136 research outputs found

    Decentralized Limited-Feedback Multiuser MIMO for Temporally Correlated Channels

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    Distribution dependent adaptive learning

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

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    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

    A Comprehensive Review on Various Estimation Techniques for Multi Input Multi Output Channel

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    لقد تطورت مشكلة تقدير القناة اللاسلكية بسبب بعض التأثيرات غير المرغوب فيها للخواص الفيزيائية للقناة على الإشارات المرسلة. في نهاية المستقبل، التشوه، والتأخير، والتوهين، والتداخلات، ونوبات الطور هي أكثر المشكلات التي تواجهها مع الإشارات المستقبلة. من أجل التغلب على تأثيرات القناة وتوفير جودة كاملة تقريبًا لنقل البيانات، يلزم تقدير معلومات القناة. في أنظمة المخرجات متعددة المدخلات والمخرجات (MIMO)، يعتبر تقدير القناة خطوة أكثر تعقيدًا مقارنة بأنظمة المخرجات ذات المدخلات المفردة، SISO، نظرًا لأن عدد القنوات الفرعية التي تحتاج إلى تقدير أكبر بكثير من انظمة SISO. الهدف الأساسي من هذه الورقة البحثية هو مراجعة شاملة لاغلب الخوارزميات الشهيرة والفعالة التي تم ابتكارها لحل مشكلة تقدير قناة MIMO في أنظمة الاتصالات اللاسلكية. في هذه الورقة، تم تصنيف هذه التقنيات إلى ثلاث مجموعات: غير المكفوفين، شبه الأعمى وتقدير أعمى. لكل مجموعة، يتم تقديم توضيح مختصر لخوارزميات التقدير المألوفة. وأخيرًا، نقارن بين هذه التقنيات استنادًا إلى التعقيد الحسابي والكمون ودقة التقدير.The problem of wireless channel estimation has been evolving due to some undesirable effects of channel physical properties on transmitted signals. At the receiver end, distortions, delays, attenuations, interferences, and phase shifts are the most issues encounter together with the received signals. In order to overcome channel effects and provide almost a perfect quality of data transmission, channel parameter estimation is needed. In Multiple Input-Multiple Output systems (MIMO), channel estimation is a more complicated step as compared with the Single Input-Single Output systems, SISO, because of the fact that the number of sub-channels that needs estimate is much greater than SISO systems. The fundamental objective of this research paper is to go over the famous and efficient algorithms that have been innovated to solve the problem of MIMO channel estimation in wireless communication systems. In this paper, these techniques have been classified into three groups: non-blind, semi-blind and blind estimation. For each group, a brief illustration is presented for familiar estimation algorithms. Finally, we compare between these techniques based on computational complexity, latency and estimation accuracy

    Estimation and detection techniques for doubly-selective channels in wireless communications

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    A fundamental problem in communications is the estimation of the channel. The signal transmitted through a communications channel undergoes distortions so that it is often received in an unrecognizable form at the receiver. The receiver must expend significant signal processing effort in order to be able to decode the transmit signal from this received signal. This signal processing requires knowledge of how the channel distorts the transmit signal, i.e. channel knowledge. To maintain a reliable link, the channel must be estimated and tracked by the receiver. The estimation of the channel at the receiver often proceeds by transmission of a signal called the 'pilot' which is known a priori to the receiver. The receiver forms its estimate of the transmitted signal based on how this known signal is distorted by the channel, i.e. it estimates the channel from the received signal and the pilot. This design of the pilot is a function of the modulation, the type of training and the channel. [Continues.

    Investigation of coding and equalization for the digital HDTV terrestrial broadcast channel

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    Includes bibliographical references (p. 241-248).Supported by the Advanced Telecommunications Research Program.Julien J. Nicolas

