This dissertation develops an unclocked receiver analog decision-feedback equalizer (ADFE) circuit architecture and topology and implements the circuit in 0.18-um CMOS to enable 10-Gb/sec serial baseband data transmission over FR-4 backplane and optical fibre. The ADFE overcomes the first feedback-loop latency challenge of traditional digital and mixed-signal DFEs by separating data re-timing from equalization and also eliminates the need for clock-recovery prior to decision-feedback equalization. The ADFE enables 10-Gb/sec decision-feedback equalization using a 0.18-um CMOS process, the first to do so to the author s knowledge. A tuneable current-mode-logic (CML) feedback-loop is designed to enable first post-cursor cancellation for a range of data-rates and to have external control over loop latency over variations in process, voltage and temperature. CML design techniques are used to minimize current consumption and achieve the required voltage swing for decision-feedback to take place. The all-analog equalizer consumes less power and area than comparable state-of-the art DFEs. The ADFE is used to compensate inter-symbol interference (ISI) for 20 inches of FR-4 backplane and 300 m of multi-mode fibre at 10-Gb/sec. The ADFE also extends the reach of single-mode fibre at 10-Gb/sec to 120 km. The work described in this dissertation advances the state-of-the-art in equalization solutions for multi-Gb/sec serial data transmission and can find applications in several of the 10-Gb/sec Ethernet standards that have been approved recently. The contributions of this work toward future research are also discussed.

All digital communication channels are subject to inter-symbol interference (ISI). To achieve the desired system performance, at receiver end, the effect of ISI must be compensated and the task of the equalizer is to combat the degrading effects of ISI on the transmission. Due to the demand of high data transmission rate, the multicarrier modulation (MCM) technique implemented with the orthogonal frequency division multiplexing (OFDM) has been adopted in many modern communications systems for block transmission. In block transmission systems, transmitter-included redundancy using finite-impulse response (FIR) filterbanks can be utilized to suppress inter-block-interference (IBI). However, the length of redundancy will affect the system performance, which is highly dependent on the length of channel impulse response. To deal with the effect of ISI, many equalizing schemes have been proposed, among them the FIR zero-forcing (ZF) equalizer with the non-orthogonal projector provides a useful transceiver design structure for suppressing the IBI and ISI, simultaneously. In this thesis, we propose a new equalizing scheme; it combines the FIR-ZF equalizer with non-orthogonal projector as well as the Bayesian decision feedback equalizer (DFE) for IBI and ISI suppression. The Bayesian DFE is known to be one of the best schemes to achieve the desired performance for eliminating ISI. It can be employed to achieve the full potential of symbol-by-symbol equalizer. That is, after removing the effect of IBI with the non-orthogonal projector, the Bayesian DFE is employed for eliminating the ISI, simultaneously. For comparison, the system performance, in term of bit error rate (BER) is investigated, and compared with the minimum mean square error (MMSE)-IBI-DFE. The advantage of the new proposed equalizing scheme is verified via computer simulation under condition of insufficient redundancy.

