74 research outputs found
On the Queueing Behavior of Random Codes over a Gilbert-Elliot Erasure Channel
This paper considers the queueing performance of a system that transmits
coded data over a time-varying erasure channel. In our model, the queue length
and channel state together form a Markov chain that depends on the system
parameters. This gives a framework that allows a rigorous analysis of the queue
as a function of the code rate. Most prior work in this area either ignores
block-length (e.g., fluid models) or assumes error-free communication using
finite codes. This work enables one to determine when such assumptions provide
good, or bad, approximations of true behavior. Moreover, it offers a new
approach to optimize parameters and evaluate performance. This can be valuable
for delay-sensitive systems that employ short block lengths.Comment: 5 pages, 4 figures, conferenc
Forward error correction for molecular communications
Communication between nanoscale devices is an area of considerable importance as it is essential that future devices be able to form nanonetworks and realise their full potential. Molecular communication is a method based on diffusion, inspired by biological systems and useful over transmission distances in the nm to μm range. The propagation of messenger molecules via diffusion implies that there is thus a probability that they can either arrive outside of their required time slot or ultimately, not arrive at all. Therefore, in this paper, the use of a error correcting codes is considered as a method of enhancing the performance of future nanonetworks. Using a simple block code, it is shown that it is possible to deliver a coding gain of ∼1.7 dB at transmission distances of . Nevertheless, energy is required for the coding and decoding and as such this paper also considers the code in this context. It is shown that these simple error correction codes can deliver a benefit in terms of energy usage for transmission distances of upwards of for receivers of a radius
Copyright Protection of Color Imaging Using Robust-Encoded Watermarking
In this paper we present a robust-encoded watermarking method applied to color images for copyright protection, which presents robustness against several geometric and signal processing distortions. Trade-off between payload, robustness and imperceptibility is a very important aspect which has to be considered when a watermark algorithm is designed. In our proposed scheme, previously to be embedded into the image, the watermark signal is encoded using a convolutional encoder, which can perform forward error correction achieving better robustness performance. Then, the embedding process is carried out through the discrete cosine transform domain (DCT) of an image using the image normalization technique to accomplish robustness against geometric and signal processing distortions. The embedded watermark coded bits are extracted and decoded using the Viterbi algorithm. In order to determine the presence or absence of the watermark into the image we compute the bit error rate (BER) between the recovered and the original watermark data sequence. The quality of the watermarked image is measured using the well-known indices: Peak Signal to Noise Ratio (PSNR), Visual Information Fidelity (VIF) and Structural Similarity Index (SSIM). The color difference between the watermarked and original images is obtained by using the Normalized Color Difference (NCD) measure. The experimental results show that the proposed method provides good performance in terms of imperceptibility and robustness. The comparison among the proposed and previously reported methods based on different techniques is also provided
A New Chase-type Soft-decision Decoding Algorithm for Reed-Solomon Codes
This paper addresses three relevant issues arising in designing Chase-type
algorithms for Reed-Solomon codes: 1) how to choose the set of testing
patterns; 2) given the set of testing patterns, what is the optimal testing
order in the sense that the most-likely codeword is expected to appear earlier;
and 3) how to identify the most-likely codeword. A new Chase-type soft-decision
decoding algorithm is proposed, referred to as tree-based Chase-type algorithm.
The proposed algorithm takes the set of all vectors as the set of testing
patterns, and hence definitely delivers the most-likely codeword provided that
the computational resources are allowed. All the testing patterns are arranged
in an ordered rooted tree according to the likelihood bounds of the possibly
generated codewords. While performing the algorithm, the ordered rooted tree is
constructed progressively by adding at most two leafs at each trial. The
ordered tree naturally induces a sufficient condition for the most-likely
codeword. That is, whenever the proposed algorithm exits before a preset
maximum number of trials is reached, the output codeword must be the
most-likely one. When the proposed algorithm is combined with Guruswami-Sudan
(GS) algorithm, each trial can be implement in an extremely simple way by
removing one old point and interpolating one new point. Simulation results show
that the proposed algorithm performs better than the recently proposed
Chase-type algorithm by Bellorado et al with less trials given that the maximum
number of trials is the same. Also proposed are simulation-based performance
bounds on the MLD algorithm, which are utilized to illustrate the
near-optimality of the proposed algorithm in the high SNR region. In addition,
the proposed algorithm admits decoding with a likelihood threshold, that
searches the most-likely codeword within an Euclidean sphere rather than a
Hamming sphere
- …