Design and Implementation of Belief Propagation Symbol Detectors for Wireless Intersymbol Interference Channels

In modern wireless communication systems, intersymbol interference (ISI) introduced by frequency selective fading is one of the major impairments to reliable data communication. In ISI channels, the receiver observes the superposition of multiple delayed reflections of the transmitted signal, which will result errors in the decision device. As the data rate increases, the effect of ISI becomes severe. To combat ISI, equalization is usually required for symbol detectors. The optimal maximum-likelihood sequence estimation (MLSE) based on the Viterbi algorithm (VA) may be used to estimate the transmitted sequence in the presence of the ISI. However, the computational complexity of the MLSE increases exponentially with the length of the channel impulse response (CIR). Even in channels which do not exhibit significant time dispersion, the length of the CIR will effectively increase as the sampling rate goes higher. Thus the optimal MLSE is impractical to implement in the majority of practical wireless applications. This dissertation is devoted to exploring practically implementable symbol detectors with near-optimal performance in wireless ISI channels. Particularly, we focus on the design and implementation of an iterative detector based on the belief propagation (BP) algorithm. The advantage of the BP detector is that its complexity is solely dependent on the number of nonzero coefficients in the CIR, instead of the length of the CIR. We also extend the work of BP detector design for various wireless applications. Firstly, we present a partial response BP (PRBP) symbol detector with near-optimal performance for channels which have long spanning durations but sparse multipath structure. We implement the architecture by cascading an adaptive linear equalizer (LE) with a BP detector. The channel is first partially equalized by the LE to a target impulse response (TIR) with only a few nonzero coefficients remaining. The residual ISI is then canceled by a more sophisticated BP detector. With the cascaded LE-BP structure, the symbol detector is capable to achieve a near-optimal error rate performance with acceptable implementation complexity. Moreover, we present a pipeline high-throughput implementation of the detector for channel length 30 with quadrature phase-shift keying (QPSK) modulation. The detector can achieve a maximum throughput of 206 Mb/s with an estimated core area of 3.162 mm^{2} using 90-nm technology node. At a target frequency of 515 MHz, the dynamic power is about 1.096 W. Secondly, we investigate the performance of aforementioned PRBP detector under a more generic 3G channel rather than the sparse channel. Another suboptimal partial response maximum-likelihood (PRML) detector is considered for comparison. Similar to the PRBP detector, the PRML detector also employs a hybrid two-stage scheme, in order to allow a tradeoff between performance and complexity. In simulations, we consider a slow fading environment and use the ITU-R 3G channel models. From the numerical results, it is shown that in frequency-selective fading wireless channels, the PRBP detector provides superior performance over both the traditional minimum mean squared error linear equalizer (MMSE-LE) and the PRML detector. Due to the effect of colored noise, the PRML detector in fading wireless channels is not as effective as it is in magnetic recording applications. Thirdly, we extend our work to accommodate the application of Advanced Television Systems Committee (ATSC) digital television (DTV) systems. In order to reduce error propagation caused by the traditional decision feedback equalizer (DFE) in DTV receiver, we present an adaptive decision feedback sparsening filter BP (DFSF-BP) detector, which is another form of PRBP detector. Different from the aforementioned LE-BP structure, in the DFSF-BP scheme, the BP detector is followed by a nonlinear filter called DFSF as the partial response equalizer. In the first stage, the DFSF employs a modified feedback filter which leaves the strongest post-cursor ISI taps uncorrected. As a result, a long ISI channel is equalized to a sparse channel having only a small number of nonzero taps. In the second stage, the BP detector is applied to mitigate the residual ISI. Since the channel is typically time-varying and suffers from Doppler fading, the DFSF is adapted using the least mean square (LMS) algorithm, such that the amplitude and the locations of the nonzero taps of the equalized sparse channel appear to be fixed. As such, the channel appears to be static during the second stage of equalization which consists of the BP detector. Simulation results demonstrate that the proposed scheme outperforms the traditional DFE in symbol error rate, under both static channels and dynamic ATSC channels. Finally, we study the symbol detector design for cooperative communications, which have attracted a lot of attention recently for its ability to exploit increased spatial diversity available at distributed antennas on other nodes. A system framework employing non-orthogonal amplify-and-forward half-duplex relays through ISI channels is developed. Based on the system model, we first design and implement an optimal maximum-likelihood detector based on the Viterbi algorithm. As the relay period increases, the effective CIR between the source and the destination becomes long and sparse, which makes the optimal detector impractical to implement. In order to achieve a balance between the computational complexity and performance, several sub-optimal detectors are proposed. We first present a multitrellis Viterbi algorithm (MVA) based detector which decomposes the original trellis into multiple parallel irregular sub-trellises by investigating the dependencies between the received symbols. Although MVA provides near-optimal performance, it is not straightforward to decompose the trellis for arbitrary ISI channels. Next, the decision feedback sequence estimation (DFSE) based detector and BP-based detector are proposed for cooperative ISI channels. Traditionally these two detectors are used with fixed, static channels. In our model, however, the effective channel is periodically time-varying, even when the component channels themselves are static. Consequently, we modify these two detector to account for cooperative ISI channels. Through simulations in frequency selective fading channels, we demonstrate the uncoded performance of the DFSE detector and the BP detector when compared to the optimal MLSE detector. In addition to quantifying the performance of these detectors, we also include an analysis of the implementation complexity as well as a discussion on complexity/performance tradeoffs