Κανάλια με αραιή κρουστική απόκριση εμφανίζονται πάρα πολύ συχνά σε εφαρμογές ασύρματων κυρίως τηλεπικοινωνιακών συστημάτων. Παραδείγματα τέτοιων εφαρμογών είναι η εκπομπή HDTV (HighDefinitionΤelevision) ή εκπομπή μέσω υποθαλλάσιων ακουστικών καναλιών. Σε όλες αυτές τις εφαρμογές η μορφή του καναλιού διαμορφώνεται από το φαινόμενο της πολυδιόδευσης. Συνεπώς ο δέκτης λαμβάνει έναν περιορισμένο αριθμό από διαφορετικές εκδοχές του εκπεμπόμενου σήματος καθεμία με διαφορετική εξασθένιση και καθυστέρηση. Ως εκ τούτου η συνάρτηση της κρουστικής απόκρισης ενός τέτοιου καναλιού αποτελείται από ελάχιστα μη μηδενικά στοιχεία σε συγκριση με το μήκος της, καθένα από τα οποία αντιστοιχεί σε ένα από τα μονοπάτια πολυδιόδευσης. Για την ισοστάθμιση αυτών των καναλιών έχουν προταθεί διάφορες τεχνικές, πολλές από τις οποίες εκμεταλλεύονται την ιδιαίτερη αυτή μορφή της κρουστικής απόκρισης. Πολλοί από τους προτεινόμενους ισοσταθμιστές καναλιών απαιτούν την παρεμβολή ακολουθίων εκμάθησης ανάμεσα στην ακολουθία δεδομένων, οι οποίες είναι εκ των προτέρων γνωστές στον δέκτη. Χρησιμοποιούνται δε προκειμένου ο αλγόριθμος εκτίμησης του καναλιού να συγκλίνει όσο το δυνατόν ταχύτερα στην επιθυμητή τιμή. Μειονέκτημα αυτών των μεθόδων είναι η επιβάρυνση του ωφέλιμου εύρους ζώνης που συνεπάγεται. Ωστόσο η εκ των προτέρων γνώση της αραιής μορφής της κρουστικής απόκρισης εχει δώσει αφορμή για την σχεδίαση ισοσταθμιστών με περιορισμένο μήκος αλλά εξίσου καλή απόδοση. Οι συμβατικές τεχνικές εκτίμησης καναλιών, όπως η Least Square μέθοδος, δεν εκμεταλλεύονται αυτή την γνώση. Οι πρόσφατες δε εξελίξεις στην ανακατασκευή αραιών σημάτων μέσω τεχνικών συμπιεσμένης καταγραφής (compressed sensing) έχουν οδηγήσει στην μελέτη της εφαρμογής τέτοιων τεχνικών στο πρόβλημα της εκτίμησης καναλιού. Η μέθοδος της συμπιεσμένης καταγραφής στηρίζεται στη δυνατότητα ανακατασκευής αραιών σημάτων από πλήθος δειγμάτων αισθητά κατώτερο από αυτό που προβλέπει το θεωρητικό όριο του Nyquist. Έχει αποδειχθεί ότι η ανακατασκευή αυτή είναι δυνατή όταν το σήμα ή έστω κάποιος μετασχηματισμός του περιέχει λίγα μη μηδενικά στοιχεία σε σχέση με το μήκος του. Οι εφαρμογές αυτών των τεχνικών εκτείνονται και σε άλλα πεδία όπως η επεξεργασία εικόνας, η μαγνητική τομογραφία, η ανάλυση γεωφυσικών δεδομένων, η επεξεργασία εικόνας radar, η αστρονομία κ.α. Στα πλαίσια αυτής της εργασίας παρουσιάζονταιοι βασικές αρχές που διέπουν την ανακατασκευή αραιών σημάτων μέσω της επίλυσης υποορισμένων συστημάτων γραμμικών εξισώσεων. Παράλληλα παρουσιάζονται οι κυριότεροι αλγόριθμοι που έχουν προταθεί για την υλοποίηση της και εξετάζονται ως προς την απόδοση και την υπολογιστική πολυπλοκότητα τους. Εν συνεχεία εξετάζεται η εφαρμογή αυτών των αλγορίθμων στο πρόβλημα της εκτίμησης αραιών καναλιών. Προτείνονται δε ισοσταθμιστές αραιών καναλιών βασισμένοι σε εκτιμητές απόκρισης που χρησιμοποιούν τεχνικές συμπιεσμένης καταγραφής. / Channels with sparse impulse response are very common in wireless telecommunications systems applications. Example of such channel is HDTV channel where multipath distribution of the transmitted signal results in a sparse form of the channel impulse response. Several different versions of the same signal are received, each one with its own gain and delay. As a result, channel impulse response has a few non zero taps compared to its length, its one corresponding to a different distribution path. Several techniques for estimating and equalizing such channels have been proposed, most of them taking advantage of this sparse form of the impulse response. The transmission of a training sequence known to the receiver is required for this purpose. It is used so that the channel estimation algorithm at the receiver converges faster. The disadvantage of the use of a training sequence is the fact that the useful bandwidth is reduced. However the a priori knowledge of the sparse form of the training sequence has led to the design of equalizers that require short training sequences but have satisfactory performance. Channel estimation techniques based on least square method do not take advantage of this idea. On the other hand recent progress on sparse signal reconstruction using compressed sensing techniques has led scientists to research the potential use of such algorithms in channel estimation. Compressed sensing is based on the idea of reconstructing a sparse signal using less samples that those predicted by Nyquist theorem. It has been proved that such a reconstruction is feasible if the reconstructed signal is sparse enough. In this dissertation several sparse signal reconstruction algorithms are presented and their performance and complexity are evaluated. Then the application of these algorithms on channel estimation equalization problem is analyzed.

