find out the optimal activation schedule for them. A semi-analytical expression of the EXIT function is derived for the LS channel estimator. An algorithm is proposed to generate the EXIT function of the APP algorithm as a function of the channel estimate’s mutual information (MI). Surface fitting is used to get closed form expressions for the EXIT functions of the APP algorithm and the channel decoder. Trellis search algorithms are shown to find the convergence with the lowest possible complexity using the EXIT functions. With the proposed concept, the activation scheduling can be adapted to prevailing channel circumstances and unnecessary iterations will be avoided.

Monte Carlo algorithms can be used to estimate the state of a system given relative observations. In this dissertation, these algorithms are applied to physical layer communications system models to estimate channel state information, to obtain soft information about transmitted symbols or multiple access interference, or to obtain estimates of all of these by joint estimation. Initially, we develop and analyze a multiple access technique utilizing mutually orthogonal complementary sets (MOCS) of sequences. These codes deliberately introduce inter-chip interference, which is naturally eliminated during processing at the receiver. However, channel impairments can destroy their orthogonality properties and additional processing becomes necessary. We utilize Monte Carlo algorithms to perform joint channel and symbol estimation for systems utilizing MOCS sequences as spreading codes. We apply Rao-Blackwellization to reduce the required number of particles. However, dense signaling constellations, multiuser environments, and the interchannel interference introduced by the spreading codes all increase the dimensionality of the symbol state space significantly. A full maximum likelihood solution is computationally expensive and generally not practical. However, obtaining the optimum solution is critical, and looking at only a part of the symbol space is generally not a good solution. We have sought algorithms that would guarantee that the correct transmitted symbol is considered, while only sampling a portion of the full symbol space. The performance of the proposed method is comparable to the Maximum Likelihood (ML) algorithm. While the computational complexity of ML increases exponentially with the dimensionality of the problem, the complexity of our approach increases only quadratically. Markovian structures such as the one imposed by MOCS spreading sequences can be seen in other physical layer structures as well. We have applied this partitioning approach with some modification to blind equalization of frequency selective fading channel and to multiple-input multiple output receivers that track channel changes. Additionally, we develop a method that obtains a metric for quantifying the convergence rate of Monte Carlo algorithms. Our approach yields an eigenvalue based method that is useful in identifying sources of slow convergence and estimation inaccuracy.

With the recent advancements of wireless networks to satisfy new requirements, the investigation of novel transmission schemes to improve the link level performance is of major importance. A very common technique utilized in nowadays systems is the Orthogonal frequency division multiplexing (OFDM) waveform, which has been adopted by several standards, including WiFi, LTE, and more recently 5G, due to its simple equalization process. Despite its success, this dissertation shows that OFDM is a sub-optimal scheme under frequency-selective channel (FSC), when channel state information (CSI) is available at the receiver only. Based on the coded modulation capacity approach, this work demonstrates that the data symbols should experience the same channel gain in order to achieve the best performance, leading to the equal gain criterion (EGC). However, this comes at a cost in terms of losing orthogonality among data symbols. The result is valid for linear modulation matrices under the assumptions of CSI at only at the receiver with perfect feedback equalization. In order to attain the EGC for doubly-dispersive channels, the block multiplexing (BM) waveform is proposed in this thesis, where the data symbols are spread in frequency and time. For instance, the recently conceived orthogonal time frequency space (OTFS) is shown to be a particular case of BM with the classical single-carrier (SC). Regarding the equalization for the robust waveforms, it is shown that the minimum mean squared error with parallel interference cancellation (MMSE-PIC) employed together with convolutional encoder and soft decoder can completely remove the inter-symbol interference (ISI), where a low-complexity implementation is designed. In addition, a waveform with decreased complexity based on the sparse Walsh-Hadamard (SWH) is proposed for two reasons, i) sparse spreading requires a transform with lower size, ii) the Walsh-Hadamard transform is implemented with 1s and −1s, which requires less complexity than fast Fourier transform (FFT) based waveforms. Furthermore, the problem of estimating the time varying channel is considered, where a unique word (UW) or (pilot block) based approach is studied. In this regard, another main contribution of this dissertation is to develop an optimization framework, where the combination of channel estimation plus Doppler spread error is minimized. In particular, the composite error minimization is achieved by properly setting the FFT size of the system, for a fixed data length. Lastly, cyclic prefix (CP)-free system is considered such that the transmission time is decreased, and therefore provides a better channel estimation. Naturally, the CP-free system has undesirable interference, which is resolved by an iterative CP-Restoration algorithm. In this case, we extend the EGC to equal reliability criterion (ERC), i.e., the data symbols should be equally reliable and not only have equal gain. As a consequence, the BM with orthogonal chirp division multiplexing (OCDM) waveform has the best performance due to equal time and frequency spreading. In conclusion, the coded modulation capacity approach of this dissertation provides new insights and solutions to improve the performance of wireless systems.

