The challenging problem in the design of digital receivers of today's and future high-speed, high data-rate wireless communication systems is to implement the optimal decoding and channel estimation processes join...
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The challenging problem in the design of digital receivers of today's and future high-speed, high data-rate wireless communication systems is to implement the optimal decoding and channel estimation processes jointly in a computationally feasible way. Without realising such a critical function perfectly at receiver, the whole system will not work properly within the desired performance limits. Unfortunately, direct implementation of such optimal algorithms is not possible mainly due to their mathematically intractable and computationally prohibitive nature. A novel algorithm that reaches the performance of the optimal maximum a posteriori (map) algorithm with a feasible computational complexity is proposed. The algorithm makes use of a powerful statistical signal processing tool called the expectation-maximisation (EM) technique. It iteratively executes the map joint channel estimation and decoding for space-time block-coded orthogonal frequency division multiplexing systems with turbo channel coding in the presence of unknown wireless dispersive channels. The main novelty of the work comes from the facts that the proposed algorithm estimates the channel in a non-data-aided fashion and therefore except a small number of pilot symbols required for initialisation, no training sequence is necessary. Also the approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and finds map estimates of the uncorrelated KL series expansion coefficients. Based on such an expansion, no matrix inversion is required in the proposed map estimator. Moreover, optimal rank reduction is achieved by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the iterative estimation approach.
This paper investigates the use of a maximum a posteriori probability (map) algorithm to realize soft-output equalization in a concatenated equalization and trellis-coded modulation (TCM) decoding-based wireless commu...
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This paper investigates the use of a maximum a posteriori probability (map) algorithm to realize soft-output equalization in a concatenated equalization and trellis-coded modulation (TCM) decoding-based wireless communication system. Specifically, we first begin with a general map algorithm and then focus on studying Bahl's map and Lee's map algorithms. We then propose a modified version of Lee's map algorithm which is much simpler than the original, in terms of complexity, and is more practical. In particular, a very simple channel estimation method which employs orthogonal training sequences is proposed. In order to improve the system performance, equal-gain combining and selection diversity will be also considered. Finally, we compare the performance of the map algorithm-based equalization with our previously proposed equalization scheme, which combines decision feedback equalization and TCM.
The Tsinghua University MUon Tomography facility (TUMUTY) has been built up and it is utilized to reconstruct the special objects with complex structure. Since fine image is required, the conventional Maximum likeliho...
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The Tsinghua University MUon Tomography facility (TUMUTY) has been built up and it is utilized to reconstruct the special objects with complex structure. Since fine image is required, the conventional Maximum likelihood Scattering and Displacement (MLSD) algorithm is employed. However, due to the statistical characteristics of muon tomography and the data incompleteness, the reconstruction is always instable and accompanied with severe noise. In this paper, we proposed a Maximum a Posterior (map) algorithm for muon tomography regularization, where an edge-preserving prior on the scattering density image is introduced to the object function. The prior takes the l(p), norm (p > 0) of the image gradient magnitude, where p = 1 and p = 2 are the well-known total-variation (TV) and Gaussian prior respectively. The optimization transfer principle is utilized to minimize the object function in a unified framework. At each iteration the problem is transferred to solving a cubic equation through paraboloidal surrogating. To validate the method, the French Test Object (FTO) is imaged by both numerical simulation and TUMUTY. The proposed algorithm is used for the reconstruction where different norms are detailedly studied, including l(2), l(1), l(05), and an l(2-05) mixture norm. Compared with MLSD method, map achieves better image quality in both structure preservation and noise reduction. Furthermore, compared with the previous work where one dimensional image was acquired, we achieve the relatively clear three dimensional images of FTO, where the inner air hole and the tungsten shell is visible. (C) 2015 Elsevier B.V. All rights reserved.
To decrease the storage complexity of a double binary convolutional turbo code (DB-CTC) decoder, a novel decoding scheme is proposed in this paper. Different from the conventional decoding scheme, only a part of the s...
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To decrease the storage complexity of a double binary convolutional turbo code (DB-CTC) decoder, a novel decoding scheme is proposed in this paper. Different from the conventional decoding scheme, only a part of the state metrics is stored in the last-in first-out (LIFO) state metrics cache (SMC). Based on an improved maximum a posteriori probability (map) algorithm, we present a method to recalculate the unstored state metrics at the corresponding decoding time slot, and discuss in detail the procedures of the recalculation are discussed. Because of the compare-select-recalculate processing operations, compared to the classical decoding scheme, the proposed decoding scheme reduces the storage complexity of SMC and the amount of memory accesses by approximately 40% while limiting involved computational cost. Moreover, simulation results show that the proposed scheme achieves good decoding performance, which is close to that of the well-known Log-map algorithm. (c) 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
作者:
Park, GHYoon, SHHong, DKang, CEYonsei Univ
Dept Elect & Comp Engn Informat & Telecommun Lab Seodaemoon Gu Seoul 120749 South Korea LG Elect Inc
LG R&D Complex 533 Mobile Comm Res Lab Dept Mobile Comm TechDongan Gu Kyeongku Do 431749 South Korea
Several implementation methods for a map decoder are proposed in this paper, Using a novel pipeline structured time-shared process, the authors are able to efficiently overcome the restrictions imposed by the recursio...
