In this contribution, we propose a novel distributed Source-coding, Channel-coding and Modulation (DSCM) scheme for cooperative communications. The proposed DSCM scheme is designed for ensuring the decoding convergenc...
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ISBN:
(纸本)9781424435746
In this contribution, we propose a novel distributed Source-coding, Channel-coding and Modulation (DSCM) scheme for cooperative communications. The proposed DSCM scheme is designed for ensuring the decoding convergence of its constituent component codes, namely, the Variable Length Code (VLC) and two Coded Modulation (CM) schemes. The source node encodes the source symbols with the aid of a serially-concatenated VLC and a Turbo Trellis Coded Modulation (TTCM) scheme. The TTCM-VLC encoded symbols are transmitted to both a relay node and to the destination node during the first transmission period. The relay node employs a powerful iterative TTCM-VLC decoder for estimating the VLC-encoded bit sequence. This decoded bit sequence is then re-encoded with the aid of a simple Trellis Coded Modulation (TCM) scheme before it is transmitted to the destination node. At the destination node, a novel four-component iterative decoding arrangement is invoked for recovering the original source symbols. It is shown that the DSCM scheme significantly outperforms the TTCM-VLC benchmarker scheme dispensing with relaying. The proposed power-and bandwidth-efficient DSCM scheme is an ideal candidate for next-generation mobile multimedia systems.
In this paper, we propose a distributed rateless coding (DRC) scheme for a two-user cooperative system. In DRC, the overall transmission is divided into two phases, a broadcast phase and a cooperation phase. In the br...
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ISBN:
(纸本)9781467325790
In this paper, we propose a distributed rateless coding (DRC) scheme for a two-user cooperative system. In DRC, the overall transmission is divided into two phases, a broadcast phase and a cooperation phase. In the broadcast phase, each user keeps transmitting its rateless coded symbols to the other user and the destination until its message has been successfully decoded by the destination or the other user. In the cooperation phase, each user encodes both users' messages by using a rateless code and transmits them to the destination. A linear programming optimization problem is then formulated to find the optimal degree distribution for the proposed distributed rateless code. The performance of the proposed code is analyzed and validated by simulations.
Efficient coding of speech and audio in a distributed system requires that quantization errors across nodes are uncorrelated. Yet, with conventional methods at low bitrates, quantization levels become increasingly spa...
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Efficient coding of speech and audio in a distributed system requires that quantization errors across nodes are uncorrelated. Yet, with conventional methods at low bitrates, quantization levels become increasingly sparse, which does not correspond to the distribution of the input signal and, importantly, also reduces coding efficiency in a distributed system. We have recently proposed a distributed speech and audio codec design, which applies quantization in a randomized domain such that quantization errors are randomly rotated in the output domain. Similar to dithering, this ensures that quantization errors across nodes are uncorrelated and coding efficiency is retained. In this paper, we improve this approach by proposing faster randomization methods, with a computational complexity of O(N log N). The presented experiments demonstrate that the proposed randomizations yield uncorrelated signals, that perceptual quality is competitive, and that the complexity of the proposed methods is feasible for practical applications.
In this paper, we propose a power-efficient distributed binary self-concatenated coding scheme using iterative decoding (DSECCC-ID) for cooperative communications. The DSECCC-ID scheme is designed with the aid of bina...
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In this paper, we propose a power-efficient distributed binary self-concatenated coding scheme using iterative decoding (DSECCC-ID) for cooperative communications. The DSECCC-ID scheme is designed with the aid of binary extrinsic information transfer (EXIT) charts. The source node transmits self-concatenated convolutional coded (SECCC) symbols to both the relay and destination nodes during the first transmission period. The relay performs SECCC-ID decoding, where it may or may not encounter decoding errors. It then reencodes the information bits using a recursive systematic convolutional (RSC) code during the second transmission period. The resultant symbols transmitted from the source and relay nodes can be viewed as the coded symbols of a three-component parallel concatenated encoder. At the destination node, three-component DSECCC-ID decoding is performed. The EXIT chart gives us an insight into operation of the distributed coding scheme, which enables us to significantly reduce the transmit power by about 3.3 dB in signal-to-noise ratio (SNR) terms, as compared with a noncooperative SECCC-ID scheme at a bit error rate (BER) of 10(-5). Finally, the proposed system is capable of performing within about 1.5 dB from the two-hop relay-aided network's capacity at a BER of 10(-5), even if there may be decoding errors at the relay.
Modern distributed storage systems usually store new data in replicas, and later code these data into erasure coded blocks when they get cold. This letter studies optimal bandwidth consumption problem for this replica...
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Modern distributed storage systems usually store new data in replicas, and later code these data into erasure coded blocks when they get cold. This letter studies optimal bandwidth consumption problem for this replica to erasure coded blocks (R2E) coding process, and proposes schemes of R2E_singleTree and R2E_multiTree based on problem observations. Theoretical analysis and evaluation are conducted for these two schemes.