Electronic processing for optical communication systems

I sistemi di comunicazione in fibra ottica risentono di diversi tipi di disturbi, quali ad esempio la dispersione cromatica e la dispersione dei modi di polarizzazione. La compensazione ottica di tali disturbi è possibile ma complessa e costosa, mentre le tecniche di elaborazione elettronica del segnale presentano diversi vantaggi, semplicità, costo, adattabilità. L'equalizzazione elettronica e la strategia di rivelazione di sequenza a massima verosimiglianza rappresentano soluzioni efficaci e realizzabili con semplici modulazioni di ampiezza e anche con più avanzate modulazioni di fase e fase-ampiezza.Optical communication systems are suffering from several typical impairments, chromatic dispersion and polarization mode dispersion. Optical compensation of such impairments is possible but it is technological demanding and expensive, whereas electronic signal processing presents many advantages, implementation ease, cost-efficiency, adaptability. Electronic equalization and maximum likelihood sequence detection represent effective and feasible solutions for simple amplitude modulation formats as well as for more advanced phase and phase-amplitude modulation formats

Adaptive RAKE receiver structures for ultra wide-band systems

Ultra wide band (UWB) is an emerging technology that recently has gained regulatory approval. It is a suitable solution for high speed indoor wireless communications due to its promising ability to provide high data rate at low cost and low power consumption. Another benefit of UWB is its ability to resolve individual multi-path components. This feature motivates the use of RAKE multi-path combining techniques to provide diversity and to capture as much energy as possible from the received signal. Potential future and rule limitation of UWB, lead to two important characteristics of the technology: high bit rate and low emitting power. Based on the power emission limit of UWB, the only choice for implementation is the low level modulation technology. To obtain such a high bit rate using low level modulation techniques, significant inter-symbol interference (ISI) is unavoidable. Three N (N means the numbers of fingers) fingers RAKE receiver structures are proposed: the N-selective maximal ratio combiner (MRC), the N-selective MRC receiver with least-mean-square (LMS) adaptive equalizer and the N-selective MRC receiver with LMS adaptive combiner. These three receiver structures were all simulated for N=8, 16 and 32. Simulation results indicate that ISI is effectively suppressed. The 16-selective MRC RAKE receiver with LMS adaptive combiner demonstrates a good balance between performance, computation complexity and required length of the training sequence. Due to the simplicity of the algorithm and a reasonable sampling rate, this structure is feasible for practical VLSI implementations

Available Techniques for Magnetic Hard Disk Drive Read Channel Equalization

This paper presents an extensive, non-exhaustive, study of available hard disk drive read channel equalization techniques used in the storage and readback of magnetically stored information. The physical elements and basic principles of the storage processes are introduced together with the basic theoretical definitions and models. Both read and write processes in magnetic storage are explained along with the definition of simple key concepts such as user bit density, intersymbol interference, linear and areal density, read head pulse response models, and coding algorithm