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Several implementation methods for a map decoder are proposed in this paper, Using a novel pipeline structured time-shared process, the authors are able to efficiently overcome the restrictions imposed by the recursion process on state metrics. and the complexity of the map decoder can be reduced to a level on the order of a SOVA (Soft Output Viterbi algorithm) decoder. In addition. the authors propose an efficient controller structure that can be used for variable frame-size systems such as cdma-2000. The map decoder using a block-wise algorithm designed here was implemented in only one 20,000 gate circuit. It was validated by VHDL, which was compared with the results of the initial simulation (C programs). The decoder demonstrated a 300 kbps decoding processing ability with 8 iterations on a FPGA circuit, with a deviation only about 0.1-0.2 dB greater than that for an ideal map decoder, even when all hardware environments are considered.
Cosmic ray muon tomography is a novel technology to detect high-Z material. A prototype of TUMUTY with 73.6 cm x 73.6 cm large scale position sensitive MRPC detectors has been developed and is introduced in this paper...
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Cosmic ray muon tomography is a novel technology to detect high-Z material. A prototype of TUMUTY with 73.6 cm x 73.6 cm large scale position sensitive MRPC detectors has been developed and is introduced in this paper. Three test kits have been tested and image is reconstructed using map algorithm. The reconstruction results show that the prototype is working well and the objects with complex structure and small size (20 mm) can be imaged on it, while the high-Z material is distinguishable from the low-Z one. This prototype provides a good platform for our further studies of the physical characteristics and the performances of cosmic ray muon tomography. (C) 2015 Elsevier B.V. All rights reserved.
A novel type of recursive algorithm for decoding turbo codes with a convolutional interleaver is proposed, based on a symbol-by-symbol maximum a posteriori probability algorithm. It requires only a forward recursion w...
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A novel type of recursive algorithm for decoding turbo codes with a convolutional interleaver is proposed, based on a symbol-by-symbol maximum a posteriori probability algorithm. It requires only a forward recursion which can be performed in parallel, and the number of variables to be stored does not increase with decoding delay. This algorithm can be used in continuous decoding for both recursive and nonrecursive encoders. Simulation results of demonstrating its performance are presented.
Behavior planning is an important function of any complex technical facility intelligent control system. Presently, a symbol paradigm of artificial intelligence offers a variety of planning algorithms, including those...
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Behavior planning is an important function of any complex technical facility intelligent control system. Presently, a symbol paradigm of artificial intelligence offers a variety of planning algorithms, including those that use precedent information, i.e. algorithms based on acquired knowledge. A symbol grounding problem within the exiting approaches of knowledge representation does not allow effective use the developed algorithms together with learning mechanisms for the purpose of solving a wide variety of applied problems by actual intelligent agents (robotics systems). This article presents the original planning algorithm (map Planner), which uses a sign world model as the basis for acquisition and maintenance of knowledge for future use in behavior planning. the sign problem approach describes planning as a cognitive function actualized by the world model of a subject of activity. Apart from solving symbol grounding problems and ensuring psychological and biological plausibility, a sign planning process model allows interaction of an intelligent agent with other participants in solving a cooperative task. The article presents the description of the knowledge representation method used, a map planning algorithm, and a model experiment in a "block world". (C) 2016 Elsevier B.V. All rights reserved.
Symbol-by-symbol maximum a posteriori (map) decoding algorithms for nonbinary block and convolutional codes over an extension field GF (p(a)) are presented. Equivalent map decoding rules employing the dual code are gi...
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Symbol-by-symbol maximum a posteriori (map) decoding algorithms for nonbinary block and convolutional codes over an extension field GF (p(a)) are presented. Equivalent map decoding rules employing the dual code are given which are computationally more efficient for high-rate codes. It is shown that these algorithms meet all requirements needed for iterative decoding as the output of the decoder can be split into three independent estimates: soft channel value, a priori term and extrinsic value. The discussed algorithms are then applied to a parallel concatenated coding scheme with nonbinary component codes in conjunction with orthogonal signaling.
In order to calculate the branches metric in the maximum a posteriori algorithm of turbo decoder, it is mandatory to know the values of parameters of the noise contaminating the transmitted signal. In the case of a ge...
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In order to calculate the branches metric in the maximum a posteriori algorithm of turbo decoder, it is mandatory to know the values of parameters of the noise contaminating the transmitted signal. In the case of a generalized Gaussian distribution impulsive noise, it is very difficult to estimate the shape parameter, because the noise is inseparable from transmitted signal at turbo decoder reception. Until now, few researches about shape parameter estimation for an impulsive noise on turbo codes have been presented, and existing estimation methods use only the high order statistics (HOS). In this paper, we propose a novel semi-blind method, that does not use the HOS, to estimate the shape parameter from only the received signal in the turbo decoder. This method is based on fractional lower order statistics and the probability that the received signal is the same sign as the transmitted signal modulated with BPSK. The results, in terms of root mean square error, show the advantage of our method over other methods using HOS in the case of impulsive noise.
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