Low Complexity Adaptive Iterative Receivers for Layered Space-Time Coded and CDMA Systems

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

Frequency domain system identification and it's application in jamming

Identification is a powerful technique used to build accurate models of system from noisy data. The Frequency Domain System Identification utilizes specialized tools for identifying linear dynamic multiple input/single-output (MISO) systems from time responses or measurements of the system's frequency response. Frequency domain methods supports continuous-time modeling, which can be a powerful and highly accurate complement to the more commonly used discrete-time methods. The methods described here can be applied to problems such as the modeling of electronic, mechanical, and acoustical systems. A brief intuitive introduction to system identification using adaptive filters has been provided. Adaptive filtering has been broadly divided into seven broad categories .The first part describes linear and non-linear filtering and gives an overview of various kinds of estimation techniques. The second part describes Weiner filter and its applications in real world. The third part introduces system modeling like stochastic and stationary models. In the fourth part we describe the least mean square algorithm and it’s error performance. The fifth part gives an overview of variants of LMS like sign LMS, block LMS, normalized LMS. The sixth part introduces transform domain adaptive filtering and algorithms used like DCT/DFT LMS. The last part is an implementation of system identification in design of a jam resistant receiver

Reduced-rank adaptive least bit-error-rate detection in hybrid direct-sequence time-hopping ultrawide bandwidth systems

Design of high-efficiency low-complexity detection schemes for ultrawide bandwidth (UWB) systems is highly challenging. This contribution proposes a reduced-rank adaptive multiuser detection (MUD) scheme operated in least bit-errorrate (LBER) principles for the hybrid direct-sequence timehopping UWB (DS-TH UWB) systems. The principal component analysis (PCA)-assisted rank-reduction technique is employed to obtain a detection subspace, where the reduced-rank adaptive LBER-MUD is carried out. The reduced-rank adaptive LBERMUD is free from channel estimation and does not require the knowledge about the number of resolvable multipaths as well as the knowledge about the multipaths’ strength. In this contribution, the BER performance of the hybrid DS-TH UWB systems using the proposed detection scheme is investigated, when assuming communications over UWB channels modeled by the Saleh-Valenzuela (S-V) channel model. Our studies and performance results show that, given a reasonable rank of the detection subspace, the reduced-rank adaptive LBER-MUD is capable of efficiently mitigating the multiuser interference (MUI) and inter-symbol interference (ISI), and achieving the diversity gain promised by the UWB systems

Iterative turbo beamforming for OFDM based hybrid terrestrial-satellite mobile system

In the context of orthogonal frequency division multiplexing (OFDM)-based systems, pilot-based beamforming (BF) exhibits a high degree of sensitivity to the pilot sub-carriers. Increasing the number of reference pilots significantly improves BF performance as well as system performance. However, this increase comes at the cost of data throughput, which inevitably shrinks due to transmission of additional pilots. Hence an approach where reference signals available to the BF process can be increased without transmitting additional pilots can exhibit superior system performance without compromising throughput. Thus, the authors present a novel three-stage iterative turbo beamforming (ITBF) algorithm for an OFDM-based hybrid terrestrial-satellite mobile system, which utilises both pilots and data to perform interference mitigation. Data sub-carriers are utilised as virtual reference signals in the BF process. Results show that when compared to non-iterative conventional BF, the proposed ITBF exhibits bit error rate gain of up to 2.5 dB with only one iteration