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

Optimal Receiver Design for Diffusive Molecular Communication With Flow and Additive Noise

In this paper, we perform receiver design for a diffusive molecular communication environment. Our model includes flow in any direction, sources of information molecules in addition to the transmitter, and enzymes in the propagation environment to mitigate intersymbol interference. We characterize the mutual information between receiver observations to show how often independent observations can be made. We derive the maximum likelihood sequence detector to provide a lower bound on the bit error probability. We propose the family of weighted sum detectors for more practical implementation and derive their expected bit error probability. Under certain conditions, the performance of the optimal weighted sum detector is shown to be equivalent to a matched filter. Receiver simulation results show the tradeoff in detector complexity versus achievable bit error probability, and that a slow flow in any direction can improve the performance of a weighted sum detector.Comment: 14 pages, 7 figures, 1 appendix. To appear in IEEE Transactions on NanoBioscience (submitted July 31, 2013, revised June 18, 2014, accepted July 7, 2014

Implementable Wireless Access for B3G Networks - III: Complexity Reducing Transceiver Structures

This article presents a comprehensive overview of some of the research conducted within Mobile VCE’s Core Wireless Access Research Programme,1 a key focus of which has naturally been on MIMO transceivers. The series of articles offers a coherent view of how the work was structured and comprises a compilation of material that has been presented in detail elsewhere (see references within the article). In this article MIMO channel measurements, analysis, and modeling, which were presented previously in the first article in this series of four, are utilized to develop compact and distributed antenna arrays. Parallel activities led to research into low-complexity MIMO single-user spacetime coding techniques, as well as SISO and MIMO multi-user CDMA-based transceivers for B3G systems. As well as feeding into the industry’s in-house research program, significant extensions of this work are now in hand, within Mobile VCE’s own core activity, aiming toward securing major improvements in delivery efficiency in future wireless systems through crosslayer operation

Exploiting Diversity in Broadband Wireless Relay Networks

Fading is one of the most fundamental impairments to wireless communications. The standard approach to combating fading is by adding redundancy - or diversity - to help increase coverage and transmission speed. Motivated by the results in multiple-input multiple-output technologies, which are usually used at base stations or access points, cooperation commutation has been proposed to improve the performance of wireless networks which consist of low-cost single antenna devices. While the majority of the research in cooperative communication focuses on flat fading for its simplicity and easy analysis, in practice the underlying channels in broadband wireless communication systems such as cellular systems (UMTS/LTE) are more likely to exhibit frequency selective fading. In this dissertation, we consider a frequency selective fading channel model and explore distributed diversity techniques in broadband wireless relay networks, with consideration to practical issues such as channel estimation and complexity-performance tradeoffs. We first study a system model with one source, one destination and multiple decode-and-forward (DF) relays which share a single channel orthogonal to the source. We derive the diversity-multiplexing tradeoff (DMT) for several relaying strategies: best relay selection, random relay selection, and the case when all decoding relays participate. The best relay selection method selects the relay in the decoding set with the largest sum-squared relay-to-destination channel coefficients. This scheme can achieve the optimal DMT of the system at the expense of higher complexity, compared to the other two relaying strategies which do not always exploit the spatial diversity offered by the relays. Different from flat fading, we find special cases when the three relaying strategies have the same DMT. We further present a transceiver design and prove it can achieve the optimal DMT asymptotically. Monte Carlo simulations are presented to corroborate the theoretical analysis. We provide a detailed performance comparison of the three relaying strategies in channels encountered in practice. The work has been extended to systems with multiple amplify-and-forward relays. We propose two relay selection schemes with maximum likelihood sequential estimator and linear zero- forcing equalization at the destination respectively and both schemes can asymptotically achieve the optimal DMT. We next extend the results in the two-hop network, as previously studied, to multi-hop networks. In particular, we consider the routing problem in clustered multi-hop DF relay networks since clustered multi-hop wireless networks have attracted significant attention for their robustness to fading, hierarchical structure, and ability to exploit the broadcast nature of the wireless channel. We propose an opportunistic routing (or relay selection) algorithm for such networks. In contrast to the majority of existing approaches to routing in clustered networks, our algorithm only requires channel state information in the final hop, which is shown to be essential for reaping the diversity offered by the channel. In addition to exploiting the available diversity, our simple cross-layer algorithm has the flexibility to satisfy an additional routing objective such as maximization of network lifetime. We demonstrate through analysis and simulation that our proposed routing algorithm attains full diversity under certain conditions on the cluster sizes, and its diversity is equal to the diversity of more complicated approaches that require full channel state information. The final part of this dissertation considers channel estimation in relay networks. Channel state information is vital for exploiting diversity in cooperative networks. The existing literature on cooperative channel estimation assumes that block lengths are long and that channel estimation takes place within a fading block. However, if the forwarding delay needs to be reduced, short block lengths are preferred, and adaptive estimation through multiple blocks is required. In particular, we consider estimating the relay-to-destination channel in DF relay systems for which the presence of forwarded information is probabilistic since it is unknown whether the relay participates in the forwarding phase. A detector is used so that the update of the least mean square channel estimate is made only when the detector decides the presence of training data. We use the generalized likelihood ratio test and focus on the detector threshold for deciding whether the training sequence is present. We also propose a heuristic objective function which leads to a proper threshold to improve the convergence speed and reduce the estimation error. Extensive numerical results show the superior performance of using this threshold as opposed to fixed thresholds

Turbo receivers for interleave-division multiple-access systems

In this paper several turbo receivers for Interleave-Division Multiple-Access (IDMA) systems will be discussed. The multiple access system model is presented first. The optimal, Maximum A Posteriori (MAP) algorithm, is then presented. It will be shown that the use of a precoding technique at the emitter side is applicable to IDMA systems. Several low complexity Multi-User Detector (MUD), based on the Gaussian approximation, will be next discussed. It will be shown that the MUD with Probabilistic Data Association (PDA) algorithm provides faster convergence of the turbo receiver. The discussed turbo receivers will be evaluated by means of Bit Error Rate (BER) simulations and EXtrinsic Information Transfer (EXIT) charts