Joint Detection and Decoding of High-Order Modulation Schemes for CDMA and OFDM Wireless Communications

Wireless communications call for high data rate, power and bandwidth efficient transmissions. High-order modulation schemes are suitable candidates for this purpose as the potential to reduce the symbol period is often limited by the multipath-induced intersymbol interference. In order to reduce the power consumption, and at the same time, to estimate time-variant wireless channels, we propose low-complexity, joint detection and decoding schemes for high-order modulation signals in this dissertation. We start with the iterative demodulation and decoding of high-order CPM signals for mobile communications. A low complexity, pilot symbol-assisted coherent modulation scheme is proposed that can significantly improve the bit error rate performance by efficiently exploiting the inherent memory structure of the CPM modulation. A noncoherent scheme based on multiple symbol differential detection is also proposed and the performances of the two schemes are simulated and compared. Second, two iterative demodulation and decoding schemes are proposed for quadrature amplitude modulated signals in flat fading channels. Both of them make use of the iterative channel estimation based on the data signal reconstructed from decoder output. The difference is that one of them has a threshold controller that only allows the data reconstructed with high reliability values to be used for iterative channel estimation, while the other one directly uses all reconstructed data. As the second scheme has much lower complexity with a performance similar to the best of the first one, we further apply it to the space-time coded CDMA Rake receiver in frequency-selective multipath channels. We will compare it to the pilot-aided demodulation scheme that uses a dedicated pilot signal for channel estimation. In the third part of the dissertation, we design anti-jamming multicarrier communication systems. Two types of jamming signals are considered - the partial-band tone jamming and the partial-time pulse jamming. We propose various iterative schemes to detect, estimate, and cancel the jamming signal in both AWGN and fading channels. Simulation results demonstrate that the proposed systems can provide reliable communications over a wide range of jamming-to-signal power ratios. Last, we study the problem of maximizing the throughput of a cellular multicarrier communication network with transmit or receive diversity. The total throughput of the network is maximized subject to power constraints on each mobile. We first extend the distributed water-pouring power control algorithm from single transmit and receive antenna to multiple transmit and receive antennas. Both equal power diversity and selective diversity are considered. We also propose a centralized power control algorithm based on the active set strategy and the gradient projection method. The performances of the two algorithms are assessed with simulation and compared with the equal power allocation algorithm

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

Hybrid solutions to instantaneous MIMO blind separation and decoding: narrowband, QAM and square cases

Future wireless communication systems are desired to support high data rates and high quality transmission when considering the growing multimedia applications. Increasing the channel throughput leads to the multiple input and multiple output and blind equalization techniques in recent years. Thereby blind MIMO equalization has attracted a great interest.Both system performance and computational complexities play important roles in real time communications. Reducing the computational load and providing accurate performances are the main challenges in present systems. In this thesis, a hybrid method which can provide an affordable complexity with good performance for Blind Equalization in large constellation MIMO systems is proposed first. Saving computational cost happens both in the signal sep- aration part and in signal detection part. First, based on Quadrature amplitude modulation signal characteristics, an efficient and simple nonlinear function for the Independent Compo- nent Analysis is introduced. Second, using the idea of the sphere decoding, we choose the soft information of channels in a sphere, and overcome the so- called curse of dimensionality of the Expectation Maximization (EM) algorithm and enhance the final results simultaneously. Mathematically, we demonstrate in the digital communication cases, the EM algorithm shows Newton -like convergence.Despite the widespread use of forward -error coding (FEC), most multiple input multiple output (MIMO) blind channel estimation techniques ignore its presence, and instead make the sim- plifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In final part of this work, we exploit the iterative channel estimation and decoding performance for blind MIMO equalization. Experiments show the improvements achievable by exploiting the existence of coding structures and that it can access the performance of a BCJR equalizer with perfect channel information in a reasonable SNR range. All results are confirmed experimentally for the example of blind equalization in block fading MIMO systems

Proceedings of the Mobile Satellite Conference

A satellite-based mobile communications system provides voice and data communications to mobile users over a vast geographic area. The technical and service characteristics of mobile satellite systems (MSSs) are presented and form an in-depth view of the current MSS status at the system and subsystem levels. Major emphasis is placed on developments, current and future, in the following critical MSS technology areas: vehicle antennas, networking, modulation and coding, speech compression, channel characterization, space segment technology and MSS experiments. Also, the mobile satellite communications needs of government agencies are addressed, as is the MSS potential to fulfill them

A General Framework for Analyzing, Characterizing, and Implementing Spectrally Modulated, Spectrally Encoded Signals

Fourth generation (4G) communications will support many capabilities while providing universal, high speed access. One potential enabler for these capabilities is software defined radio (SDR). When controlled by cognitive radio (CR) principles, the required waveform diversity is achieved via a synergistic union called CR-based SDR. Research is rapidly progressing in SDR hardware and software venues, but current CR-based SDR research lacks the theoretical foundation and analytic framework to permit efficient implementation. This limitation is addressed here by introducing a general framework for analyzing, characterizing, and implementing spectrally modulated, spectrally encoded (SMSE) signals within CR-based SDR architectures. Given orthogonal frequency division multiplexing (OFDM) is a 4G candidate signal, OFDM-based signals are collectively classified as SMSE since modulation and encoding are spectrally applied. The proposed framework provides analytic commonality and unification of SMSE signals. Applicability is first shown for candidate 4G signals, and resultant analytic expressions agree with published results. Implementability is then demonstrated in multiple coexistence scenarios via modeling and simulation to reinforce practical utility