In 2008, the European Digital Video Broadcasting (DVB) standardization committee issued the second generation of Digital Video Broadcasting-Terrestrial (DVB-T2) standard in order to enable the wide broadcasting of high definition and 3D TV programmes. DVB-T2 has adopted several new technologies to provide more robust reception compared to the first genaration standard. One important technology is the bit interleaved coded modulation (BICM) with doubled signal space diversity plus the usage of low-density parity check (LDPC) codes. Both techniques can be combined at the receiver side through an iterative process between the decoder and demapper in order to further increase the system performance. The object of my study was to design and prototype a DVB-T2 receiver which supports iterative process. The two main contributions to the demapper design are the proposal of a linear approximation of Euclidean distance computation and the derivation of a sub-region detection algorithm for the two-dimensional demapper. Both contributions allows the computational complexity of the demapper to be reduced for its hardware implementation. In order to enable iterative processing between the demapper and the decoder, we investigated the use of vertical shuffled Min-Sum LDPC decoding algorithm. A novel vertical shuffled iterative structure aiming at reducing the latency of iterative processing and the corresponding architecture of the decoder were proposed. The proposed demapper and decoder have been integrated in a real DVB-T2 demodulator and tested in order to validate the efficiency of the proposed architecture. The prototype of a simplified DVB-T2 transceiver has been implemented, in which the receiver supports both non-iterative process and iterative process. We published the first paper related to a DVB-T2 iterative receiver.

Les standards « Long-term evolution » (LTE) et LTE-Advanced (LTE-A) devraient influencer fortement l’avenir de la cinquième génération (5G) des réseaux mobiles. Ces normes exigent de hauts débits de données et une qualité de service de très bon niveau, ce qui permet d’assurer un faible taux d’erreur, avec une faible latence. Par ailleurs, la complexité doit être limitée. Dans le but de déterminer des solutions technologiques modernes qui satisfont ces contraintes fortes, nous étudions dans la thèse des systèmes de communication sans fil MIMO codés. D’abord, nous imposons un simple code convolutif récursif systématique (RSC) pour limiter la complexité et la latence. En considérant des récepteurs itératifs, nous optimisons alors la performance en termes de taux d’erreur de ces systèmes en définissant un précodage linéaire MIMO et des techniques de mapping appropriées. Dans la deuxième partie de la thèse, nous remplaçons le RSC par un LDPC non-binaire (NB-LDPC). Nous proposons d’utiliser les techniques de précodage MIMO afin de réduire la complexité des récepteurs des systèmes MIMO intégrant des codes NB-LDPC. Enfin, nous proposons également un nouvel algorithme de décodage itératif à faible complexité adapté aux codes NB-LDPC. / The long-term evolution (LTE) and the LTE-Advanced (LTE-A) standardizations are predicted to play essential roles in the future fifth-generation (5G) mobile networks. These standardizations require high data rate and high quality of service, which assures low error-rate and low latency. Besides, as discussed in the recent surveys, low complexity communication systems are also essential in the next 5G mobile networks. To adapt to the modern trend of technology, in this PhD thesis, we investigate the multiple-input multiple-output (MIMO) wireless communication schemes. In the first part of this thesis, low-complex forward error correction (FEC) codes are used for low complexity and latency. By considering iterative receivers at the receiver side, we exploit MIMO linear precoding and mapping methods to optimize the error-rate performance of these systems. In the second part of this thesis, non-binary low density parity check (NB-LDPC) codes are investigated. We propose to use MIMO precoders to reduce the complexity for NB-LDPC encoded MIMO systems. A novel low complexity decoding algorithm for NB-LDPC codes is also proposed at the end of this thesis.