In this dissertation the aim was to investigate the usage of algorithms found in computer science and apply suitable algorithms to the problem of decoding multiple-input multipleoutput (MIMO) space-time-frequency block coded signals. It was found that the sphere decoder is a specific implementation of the A* tree search algorithm that is well known in computer science. Based on this knowledge, the sphere decoder was extended to include a priori information in the maximum a posteriori probability (MAP) joint decoding of the STFC block coded MIMO signals. The added complexity the addition of a priori information has on the sphere decoder was investigated and compared to the sphere decoder without a priori information. To mitigate the potential additional complexity several algorithms that determine the order in which the symbols are decoded were investigated. Three new algorithms incorporating a priori information were developed and compared with two existing algorithms. The existing algorithms compared against are sorting based on the norms of the channel matrix columns and the sorted QR decomposition. Additionally, the zero forcing (ZF) and minimum mean squared error (MMSE) decoderswith and without decision feedback (DF) were also extended to include a priori information. The developed method of incorporating a priori information was compared to an existing algorithm based on receive vector translation (RVT). The limitation of RVT to quadrature phase shift keying (QPSK) and binary shift keying (BPSK) constellations was also shown in its derivation. The impact of the various symbol sorting algorithms initially developed for the sphere decoder on these decoders was also investigated. The developed a priori decoders operate in the log domain and as such accept a priori information in log-likelihood ratios (LLRs). In order to output LLRs to the forward error correcting (FEC) code, use of the max-log approximation, occasionally referred to as hard-to-soft decoding, was made. In order to test the developed decoders, an iterative turbo decoder structure was used together with an LDPC decoder to decode threaded algebraic space-time (TAST) codes in a Rayleigh faded MIMO channel. Two variables that have the greatest impact on the performance of the turbo decoder were identified: the hard limit value of the LLRs to the LDPC decoder and the number of independently faded bits in the LDPC code. / Dissertation (MEng)--University of Pretoria, 2013. / gm2014 / Electrical, Electronic and Computer Engineering / unrestricted

Massive MU-MIMO (Multiuser-Multiple Input and Multple Output) is a promising technology for 5G wireless communications because of its spectrum and energy efficiency. To combat the distortion from multipath fading channel, the acquisition of channel state information is essential, which generally requires the training signal that lowers the data rate. In addition, coarse quantization can reduce the high computational energy and cost, yet results in the loss of information. In this thesis, an iterative decision feedback receiver, including iterative Channel Estimation (CE) and equalization, is constructed for a Massive MU-MIMO uplink system. The impact of multipath distortion and coarse quantization can be gradually reduced due to the iterative structure that exploits extrinsic feedback to improve the CE and data detection, so that the data rate is improved by reducing training signals for CE and by using low precision quantization. To observe and evaluate the convergence behaviour, an Extrinsic Information Transfer (EXIT) chart method is utilized to visualize the performance of the iterative receiver. / Graduate

No description available.

<p> We consider the design of the precoders for a multi-input multi-output (MIMO) communication system equipped with a decision feedback equalizer (DFE) receiver. For such design problems, perfect knowledge of the channel state information (CSI) at both the transmitter and the receiver is usually required. However, in the environment of wireless communications, it is often difficult to provide sufficiently timely and accurate feedback of CSI from the receiver to the transmitter for such designs to be practically viable.</p> <p> In this thesis, we consider the optimum precoder designs for a wireless communication link having M transmitter antennas and N receiver antennas (M < N), in which the channels are assumed to be flat fading and may be correlated. We assume that full knowledge of CSI is available at the receiver. At the transmitter, however, only the first- and second-order statistics of the channels are available. Our first goal is to come up with an efficient design of the optimal precoder for such a MIMO system by minimizing the average arithmetic mean-squared error (MSE) of zero-forcing (ZF) decision feedback detection subject to a constraint on the total transmission power. Applying some of the properties of the matrix parameters, this non-convex optimization problem can be transformed into a convex geometrical programming problem which can then be efficiently solved using an interior point method. The performance of the MIMO system equipped with this optimum precoder and a ZF-DFE has also been found to be comparable, and in some cases, superior to that of V-BLAST which necessitates optimally ordered successive interference cancellation based on the largest post-detection signal-to-noise ratio (SNR). In terms of trade-off between performance and implementation simplicity, the proposed system is certainly an attractive alternative.</p> <p> In addition, we also utilize these important properties of our system parameters to investigate an "inverse problem" of our first design. That is, we design another precoding matrix by minimizing the total transmission power of the MIMO communication system subject to a constraint on the average MSE. Also, a closed-form solution is derived when the channels are uncorrelated while simulation results for the minimum power precoder designs is given at the end of this thesis.</p> / Thesis / Master of Applied Science (MASc)

