In this study, we propose a superposed probabilistically shaped(PS) quadrature amplitude modulation(QAM) constellation scheme for multiple-input multiple-output visible light communication systems. PS QAM signals are ...
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In this study, we propose a superposed probabilistically shaped(PS) quadrature amplitude modulation(QAM) constellation scheme for multiple-input multiple-output visible light communication systems. PS QAM signals are generated from a nonlinear coding equation that converts uniformly distributed 8-level signals into PS 9-or 10-level signals, which are then mapped into PS 9QAM or 10QAM signals. Square-shaped 9QAM and trapezoid-shaped 10QAM constellations are introduced to maximize the minimum Euclidean distance(MED) of the superposed constellation. Finally, the PS 9QAM and 10QAM signals are superposed with the 4QAM signals in a flipped manner to obtain PS 36QAM or 40QAM signals at the receiver, *** exploit the temporal correlation of the resulting signal from nonlinear coding, we developed a detection algorithm based on Viterbi decoding. Experimental results confirmed the superiority of the proposed schemes by achieving a higher MED and stronger ability to resist nonlinearity. Compared with the traditional scheme, the peak-to-peak voltage dynamic ranges of the superposed 36QAM and 40QAM constellation schemes were improved by 52% and 48%, respectively.
In this paper,we propose a 36-quadrature amplitude modulation(QAM)superposition modulation technique that is featured with uneven symbol probability by nonlinear precoding,named nonlinear coded nonuniform superpositio...
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In this paper,we propose a 36-quadrature amplitude modulation(QAM)superposition modulation technique that is featured with uneven symbol probability by nonlinear precoding,named nonlinear coded nonuniform superposition(NCNS)*** aim is to alleviate the nonlinearity effect caused by high instantaneous power in multi-input single-output(MISO)visible light communication(VLC)system,with an uneven probabilistic-shaped *** transmitter includes two LEDs to send signals independently,and the receiver uses a photo detector to receive the superposed QAM *** experiment results show that NCNS has a better robustness against nonlinearity than pulse amplitude modulation 4,approximately gaining a 16% increase in maximum usable peak-to-peak voltage and a 33% enlargement in dynamic range *** is a simple but effective approach to solve the bandwidth limits related to signal power and hopefully be applied in large power VLC systems such as underwater VLC,or to improve the robustness against power fluctuation.
Multiple-Input-Single-Output (MISO) is a promising application for visible light communication (VLC) system, which is featured in large user capacity, but also suffers from the nonlinearity problem introduced by the l...
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ISBN:
(数字)9781510651852
ISBN:
(纸本)9781510651852;9781510651845
Multiple-Input-Single-Output (MISO) is a promising application for visible light communication (VLC) system, which is featured in large user capacity, but also suffers from the nonlinearity problem introduced by the light emitting diode (LED) itself and the signal superposition at the receiver. In this article, to suppress the negative effect of nonlinearity in MISO VLC system that utilizes superposition modulation, we proposed a solution that applies nonlinear Trellis-Coded Precoding (NL-TCP) to shape the spectrum and constellation diagram of the original PAM-4. A PAM-6 signal converted from PAM-4 by NL-TCP algorithm successfully lowers its BER under the threshold for 7% FEC and supports up to 1.1 Gb/s data rate within severe nonlinearity, while the conventional PAM-4 modulation fails to meet the threshold requirement. The maximum improvement in Q-factor recorded is 1.2dB at the data rate of 1 Gb/s. In comparison, NL-TCP is more sensitive to the data rate, but it has a more desirable robustness against the nonlinearity in the channel. This experiment verifies the practical benefit of NL-TCP in high nonlinearity channel. It is believed that this research is significative for the researchers who are aimed at establishing a usable link, yet have to tolerate the nonlinearity to exist in the channel.
Based on the assumption about the sparse representation of natural images and the theory of compressed sensing, very promising results about single-image super-resolution were obtained by an excellent algorithm introd...
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Based on the assumption about the sparse representation of natural images and the theory of compressed sensing, very promising results about single-image super-resolution were obtained by an excellent algorithm introduced by Yang et al. [45]. However, their success could not be well explained theoretically. The lack of theoretical insight has hindered the further improvement of the algorithm. In this paper, Yang's algorithm is revisited in the view of learning theory. According to this point, Yang's algorithm can be considered as a linear regression method in a special feature space which is named as sparse coding space by us. In fact, it has been shown that Yang's algorithm is a result of optimal linear estimation in sparse coding space. More importantly, our theoretical analysis suggests that Yang's algorithm can be improved by using more flexible regression methods than the linear regression method. Following the idea, a novel single-image super-resolution algorithm which is designed based on the framework of L-2-Boosting is proposed in the paper. The experimental results show the effectiveness of the proposed algorithm by comparing with other methods, which verify our theoretical analysis about Yang's algorithm. (C) 2012 Elsevier Inc. All rights reserved.
In this paper, we propose a deterministic tensor-based approach for joint channel and symbol estimation in the context of multiuser single-input multi-output (SIMO) CDMA communication systems. We use a new nonlinear (...
