• Journal of Communications and Networks
• /
• v.10 no.1
• /
• pp.44-54
• /
• 2008

In this paper, an iterative multiple symbol differential detection for turbo coded differential unitary space-time modulation using a posteriori probability (APP) demodulator is investigated. Two approaches of different complexity based on linear prediction are presented to utilize the temporal correlation of fading for the APP demodulator. The first approach intends to take account of all possible previous symbols for linear prediction, thus requiring an increase of the number of trellis states of the APP demodulator. In contrast, the second approach applies Viterbi algorithm to assist the APP demodulator in estimating the previous symbols, hence allowing much reduced decoding complexity. These two approaches are found to provide a trade-off between performance and complexity. It is shown through simulation that both approaches can offer significant BER performance improvement over the conventional differential detection under both correlated slow and fast Rayleigh flat-fading channels. In addition, when comparing the first approach to a modified bit-interleaved turbo coded differential space-time modulation counterpart of comparable decoding complexity, the proposed decoding structure can offer performance gain over 3 dB at BER of $10^{-5}$.

• ETRI Journal
• /
• v.33 no.2
• /
• pp.155-162
• /
• 2011

The scalable extension of the H.264/AVC video coding standard (SVC) demonstrates superb adaptability in video communications. Joint source and channel coding (JSCC) has been shown to be very effective for such scalable video consisting of parts of different significance. In this paper, a new JSCC scheme for SVC transmission over packet loss channels is proposed which performs two-dimensional optimization on the quality layers of each frame in a rate-distortion (R-D) sense as well as on the temporal hierarchical structure of frames under dependency constraints. To compute the end-to-end R-D points of a frame, a novel reduced trellis algorithm is developed with a significant reduction of complexity from the existing Viterbi-based algorithm. The R-D points of frames are sorted under the hierarchical dependency constraints and optimal JSCC solution is obtained in terms of the best R-D performance. Experimental results show that our scheme outperforms the existing scheme of [13] with average quality gains of 0.26 dB and 0.22 dB for progressive and non-progressive modes respectively.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2018.11a
• /
• pp.11-14
• /
• 2018

The aim of this study is to rectify the misclassified image features and enhance the performance of image classification tasks by incorporating a channel- coding technique, widely used in telecommunication. Specifically, the proposed algorithm employs the error - correcting mechanism of convolutional coding combined with the convolutional neural networks (CNNs) that are the state - of- the- arts image classifier s. We develop an encoder and a decoder to employ the error - correcting capability of the convolutional coding. In the encoder, the label values of the image data are converted to convolutional codes that are used as target outputs of the CNN, and the network is trained to minimize the Euclidean distance between the target output codes and the actual output codes. In order to correct misclassified features, the outputs of the network are decoded through the trellis structure with Viterbi algorithm before determining the final prediction. This paper demonstrates that the proposed architecture advances the performance of the neural networks compared to the traditional one- hot encoding method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.29 no.4
• /
• pp.299-307
• /
• 2018

Considering a nonlinear high power amplifier(HPA) and a predistorter, we have designed a four-dimensional 8-ary phase shift keying trellis-coded modulation(4D-8PSK-TCM) system, which is recommended for X-band satellite communications. Subsequently, we have evaluated and analyzed the spectrum, constellation characteristics, and BER performance of the system. In satellite communications, owing to the limited power, nonlinear characteristics that determine the operating point of the HPA must be analyzed because the HPA consumes high power. We herein report the design of the 4D-8PSK-TCM system, with efficiencies of 2 and 2.25 bits/channel-symbol. The simulation results confirmed that a 0.35 roll-off value is effective, considering the low peak-to-average power ratio(PAPR) characteristic and the narrow occupation bandwidth of the spectrum. It also confirmed that approximately 15~20 dB of output backoff(OBO) value is required at the HPA when the predistorter is not used, and approximately 1 dB of the OBO value is required when the predistorter is used.

• Journal of Communications and Networks
• /
• v.5 no.2
• /
• pp.157-166
• /
• 2003

This paper deals with the problem of channel identification for Single Input Multiple Output (SIMO) slow fading channels using clustering algorithms. Due to the intrinsic memory of the discrete-time model of the channel, over short observation periods, the received data vectors of the SIMO model are spread in clusters because of the AWGN noise. Each cluster is practically centered around the ideal channel output labels without noise and the noisy received vectors are distributed according to a multivariate Gaussian distribution. Starting from the Markov SIMO channel model, simultaneous maximum ikelihood estimation of the input vector and the channel coefficients reduce to one of obtaining the values of this pair that minimizes the sum of the Euclidean norms between the received and the estimated output vectors. Viterbi algorithm can be used for this purpose provided the trellis diagram of the Markov model can be labeled with the noiseless channel outputs. The problem of identification of the ideal channel outputs, which is the focus of this paper, is then equivalent to designing a Vector Quantizer (VQ) from a training set corresponding to the observed noisy channel outputs. The Linde-Buzo-Gray (LBG)-type clustering algorithms [1] could be used to obtain the noiseless channel output labels from the noisy received vectors. One problem with the use of such algorithms for blind time-varying channel identification is the codebook initialization. This paper looks at two critical issues with regards to the use of VQ for channel identification. The first has to deal with the applicability of this technique in general; we present theoretical results for the conditions under which the technique may be applicable. The second aims at overcoming the codebook initialization problem by proposing a novel approach which attempts to make the first phase of the channel estimation faster than the classical codebook initialization methods. Sample simulation results are provided confirming the effectiveness of the proposed initialization technique.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.27 no.3A
• /
• pp.188-195
• /
• 2002

The M-algorithm for decoding convolutional codes can significantly reduce the complexity of the Viterbi algorithm by tracking a fixed number of survivor paths in each level of the decoding trellis. It is an easily-implementable algorithm suited for real-time processing of high-speed data. The algorithm, however, generates a sequence of catastrophic errors when the correct path is not included in the set of survivor paths. In this paper, the performance of the M-algorithm obtained from using various decoding complexity levels, frame lengths, and code constraint lengths is presented. The performance gain is quantified when the algorithm is used in conjunction with codes of increased constraint length. In particular, it is demonstrated the gain from the increased code free distance overcompensates the loss from the correct path being excluded from the survivors, when the frame length is short to moderate. Using 64 survivor paths, the signal-to-noise ratio gain obtained by increasing the constraint length from K=7 to K=9, 11, 15 is respectively 0.6, 0.75, and 08dB, when the frame of length L=100 has the frame error rate of 0.01%.