The Decision Feedback Equalizer (DFE) is a known method of channel equalization which has performance superiority over linear equalizer. The best performance of DFE is obtained, commonly, with training period which is used for initial acquisiton of channel or recovering changes in the channel. The training period requires a training sequence which reduces the bit transmission rate or is not possible to send in most of the situations. So, it is desirable to skip the training period. The Unsupervised (Blind) DFE (UDFE) is such a DFE scheme which has no training period. The UDFE has two modes of operation. In one mode, the UDFE uses Constant Modulus Algorithm (CMA) to perform channel acquisition, blindly. The other mode is the same as classical decision-directed DFE. This thesis compares the performances of the classical trained DFE method and the UDFE. The performance comparison is done in some channel environments with the problem of timing error present in the received data bearing signal. The computer aided simulations are done for two stationary channels, a time-varying channel and a frequency selective Rayleigh fading channel to test the performance of the relevant equalizers. The test results are evaluted according to mean square error (MSE), bit-error rate (BER), residual intersymbol interference (RISI) performances and equalizer output diagrams. The test results show that the UDFE has an equal or, sometimes, better performance compared to the trained DFE methods. The two modes of UDFE enable it to solve the absence of training sequence.

In this thesis the telecommunication problem known as inter-cell interference is examined. Inter-cell interference originates from users in neighboring cells and affects the users in the own cell. The reason that inter-cell interference is interesting to study is that it affects the maximum data-rates achievable in the 3G network. By knowing the inter-cell interference, higher data-rates can be scheduled without risking cell-instability. An expression for the coupling between cells is derived using basic physical principles. Using the expression for the coupling factors a nonlinear model describing the inter-cell interference is developed from the model of the power control loop commonly used in the base stations. The expression describing the coupling factors depends on the positions of users which are unknown. A quasi decentralized method for estimating the coupling factors using measurements of the total interference power is presented. The estimation results presented in this thesis could probably be improved by using a more advanced nonlinear filter, such as a particle filter or an Extended Kalman filter, for the estimation. Different expressions describing the coupling factors could also be considered to improve the result.

Orthogonal frequency division multiplexing (OFDM) modulator with redundancy has been adopted in many wireless communication systems for higher data rate transmissions. The introduced redundancy at the transmitter allows us to overcome serious inter-block interference (IBI) problems due to highly dispersive channel. However, the selection of redundancy length will affect the system performance and spectral efficiency, and is highly dependent on the length of channel impulse response. In this thesis, based on the pseudorandom postfix (PRP) OFDM scheme we propose a novel block-based OFDM transceiver framework. Since in the PRP-OFDM system the PRP can be employed for semi-blind channel estimation with order-one statistics of the received signal. Hence, for sufficient redundancy case the PRP-OFDM system with the Bayesian decision feedback equalizer (DFE) is adopted for suppressing the IBI and ISI simultaneously. However, for the insufficient redundancy case (the length of redundancy is less than the order of channel), we first propose a modified scheme for channel estimation. To further reduce the complexity of receiver, the maximum shortening signal-to-noise-ratio time domain equalizer (MSSNR TEQ) with the Bayesian DFE is developed for suppressing the IBI and ISI, separately. That is, after knowing the channel state information (CSI) and removing the effect of IBI with MSSNR TEQ, the Bayesian DFE is applied for eliminating the ISI. Via computer simulation, we verify that performance improvement, in terms of bit error rate (BER), compared with the conventional block-based minimum mean square error (MMSE)-DFE can be achieved.