In distributed computing, a number of available helper nodes assist in completing a task for the master node. In such setups, the failure or straggling of even a single helper node can significantly increase the proce...
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In distributed computing, a number of available helper nodes assist in completing a task for the master node. In such setups, the failure or straggling of even a single helper node can significantly increase the processing time. Therefore, coded distributed computing has been the subject of many recent studies. A problem that arises in some setups is that the master's decoding complexity may exceed the complexity of self-computation, rending distributed computing useless. One such case is distributed large-scale FFT, where many helper nodes are required. In this work, we propose a novel distributed coded FFT, where the master's load is significantly lower than the existing work. The gain is obtained by (1) using a novel distributed FFT structure which allows for reliable distributed coding at the Shuffle stage, and (2) using Raptor codes which enjoy a linear complexity at the cost of a small number of extra helper nodes. Numerical results are provided to support the benefits of our proposed solution and to optimize design parameters.
This paper outlines a proposition of a framework optimizing the communication scheme from the physical part of the transmitters to the data gathered at the receiver in a wireless sensor network. We propose a coding sc...
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ISBN:
(纸本)9783319679105;9783319679099
This paper outlines a proposition of a framework optimizing the communication scheme from the physical part of the transmitters to the data gathered at the receiver in a wireless sensor network. We propose a coding scheme able to take into account the correlation between measurements obtained by the sensors. This scheme consists of joint distributed source encoding and linear network coding. Several coding strategies are compared. (1) linear source coding, based on the low density generator matrix (LDGM) codes, where the compression process is performed by every sensor independently (2) distributed source coding, where the correlation between sources is taken into account, without cooperation between sensors. The compression ratios costs are evaluated analytically for each strategy, with respect to the communication costs between the nodes of the network. The results show a significant improvement in terms of compression rate and distortion compared to linear source encoding.
Nowadays the need for fast and reliable communication is increasing, which leads us to look for new ways to enhance channel coding. In this paper, we will study the case of a distributed coding between two users that ...
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ISBN:
(纸本)9781467380966
Nowadays the need for fast and reliable communication is increasing, which leads us to look for new ways to enhance channel coding. In this paper, we will study the case of a distributed coding between two users that aim to transmit data to a common destination, where each user transmits a partial redundancy to the destination, and relies on the second user for the remaining. The purpose of distributing the redundancy creation and transmission, is to benefit from each user channel quality for a more accurate decoding. In the context of our analysis, we will use a 1/2 rate convolutional code with between users and a distributed Turbo code for transmission to the destination. However, this study will aim to highlight the different key factors, as well as the advantage of choosing a distributed encoding.
A low complexity distributed coding scheme is proposed for communications over Rayleigh fading channels. Convolutional coding (CC) assisted Differential Phase-Shift Keying (DPSK) modulation is employed at the source n...
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ISBN:
(纸本)9781424425198
A low complexity distributed coding scheme is proposed for communications over Rayleigh fading channels. Convolutional coding (CC) assisted Differential Phase-Shift Keying (DPSK) modulation is employed at the source node for conveying the source signals to two relay nodes as well as to the destination node during the first transmission period. Iterative detection exchanging extrinsic information between the DPSK demapper and CC decoder is carried out at each relay node in order to recover the source signals. Then, the CC-encoded bits are re-encoded by the two relays to generate Differential Space-Time Block coding (DSTBC) symbols for transmission to the destination node during the second transmission period. At the destination node, iterative decoding exchanging extrinsic information is invoked between the DPSK demapper and the concatenated CC-DSTBC decoder, where the later is viewed as a single amalgamated decoder. The relay and destination nodes do not have to estimate the channel's fading coefficients due to the employment of DPSK and DSTBC schemes. Our design requires only two decoding iterations between the DPSK and CC decoders at each relay in order to further reduce the complexity of the relay nodes. Our distributed coding scheme assisted by two low-complexity relay nodes outperforms the non-cooperative benchmarker scheme by about 8 dBs, when aiming for a bit error ratio of 10(-5).
A new context-sensitive neural network, called an EXIN (excitatory + inhibitory) network, is described. EXIN networks self-organize in complex perceptual environments, in the presence of multiple superimposed patterns...
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A new context-sensitive neural network, called an EXIN (excitatory + inhibitory) network, is described. EXIN networks self-organize in complex perceptual environments, in the presence of multiple superimposed patterns, multiple scales, and uncertainty, The networks use a new inhibitory learning rule, in addition to an excitatory learning rule, to allow superposition of multiple simultaneous neural activations ( multiple winners), under strictly regulated circumstances, instead of forcing winner-take-all pattern classifications. The multiple activations represent uncertainty or multiplicity in perception and pattern recognition. Perceptual scission (breaking of linkages) between independent category groupings thus arises and allows effective global context-sensitive segmentation, constraint satisfaction and exclusive credit attribution. A Weber Law neuron growth rule lets the network learn and classify input patterns despite variations in their spatial scale, Applications of the new techniques include segmentation of superimposed auditory or biosonar signals, segmentation of visual regions, and representation of visual transparency.
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