An upperbound on the zero-error list-coding capacity

Cataloged from PDF version of article.We present an upper bound on the zero-error list-coding capacity of discrete memoryless channels. Using this bound, we show that the list3 capacity of the 4/3 channel is at most 03512 b, improving the best previous bound. The relatien of the bound to earlier similar bouads, in particular, to Korner's graph+ntropy bound, is discussed

On the reliability exponent of the exponential timing channel

Cataloged from PDF version of article.We determine the reliability exponent E(R) of the Anantharam-Verdu exponential server timing channel with service rate p for all rates R between a critical rate R-c = (mu/4) log 2 and the channel capacity C = e(-1)mu. For rates between 0 and R-c, we provide a random-coding lower bound E,(R) and a sphere-packing upper bound E-r(R) on E(R). We also determine that the cutoff rate R-0 for this channel equals mu/4, thus answering a question posed by Sundaresan and Verdu. An interesting aspect of our results is that the lower bound E, (R) for the reliability exponent of the timing channel coincides with Wyner's reliability exponent for the photon-counting channel with no dark current and with peak power constraint mu. Whether the reliability exponents of the two channels are actually equal everywhere remains open. This shows that the exponential server timing channel is at least as reliable as this type of a photon-counting channel for all rates

A hybrid LBG/lattice vector quantizer for high quality image coding

It is well known that a vector quantizer is an efficient coder offering a good trade-off between quantization distortion and bit rate. The performance of a vector quantizer asymptotically approaches the optimum bound with increasing dimensionality. A vector quantized image suffers from the following types of degradations: (1) edge regions in the coded image contain staircase effects, (2) quasi-constant or slowly varying regions suffer from contouring effects, and (3) textured regions lose details and suffer from granular noise. All three of these degradations are due to the finite size of the code book, the distortion measures used in the design, and due to the finite training procedure involved in the construction of the code book. In this paper, we present an adaptive technique which attempts to ameliorate the edge distortion and contouring effects

Systematic polar coding

Cataloged from PDF version of article.Polar codes were originally introduced as a class of non-systematic linear block codes. This paper gives encoding and decoding methods for systematic polar coding that preserve the low-complexity nature of non-systematic polar coding while guaranteeing the same frame error rate. Simulation results are given to show that systematic polar coding offers significant advantages in terms of bit error rate performance

Optimal Randomization of Signal Constellations on Downlink of a Multiuser DS-CDMA System

Cataloged from PDF version of article.In this study, the jointly optimal power control with signal constellation randomization is proposed for the downlink of a multiuser communications system. Unlike a conventional system in which a fixed signal constellation is employed for all the bits of a user (for given channel conditions and noise power), power control with signal constellation randomization involves randomization/time- sharing among different signal constellations for each user. A formulation is obtained for the problem of optimal power control with signal constellation randomization, and it is shown that the optimal solution can be represented by a randomization among (K+1) or fewer distinct signal constellations for each user, where K denotes the number of users. In addition to the original nonconvex formulation, an approximate solution based on convex relaxation is derived. Then, detailed performance analysis is presented when the receivers employ symmetric signaling and sign detectors. Specifically, the maximum asymptotical improvement ratio is shown to be equal to the number of users, and the conditions under which the maximum and minimum asymptotical improvement ratios are achieved are derived. Numerical examples are presented to investigate the theoretical results, and to illustrate performance improvements achieved via the proposed approach. © 2002-2012 IEEE