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In this paper, we propose a deterministic tensor-based approach for joint channel and symbol estimation in the context of multiuser single-input multi-output (SIMO) CDMA communication systems. We use a new nonlinear (NL) coding allowing to obtain a third-order block-Tucker2 model for the signals received by multiple receive antennas, with a constrained structure for the core tensors that ensures the uniqueness of the tensor model. Assuming that the users' code matrices are mutually orthogonal and known at the receiver, we derive a blind algorithm composed of two steps: a separation of users' contributions in the received signals, with decoding, followed by a blind channel and symbol estimation for each user separately. Some simulation results are provided to illustrate the performance of the proposed blind receiver. (C) 2011 Elsevier B.V. All rights reserved.
The authors consider the acquisition of measurements from a source, representing a physical phenomenon, by means of sensors deployed at different distances, and measuring random variables (r.v.'s) that are correla...
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The authors consider the acquisition of measurements from a source, representing a physical phenomenon, by means of sensors deployed at different distances, and measuring random variables (r.v.'s) that are correlated with the source output. The acquired values are transmitted over a wireless channel to a sink, where an estimation of the source has to be constructed, according to a given distortion criterion. In the presence of Gaussian random variables (r.v.'s) and a Gaussian vector channel, the authors are seeking optimum real-time joint source-channel encoder-decoder pairs that achieve a distortion sufficiently close to the theoretically optimal one, under a global resource constraint, by activating only a subset of the sensors. The problem is posed in a team decision theoretic framework, and the optimal strategies are approximated by means of neural networks. The analysis investigates the generalisation capabilities of the proposed approach, by showing insights into the structure of the problem. The surprising outcome is that a quasi-static application of the approach reveals to be sufficient to maintain quasi-optimal performance under a dynamic environment (e. g. with respect to nodes' positions).
This paper studies the capacity of single-source single-sink noiseless networks under adversarial or arbitrary errors on no more than edges. Unlike prior papers, which assume equal capacities on all links, arbitrary l...
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This paper studies the capacity of single-source single-sink noiseless networks under adversarial or arbitrary errors on no more than edges. Unlike prior papers, which assume equal capacities on all links, arbitrary link capacities are considered. Results include new upper bounds, network error-correction coding strategies, and examples of network families where our bounds are tight. An example is provided of a network where the capacity is 50% greater than the best rate that can be achieved with linear coding. While coding at the source and sink suffices in networks with equal link capacities, in networks with unequal link capacities, it is shown that intermediate nodes may have to do coding, nonlinear error detection, or error correction in order to achieve the network error-correction capacity.
Neural computation in sensory systems is often modeled as a linear system. This first order approximation is computed by reverse correlating a stimulus with the spike train it evokes. The spectro-temporal receptive fi...
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Neural computation in sensory systems is often modeled as a linear system. This first order approximation is computed by reverse correlating a stimulus with the spike train it evokes. The spectro-temporal receptive field (STRF) is a generalization of this procedure which characterizes processing in the auditory pathway in both frequency and time. While the STRF performs well in predicting the overall course of the response to a novel stimulus, it is unable to account for aspects of the neural output which are inherently nonlinear (e.g. discrete events and non-negative spike rates). We measured the STRFs of neurons in the primary auditory cortex (Al) of the awake ferret using spectro-temporally modulated auditory gratings, or ripples. We quantified the degree of nonlinearity of these neurons by comparing their responses to the responses predicted from their respective STRFs. The responses of most cells in Al exhibited a squaring, nonlinear relation to the stimuli used to evoke them. Thus, the nonlinearity of these cells was nontrivial, that is it was not solely the result of spike rate rectification or saturation. By modeling the nonlinearity as a polynomial static output function, the predictive power of the STRF was significantly improved. (C) 2010 IBRO. Published by Elsevier Ltd. All rights reserved.
Although various methods exist in soft decision decoding methods for block codes, of those that can be applied to linear and nonlinear coding, there are not many with low levels of computation that provide high levels...
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Although various methods exist in soft decision decoding methods for block codes, of those that can be applied to linear and nonlinear coding, there are not many with low levels of computation that provide high levels...
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Although various methods exist in soft decision decoding methods for block codes, of those that can be applied to linear and nonlinear coding, there are not many with low levels of computation that provide high levels of performance. In this paper, a method is proposed that reduces computation requirements while maintaining performance close to that of maximum likelihood decoding by a decision-making procedure in which a candidate codeword table is referenced by performing Euclidean distance comparisons on the received signal's hard decision binary sequence. The computation requirements and the block error rate performance are investigated through computer simulation to demonstrate the effectiveness of the proposed method in nonlinear beta codes in additive Gaussian noise channels and fading channels. These results show that the block error rate performance of the proposed method in the additive Gaussian noise channel is about the same as the performance of the Chase II algorithm and is only slightly inferior to that of maximum likelihood decoding. Concerning the amount of computations, it is possible to reduce the complexity down to about 1% of that required by maximum likelihood decoding, and also the complexity can be reduced below that of the Chase II algorithm. On the other hand, in the fading channel, the block error rate performance of the proposed method, when compared to maximum likelihood decoding performance, reveals a decrease in E-b/N-0 of about 1 dB, and it is seen to have good performance compared to the Chase II algorithm. Also, application toward quasi-cyclic coding/4-ary ASK coding using a candidate word table with respect to a 4-ary sequence applied with BCH coding is investigated, and superior results are obtained. (C) 1997 Scripta Technica, Inc.
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