Multiple-input multiple-output wireless communications with imperfect channel knowledge

In the first work a recurrent neural network (RNN) is employed for MIMO channel prediction. A novel PSO-EA-DEPSO off-line training algorithm is presented and is shown to outperform PSO, PSO-EA, and DEPSO. This predictor is shown to be robust to varying channel scenarios. New expressions for the received SNR, array gain, average probability of error, and diversity gain are derived. Next, a new expression for the outage capacity of a MIMO system with no CSI at the transmitter and an estimate at the receiver is presented. Since the outage capacity is a function of the first and second moments of the mutual information, new closed form approximations are derived at low and high effective SNR. Also at low effective SNR a new result for the outage capacity is presented. Finally, the outage capacity for a frequency selective channel is derived. This is followed by a MIMO RNN predictor that operates online. A single RNN is constructed to predict all of the MIMO sub-channels instantaneously. The extended Kalman filter (EKF) and real-time recurrent learning (RTRL) algorithms are applied to compare the MSE of the prediction error. A new expression for the channel estimation error of a continuously varying MIMO channel is derived next. The optimal amount of time to send training pilots is investigated for different channel scenarios. Special cases of the new expression for the channel estimation error lead to previously established results. The last work investigates the performance of a MIMO aeronautical system in a two- ray ground reflection scenario. The ergodic capacity is analyzed when the altitude, horizontal displacement, antenna separation, and aircraft velocity are varied --Abstract, page iv

Adaptive multiple symbol decision feedback for non-coherent detection.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2006.Non-coherent detection is a simple form of signal detection and demodulation for digital communications. The main drawback of this detection method is the performance penalty incurred, since the channel state information is not known at the receiver. Multiple symbol detection (MSD) is a technique employed to close the gap between coherent and non-coherent detection schemes. Differentially encoded JW-ary phase shift keying (DM-PSK) is the classic modulation technique that is favourable for non-coherent detection. The main drawback for standard differential detection (SDD) has been the error floor incurred for frequency flat fading channels. Recently a decision feedback differential detection (DFDD) scheme, which uses the concept of MSD was proposed and offered significant performance gain over the SDD in the mobile flat fading channel, almost eliminating the error floor. This dissertation investigates multiple symbol decision feedback detection schemes, and proposes alternate adaptive strategies for non-coherent detection. An adaptive algorithm utilizing the numerically stable QR decomposition that does not require training symbols is proposed, named QR-DFDD. The QR-DFDD is modified to use a simpler QR decomposition method which incorporates sliding windows: QRSW-DFDD. This structure offers good tracking performance in flat fading conditions, while achieving near optimal DFDD performance. A bit interleaved coded decision feedback differential demodulation (DFDM) scheme, which takes advantage of the decision feedback concept and iterative decoding, was introduced by Lampe in 2001. This low complexity iterative demodulator relied on accurate channel statistics for optimal performance. In this dissertation an alternate adaptive DFDM is introduced using the recursive least squares (RLS) algorithm. The alternate iterative decoding procedure makes use of the convergence properties of the RLS algorithm that is more stable and achieves superior performance compared to the DFDM

Radio Channel Prediction Based on Parametric Modeling

Long range channel prediction is a crucial technology for future wireless communications. The prediction of Rayleigh fading channels is studied in the frame of parametric modeling in this thesis. Suggested by the Jakes model for Rayleigh fading channels, deterministic sinusoidal models were adopted for long range channel prediction in early works. In this thesis, a number of new channel predictors based on stochastic sinusoidal modeling are proposed. They are termed conditional and unconditional LMMSE predictors respectively. Given frequency estimates, the amplitudes of the sinusoids are modeled as Gaussian random variables in the conditional LMMSE predictors, and both the amplitudes and frequency estimates are modeled as Gaussian random variables in the unconditional LMMSE predictors. It was observed that a part of the channels cannot be described by the periodic sinusoidal bases, both in simulations and measured channels. To pick up this un-modeled residual signal, an adjusted conditional LMMSE predictor and a Joint LS predictor are proposed. Motivated by the analysis of measured channels and recently published physics based scattering SISO and MIMO channel models, a new approach for channel prediction based on non-stationary Multi-Component Polynomial Phase Signal (MC-PPS) is further proposed. The so-called LS MC-PPS predictor models the amplitudes of the PPS components as constants. In the case of MC-PPS with time-varying amplitudes, an adaptive channel predictor using the Kalman filter is suggested, where the time-varying amplitudes are modeled as auto-regressive processes. An iterative detection and estimation method of the number of PPS components and the orders of polynomial phases is also proposed. The parameter estimation is based on the Nonlinear LS (NLLS) and the Nonlinear Instantaneous LS (NILS) criteria, corresponding to the cases of constant and time-varying amplitudes, respectively. The performance of the proposed channel predictors is evaluated using both synthetic signals and measured channels. High order polynomial phase parameters are observed in both urban and suburban environments. It is observed that the channel predictors based on the non-stationary MC-PPS models outperform the other predictors in Monte Carlo simulations and examples of measured urban and suburban channels

Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers for WIFI, WIMAX, and Next-Generation Cellular Systems

Burts-by-burst (BbB) adaptive high-speed downlink packet access (HSDPA) style multicarrier systems are reviewed, identifying their most critical design aspects. These systems exhibit numerous attractive features, rendering them eminently eligible for employment in next-generation wireless systems. It is argued that BbB-adaptive or symbol-by-symbol adaptive orthogonal frequency division multiplex (OFDM) modems counteract the near instantaneous channel quality variations and hence attain an increased throughput or robustness in comparison to their fixed-mode counterparts. Although they act quite differently, various diversity techniques, such as Rake receivers and space-time block coding (STBC) are also capable of mitigating the channel quality variations in their effort to reduce the bit error ratio (BER), provided that the individual antenna elements experience independent fading. By contrast, in the presence of correlated fading imposed by shadowing or time-variant multiuser interference, the benefits of space-time coding erode and it is unrealistic to expect that a fixed-mode space-time coded system remains capable of maintaining a near-constant BER

MIMO Systems

In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Frequency estimation for single-carrier and OFDM signals in communication and radar systems

Eine der klassischen Problemstellungen in der Signalverarbeitung ist die Schaetzung der Frequenz eines Signals, das von weissem Rauschen additiv ueberlagert ist. Diese bedeutende Aufgabe stellt sich in vielen verschiedenen Anwendungsbereichen wie der Kommunikationstechnik, beim Doppler-Radar, beim Radar mit synthetischer Apertur (SAR), beim Array Processing, bei Radio-Frequency-IDentification (RFID), bei Resonanz-Sensoren usw. Die Anforderungen bezueglich der Leistungsfaehigkeit des Frequenzschaetzers haengen von der Anwendung ab. Die Leistungsfaehigkeit ist dabei oft unter Beruecksichtigung der folgenden 4 Punkte definiert: i) Genauigkeit, Richtigkeit der Schaetzung, ii) Arbeitsbereich (estimation range), iii) Grenzwerte der Schaetzung (im Vergleich zu einer theoretisch moeglichen Schwelle) und iv) Komplexitaet der Implementierung. Diese Anforderungen koennen nicht unabhaengig voneinander betrachtet werden und stehen sich teilweise gegenueber. Beispielsweise erfordert die Erzielung von Ergebnissen nahe an der theoretisch moeglichen Schwelle eine hohe Komplexitaet. Ebenso kann ein Schaetz-ergebnis von hoher Genauigkeit oftmals nur fuer einen stark eingeschraenkten Arbeitsbereich erzielt werden. Die Frequenzschaetzung ist im Falle von durch Fading hervorgerufenem multiplikativem Rauschen noch herausfordernder. Es handelt sich dann um den allgemeinen Fall der Frequenzschaetzung. Bisher hat man bereits viel Arbeit in die Ableitung eines Schaetzers für diesen allgemeinen Fall investiert. Ein Schaetzer, der optimal bezueglich aller oben genannten Kriterien ist, duerfte allerdings nur schwer zu finden sein. In dieser Dissertation wird mit Blick auf Kommunikationstechnik und Radaranwendungen ein verallgemeinerter, in geschlossener Form vorliegender, Frequenzschaetzer eingefuehrt, der alle genannten Kriterien der Leistungs-faehigkeit beruecksichtigt. Die Herleitung des Schaetzers beruht auf dem Prinzip der kleinsten Fehlerquadrate fuer den nichtlinearen Fall in Verbindung mit der Abelschen partiellen Summation. Zudem werden verschiedene modifizierte Frequenzschaetzer vorgestellt, die sich fuer Faelle in denen kein Fading oder nur sehr geringes Fading auftritt, eignen.Estimating the frequency of a signal embedded in additive white Gaussian noise is one of the classical problems in signal processing. It is of fundamental importance in various applications such as in communications, Doppler radar, synthetic aperture radar (SAR), array processing, radio frequency identification (RFID), resonance sensor, etc. The requirement on the performance of the frequency estimator varies with the application. The performance is often defined using four indexes: i). estimation accuracy, ii). estimation range, iii). estimation threshold, and iv). implementation complexity. These indexes may be in contrast with each other. For example, achieving a low threshold usually implies a high complexity. Likewise, good estimation accuracy is often obtained at the price of a narrow estimation range. The estimation becomes even more difficult in the presence of fading-induced multiplicative noise which is considered to be the general case of the frequency estimation problem. There have been a lot of efforts in deriving the estimator for the general case, however, a generalized estimator that fulfills all indexes can be hardly obtained. Focusing on communications and radar applications, this thesis proposes a new generalized closed-form frequency estimator that compromises all performance indexes. The derivation of the proposed estimator relies on the nonlinear least-squares principle in conjunction with the well known summation-by-parts formula. In addition to this, several modified frequency estimators suitable for non-fading or very slow fading scenarios, are also introduced in this thesis