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

Air Force Institute of Technology Research Report 2012

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Oscillatory mechanisms for controlling information flow in neural circuits

Mammalian brains generate complex, dynamic structures of oscillatory activity, in which distributed regions transiently engage in coherent oscillation, often at specific stages in behavioural or cognitive tasks. Much is now known about the dynamics underlying local circuit synchronisation and the phenomenology of where and when such activity occurs. While oscillations have been implicated in many high level processes, for most such phenomena we cannot say with confidence precisely what they are doing at an algorithmic or implementational level. This thesis presents work towards understanding the dynamics and possible function of large scale oscillatory network activity. We first address the question of how coherent oscillatory activity emerges between local networks by measuring phase response curves of an oscillating network in vitro. The network phase response curves provide mechanistic insight into inter-region synchronisation of local network oscillators. Highly simplified firing models are shown to reproduce the experimental data with remarkable accuracy. We then focus on one hypothesised computational function of network oscillations; flexibly controlling the gain of signal flow between anatomically connected networks. We investigate coding strategies and algorithmic operations that support flexible control of signal flow by oscillations, and their implementation by network dynamics. We identify two readout algorithms which selectively recover population rate coded signal with specific oscillatory modulations while ignoring other distracting inputs. By designing a spiking network model that implements one of these mechanisms, we demonstrate oscillatory control of signal flow in convergent pathways. We then investigate constraints on the structures of oscillatory activity that can be used to accurately and selectively control signal flow. Our results suggest that for inputs to be accurately distinguished from one another their oscillatory modulations must be close to orthogonal. This has implications for interpreting in vivo oscillatory activity, and may be an organising principle for the spatio-temporal structure of brain oscillations

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Investigating the Homeostatic Regulation of Kenyon Cells in Drosophila

How do Kenyon cells behave consistently with such a high variation of inputs? In Drosophila, stimulus-specificity of associative memories requires sparse coding in the neurons that are storing the memory. Effective sparse coding requires that the neurons have approximately equal probabilities of firing across all stimuli. Otherwise, some cells will be disproportionately active or silent, and thereby be less informative about stimulus identity. I study the problem of how distributed sparse coding is maintained in Kenyon cells (KCs), which are the third-order olfactory neurons. I hypothesised that KCs homeostatically adjust their intrinsic properties to ensure even activity across the population of KCs. I investigated this hypothesis using a combination of two-photon imaging and genetic manipulation of ion channel expression. Sodium and potassium channels are responsible for the depolarisation and repolarisation of the membrane, respectively. I conducted experiments to investigate the impact of artificially manipulating the expression of sodium and potassium channels on KCs' activity. Additionally, I examined whether this manipulation could potentially regulate the expression of other sodium and potassium channels through homeostatic mechanisms. My results indicate that constitutively overexpressing NaChBac, an exogenous voltage-gated sodium channel, in KCs paradoxically decreases their activity. The neurons’ activity was measured by amplitude of odour responses with calcium imaging. The developmental expression and two days of acute NaChBac expression in adults produced a significant decrease in odour responses. However, 4 days of acute expression in adults increased the odour responses of specific KCs. When NaChBac was expressed in adults for 8 days, odour responses were not significantly different from control. Thus, only specific acute expression of NaChBac causes an increase in excitability. When investigating whether the KCs had homeostatic mechanisms that counteracted NaChBac’s effect, I found that the levels of other ion channels had adjusted. Constitutively expressing NaChBac decreased expression of para, the endogenous voltage-gated sodium channel responsible for generating action potentials. It may be that NaChBac expression decreases Para levels to prevent overexcitation. Furthermore, NaChBac expression also increases endogenous levels of the potassium channel, Shaker. As NaChBac causes abnormally long action potentials due to its slow kinetics, while Shaker is normally responsible for membrane repolarisation at the end of an action potential, it may be that the increased Shaker is an attempt to compensate for the prolonged depolarisation caused by NaChBac. In contrast, knocking down or disrupting a multitude of endogenous potassium channels in KCs appeared to have very little effect on KC activity. This finding is unlike what it is typically found in most past literature that focuses on disrupting potassium channels. The project revealed a paradoxical response of KCs when they were artificially excited by expressing NaChBac and disrupting their potassium channels. Additionally, the project discovered that KCs can modulate their ion channel expression levels in response to NaChBac expression

The Hidden Forms And Functions Of Courtship In The Brown-Headed Cowbird (molothrus Ater)

Reproductive fitness is the result of complex interacting processes, however our understanding of reproduction is often limited to a few, static male traits. While conspicuous male traits are very well studied, female behavior has received far less attention. Furthermore, conspicuous male traits often fail to predict reproductive success, suggest that there are other important aspects of sexual behavior, however what these factors are or how they interact remains largely unknown. Brown-headed cowbirds (Molothrus ater) breed readily in captivity and their copulatory behavior can be evoked under carefully controlled experimental conditions. By pairing many years of behavioral observations with careful analysis and quantification of behavior, I identified several mechanisms guiding courtship and reproduction. Female copulation is directly evoked by male song, and the strength of the copulatory display reflects signal strength. Interestingly, the copulatory display is mediated by the variable behavioral state of the female, suggesting that song alone is insufficient to elicit copulation. Flocks also display measurable cohesion in the timing of their behavior, transitioning as a group between singing to males and singing to females, and the strength of this group cohesion predicts reproductive success for both individuals and the group as a whole. This work shows that reproductive fitness is far richer than just the quality of male signals and provides a platform to understand the rich complexity of animal courtship

Integrative (Synchronisations-)Mechanismen der (Neuro-)Kognition vor dem Hintergrund des (Neo-)Konnektionismus, der Theorie der nichtlinearen dynamischen Systeme, der Informationstheorie und des Selbstorganisationsparadigmas

Der Gegenstand der vorliegenden Arbeit besteht darin, aufbauend auf dem (Haupt-)Thema, der Darlegung und Untersuchung der Lösung des Bindungsproblems anhand von temporalen integrativen (Synchronisations-)Mechanismen im Rahmen der kognitiven (Neuro-)Architekturen im (Neo-)Konnektionismus mit Bezug auf die Wahrnehmungs- und Sprachkognition, vor allem mit Bezug auf die dabei auftretende Kompositionalitäts- und Systematizitätsproblematik, die Konstruktion einer noch zu entwickelnden integrativen Theorie der (Neuro-)Kognition zu skizzie-ren, auf der Basis des Repräsentationsformats einer sog. „vektoriellen Form“, u.z. vor dem Hintergrund des (Neo-)Konnektionismus, der Theorie der nichtlinearen dynamischen Systeme, der Informationstheorie und des Selbstorganisations-Paradigmas