AM/FM signal estimation with micro-segmentation and polynomial fit

Cataloged from PDF version of article.Amplitude and phase estimation of AM/FM signals with parametric polynomial representation require the polynomial orders for phase and amplitude to be known. But in reality, they are not known and have to be estimated. A well-known method for estimation is the higher-order ambiguity function (HAF) or its variants. But the HAF method has several reported drawbacks such as error propagation and slowly varying or even constant amplitude assumption. Especially for the long duration time-varying signals like AM/FM signals, which require high orders for the phase and amplitude, computational load is very heavy due to nonlinear optimization involving many variables. This paper utilizes a micro-segmentation approach where the length of segment is selected such that the amplitude and instantaneous frequency (IF) is constant over the segment. With this selection first, the amplitude and phase estimates for each micro-segment are obtained optimally in the LS sense, and then, these estimates are concatenated to obtain the overall amplitude and phase estimates. The initial estimates are not optimal but sufficiently close to the optimal solution for subsequent processing. Therefore, by using the initial estimates, the overall polynomial orders for the amplitude and phase are estimated. Using estimated orders, the initial amplitude and phase functions are fitted to the polynomials to obtain the final signal. The method does not use any multivariable nonlinear optimization and is efficient in the sense that the MSE performance is close enough to the Cramer–Rao bound. Simulation examples are presented

Rate-distortion optimization for stereoscopic video streaming with unequal error protection

We consider an error-resilient stereoscopic streaming system that uses an H.264-based multiview video codec and a rateless Raptor code for recovery from packet losses. One aim of the present work is to suggest a heuristic methodology for modeling the end-to-end rate-distortion (RD) characteristic of such a system. Another aim is to show how to make use of such a model to optimally select the parameters of the video codec and the Raptor code to minimize the overall distortion. Specifically, the proposed system models the RD curve of video encoder and performance of channel codec to jointly derive the optimal encoder bit rates and unequal error protection (UEP) rates specific to the layered stereoscopic video streaming. We define analytical RD curve modeling for each layer that includes the interdependency of these layers. A heuristic analytical model of the performance of Raptor codes is also defined. Furthermore, the distortion on the stereoscopic video quality caused by packet losses is estimated. Finally, analytical models and estimated single-packet loss distortions are used to minimize the end-to-end distortion and to obtain optimal encoder bit rates and UEP rates. The simulation results clearly demonstrate the significant quality gain against the nonoptimized schemes

Channel polarization: A method for constructing capacity-achieving codes

A method is proposed, called channel polarization, to construct code sequences that achieve the symmetric capacity I(W) of any given binary-input discrete memoryless channel (B-DMC) W. The symmetric capacity I(W) is the highest rate achievable subject to using the input letters of the channel equiprobably and equals the capacity C(W) if the channel has certain symmetry properties. Channel polarization refers to the fact that it is possible to synthesize, out of N independent copies of a given B-DMC W, a different set of N binary-input channels such that the capacities of the latter set, except for a negligible fraction of them, are either near 1 or near 0. This second set of N channels are well-conditioned for channel coding: one need only send data at full rate through channels with capacity near 1 and at 0 rate through the others. The main coding theorem about polar coding states that, given any B-DMC W with I(W) > 0 and any fixed 0 < δ < I(W), there exist finite constants n1 (W, δ) and c(W, δ) such that for all n ≥ n1, there exist polar codes with block length N = 2n, rate R > I(W)-δ, and probability of block decoding error Pe ≤ cN-1/4. The codes with this performance can be encoded and decoded within complexity O(N log N). © 2008 IEEE

An upper bound on the rate of information transfer by Grover's oracle

Grover discovered a quantum algorithm for identifying a target element in an unstructured search universe of N items in approximately π / 4 sqrt(N) search using a classical oracle, the search complexity is of order N / 2 queries since on average half of the items must be searched. In work preceding Grover's, Bennett et al. had shown that no quantum algorithm can solve the search problem in fewer than O (sqrt(N)) algorithm has optimal order of complexity. Here, we present an information-theoretic analysis of Grover's algorithm and show that the square-root speed-up by Grover's algorithm is the best possible by any algorithm using the same quantum oracle. © 2005

An Implementation of Elias Coding for Input-Restricted Channels

An implementation of Elias coding for input-restricted channels is presented and analyzed. This is a variable-to-fixed length coding method that uses finite-precision arithmetic and can work at rates arbitrarily close to channel capacity as the precision is increased. The method offers a favorable tradeoff between complexity and coding efficiency. For example, in experiments with the 12, 7] runlength constrained channel, a coding efficiency of 0.9977 is observed, which is significantly better than what is achievable by other known methods of comparable complexity. © 1990 IEE