    Interference Mitigation in Wireless Communications

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    The primary objective of this thesis is to design advanced interference resilient schemes for asynchronous slow frequency hopping wireless personal area networks (FH-WPAN) and time division multiple access (TDMA) cellular systems in interference dominant environments. We also propose an interference-resilient power allocation method for multiple-input-multiple-output (MIMO) systems. For asynchronous FH-WPANs in the presence of frequent packet collisions, we propose a single antenna interference canceling dual decision feedback (IC-DDF) receiver based on joint maximum likelihood (ML) detection and recursive least squares (RLS) channel estimation. For the system level performance evaluation, we propose a novel geometric method that combines bit error rate (BER) and the spatial distribution of the traffic load of CCI for the computation of packet error rate (PER). We also derived the probabilities of packet collision in multiple asynchronous FH-WPANs with uniform and nonuniform traffic patterns. For the design of TDMA receivers resilient to CCI in frequency selective channels, we propose a soft output joint detection interference rejection combining delayed decision feedback sequence estimation (JD IRC-DDFSE) scheme. In the proposed scheme, IRC suppresses the CCI, while DDFSE equalizes ISI with reduced complexity. Also, the soft outputs are generated from IRC-DDFSE decision metric to improve the performance of iterative or non-iterative type soft-input outer code decoders. For the design of interference resilient power allocation scheme in MIMO systems, we investigate an adaptive power allocation method using subset antenna transmission (SAT) techniques. Motivated by the observation of capacity imbalance among the multiple parallel sub-channels, the SAT method achieves high spectral efficiency by allocating power on a selected transmit antenna subset. For 4 x 4 V-BLAST MIMO systems, the proposed scheme with SAT showed analogous results. Adaptive modulation schemes combined with the proposed method increase the capacity gains. From a feasibility viewpoint, the proposed method is a practical solution to CCI-limited MIMO systems since it does not require the channel state information (CSI) of CCI.Ph.D.Committee Chair: Professor Gordon L. StBe

    Theory, design and application of gradient adaptive lattice filters

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    SIGLELD:D48933/84 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

    Multi-user detection for multi-rate DS/CDMA systems

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    Wireless cellular communication is witnessing a rapid growth in market, technology and range of services. Current and future demands for wireless communication services motivate the need for handling multi-media traffic types. In a multimedia communication system, users with different and even time-varying rates and quality of services (QoS) requirements, such as voice, image and data, must be accommodated. The use of Spread Spectrum modulation with Code Division Multiple Access (CDMA) technology is an attractive approach for economical spectrally efficient and high quality cellular and personal communication services. This dissertation explores the technologies of applying different interference cancellation techniques to multi-rate CDMA systems that serve users with different QoS. Multiple Access Interference (MAI) and multipath propagation are the major issues in wireless communication systems. It is also true for multi-rate CDMA systems. Multi-user detection has been shown to be effective in combating the near-far problem and providing superior performance over conventional detection method. In this dissertation, we combine both linear minimum mean squared error (LMMSE) detector, nonlinear decision feedback detector, with other signal processing techniques, such as array processing and multipath combining, to create effective near-far resistant detectors for multi-rate CDMA systems. Firstly, we propose MMSE receivers for synchronous multi-rate CDMA system and compare the performance with the corresponding multi-rate decorrelating detectors. The multi-rate decorrelating detector is optimally near-far resistant and easy to implement. The proposed linear MMSE multi-rate receiver can be adaptively implemented only with the knowledge of the desired user. Due to the fact that MMSE detector offers best trade-off between the MAI cancellation and noise variance enhancement, it is shown that multi-rate MMSE receiver can offer better performance than the multi-rate decorrelator when the interfering users\u27 Signal to Noise Ratio (SNR) is relatively low comparing to the desired user\u27s SNR. Secondly, the asynchronous multi-rate CDMA system, we propose multi-rate multi-shoot decorrelating detectors and multi-rate multi-shot MMSE detectors. The performance of multi-shot detectors can be improved monotonically with increasing the number of stacked bits, but a great computational complexity is going to be introduced in order to get better performance. A debiasing method is introduced to multi-rate multi-shot linear detectors. Debiasing method optimizes multi-rate detectors based on the multi-rate multi-shot model. Debiasing multi-shot MMSE detector for multi-rate signals can offer performance than the corresponding debiasing multi-shot decorrelating detector. Thirdly, we propose linear space-time receivers for multi-rate CDMA systems. The minimum mean-squared error criteria is used. We perform a comparative study on the multi-rate receiver which uses either multipath (temporal) processing or array (spatial) processing, and the one which uses both array and multipath (space-time) processing. The space-time receiver for the multi-rate CDMA signals give us the potential of improving the capacity of multi-rate systems. The space-time processing combined with multiuser detection have the advantages of combating multipath fading through temporal processing, reducing MAI through MMSE method and provide antenna or diversity gain through spatial processing and increasing the capacity of the multi-rate CDMA systems. Lastly, the group-wise interference cancellation methods are proposed for multi-rate CDMA signals. The non-linear decision feedback detection (DFD) schemes are used in the proposed receivers. The proposed interference cancellation schemes benefit from the nature of the unequal received amplitudes for multi-rate CDMA signals. Users with same data rate are grouped together. Users with the highest data-rate are detected first. Interference between the groups is cancelled in a successive order. The results show that the group-wise MMSE DFD yields better performance than multi-rate linear MMSE detector and multi-rate decorrelating detector, especially for highly loaded CDMA systems
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