Anil Kumar Goteti

QIM watermarking games

Quantization Index Modulation (QIM) methods are widely used for blind data embedding and watermarking. Given a QIM watermarking code, we ask what is the attackers noise distribution that maximizes probability of error of the detector. For memoryless attacks, the problem is reduced to a convex programming problem. Next, we derive QIM code parameters that are minmax optimal.

Optimal sparse-QIM codes for zero-rate blind watermarking

The problem of blind watermarking of an arbitrary host signal in /spl Ropf//sup n/ under squared-error distortion constraints and Gaussian attacks is considered in this paper. While distortion-compensated lattice quantization index modulation (QIM), using nearly spherical Voronoi cells, is known to be asymptotically capacity-achieving in this setup, our results suggest that such schemes are suboptimal in terms of error probability when the number of possible messages is subexponential in n. Our conjecture is substantiated by examples involving low-dimensional lattices and is related to the simplex conjecture in coding theory.

First Order Adaptive IIR Filter for CQI Prediction in HSDPA

In this work, we consider channel quality indicator (CQI) prediction for High Speed Downlink Packet Access (HSDPA). In HSDPA systems, there is a delay of about 3 subframe associated with the application of CQI feedback. Traditional FIR filter based predictors such as Least-Mean-Squares (LMS) and Recursive-Least-Squares (RLS) typically come with high computational complexity. We consider a first order adaptive IIR alternative with substantially lower complexity while attaining the same level of accuracy. By minimizing the mean squared error (MSE), we derive an exact gradient descent algorithm as well as two pseudolinear regression algorithms. The convergence rates and the convergence conditions are then established. Simulation results show that the proposed adaptive IIR filters combat both feedback delay as well as estimation error and provide up to 25\% HSDPA throughput improvement.

Block QIM watermarking games

While binning is a fundamental approach to blind data embedding and watermarking, an attacker may devise various strategies to reduce the effectiveness of practical binning schemes. The problem analyzed in this paper is design of worst-case noise distributions against L-dimensional lattice quantization index modulation (QIM) watermarking codes. The cost functions considered are 1) probability of error of the maximum-likelihood decoder, and 2) the more tractable Bhattacharyya upper bound on error probability, which is tight at low embedding rates. Both problems are addressed under the following constraints on the attackers strategy: the noise is independent of the marked signal, blockwise memoryless with block length L, and may not exceed a specified quadratic-distortion level. The embedders quadratic distortion is limited as well. Three strategies are considered for the embedder: optimization of the lattice inflation parameter (also known as Costa parameter), dithering, and randomized lattice rotation. Critical in this analysis are the symmetry properties of QIM nested lattices and convexity properties of probability of error and related functionals of the noise distribution. We derive the minmax optimal embedding and attack strategies and obtain explicit solutions as well as numerical solutions for the worst-case noise. The role of the attackers memory is investigated; in particular, we demonstrate the remarkable effectiveness of impulsive-noise attacks as L increases. The formulation proposed in this paper is also used to evaluate the capacity of lattice QIM under worst-noise conditions

Throughput Optimization in High Speed Downlink Packet Access (HSDPA)

In this paper, we investigate throughput optimization in High Speed Downlink Packet Access (HSDPA). Specifically, we propose offline and online algorithms for adjusting the Channel Quality Indicator (CQI) used by the network to schedule data transmission. In the offline algorithm, a given target BLER is achieved by adjusting CQI based on ACK/NAK history. By sweeping through different target BLERs, we can find the throughput optimal BLER offline. This algorithm could be used not only to optimize throughput but also to enable fair resource allocation among mobile users in HSDPA. In the online algorithm, the CQI offset is adapted using an estimated short term throughput gradient without specifying a target BLER. An adaptive stepsize mechanism is proposed to track temporal variation of the environment. We investigate convergence behavior of both algorithms. Simulation results show that the proposed offline algorithm can achieve the given target BLER with good accuracy. Both algorithms yield up to 30% HSDPA throughput improvement over that with 10% target BLER.

Two private, perceptual data-hiding games

Perceptual watermarking methods are designed to be transparent and robust to attacks. A perceptual model based on just noticeable difference levels introduces amplitude constraints on the watermark and the noise generated by an attacker. Two problems are considered: (1) detection performance for embedding a single bit in n data; (2) Shannon capacity. In both cases, the original host data are known to the receiver. Both problems are formulated as games involving a suitable cost function (Bhattacharyya distance and mutual information, respectively). The watermarker and the attacker design probability distributions in order to maximize and minimize, respectively, the cost function. The optimal distributions are quite different from the uniform distributions that have been previously used in the watermarking literature.

Minmax strategies for QIM watermarking subject to attacks with memory

This paper examines the role of attackers memory in quantization index modulation (QIM) watermarking systems. First we derive the attackers noise distribution that maximizes probability of error of the detector. Next, we derive QIM code parameters that are minmax optimal. The minmax optimal embedding strategy involves randomized lattice rotations, and the corresponding worst noise distributions are isotropic.