Noah Jacobsen

Robust image-adaptive data hiding using erasure and error correction

Information-theoretic analyses for data hiding prescribe embedding the hidden data in the choice of quantizer for the host data. We propose practical realizations of this prescription for data hiding in images, with a view to hiding large volumes of data with low perceptual degradation. The hidden data can be recovered reliably under attacks, such as compression and limited amounts of image tampering and image resizing. The three main findings are as follows. 1) In order to limit perceivable distortion while hiding large amounts of data, hiding schemes must use image-adaptive criteria in addition to statistical criteria based on information theory. 2) The use of local criteria to choose where to hide data can potentially cause desynchronization of the encoder and decoder. This synchronization problem is solved by the use of powerful, but simple-to-implement, erasures and errors correcting codes, which also provide robustness against a variety of attacks. 3) For simplicity, scalar quantization-based hiding is employed, even though information-theoretic guidelines prescribe vector quantization-based methods. However, an information-theoretic analysis for an idealized model is provided to show that scalar quantization-based hiding incurs approximately only a 2-dB penalty in terms of resilience to attack.

Design of Rate-Compatible Irregular LDPC Codes Based on Edge Growth and Parity Splitting

This paper considers the design of rate-compatible low-density parity-check (LDPC) codes with optimized degree distributions for their corresponding rates. The proposed design technique is based on extension, where a high-rate base code, or daughter code, is progressively extended to lower and lower rates such that each extension code is compatible with the previously obtained codes. Specifically, two well-known parity matrix construction methodologies, edge growth and parity splitting, are adapted to yield a flexible framework for constructing rate- compatible parity check matrices with a uniform performance characteristic. The design examples provided are based on extrinsic information transfer (EXIT) chart optimizations and demonstrate good performance up to rates as low as 1/5.

High-volume data hiding in images: Introducing perceptual criteria into quantization based embedding

Information-theoretic analyses for data hiding prescribe embedding the hidden data in the choice of quantizer for the host data. In this paper, we consider a suboptimal implementation of this prescription, with a view to hiding high volumes of data in images with low perceptual degradation. Our two main findings are as follows: (a) In order to limit perceptual distortion while hiding large amounts of data, the hiding scheme must use perceptual criteria in addition to information-theoretic guidelines. (b) By focusing on “benign” JPEG compression attacks, we are able to attain very high volumes of embedded data, comparable to information-theoretic capacity estimates for the more malicious Additive White Gaussian Noise (AWGN) attack channel, using relatively simple embedding techniques.

Image adaptive high volume data hiding based on scalar quantization

Information-theoretic analysis for data hiding prescribe embedding the hidden data in the choice of quantizer for the host data. We consider a suboptimal implementation of this prescription, with a view to hiding high volumes of data in images with low perceptual degradation. The three main findings are as follows. (i) Scalar quantization based data hiding schemes incur about 2 dB penalty from the optimal embedding strategy, which involves vector quantization of the host. (ii) In order to limit perceivable distortion while hiding large amounts of data, hiding schemes must use local perceptual criteria in addition to information-theoretic guidelines. (iii) Powerful erasure and error correcting codes provide a flexible framework that allows the data-hider freedom of choice of where to embed without requiring synchronization between encoder and decoder.

Coded noncoherent communication with amplitude/phase modulation: from shannon theory to practical architectures

We develop bandwidth efficient radio transceivers, using amplitude/phase modulations, for frequency non-selective channels whose time variations are typical of outdoor mobile wireless systems. The transceiver is noncoherent, neither requiring pilots for channel estimation and tracking nor assuming prior channel knowledge on the part of the receiver. Serial concatenation of a binary outer channel code with an inner differential modulation code provides a turbo structure that, along with the channel memory, is exploited for joint iterative channel and data estimation. While prior work on noncoherent communication mainly focuses on PSK alphabets, we consider a moderate to high SNR regime in which amplitude/phase constellations are more efficient. First, the complexity of block noncoherent demodulation is reduced to a level that is comparable to coherent receivers. Then, a tool for choosing the constellation and bit-to-symbol mapping is developed by adapting extrinsic information transfer (EXIT) charts for noncoherent demodulation. The recommended constellations differ significantly from standard coherent channel constellations, and from prior recommendations for uncoded noncoherent systems. The analysis shows that standard convolutional codes are nearly optimal when paired with differential amplitude/phase modulation.

Noncoherent eigenbeamforming for a wideband cellular uplink

In this paper, we investigate wideband space-time communication on the uplink of an outdoor cellular system, in which the base station is equipped with N antennas and the mobile has a single antenna. We assume noncoherent reception at the base station, which incurs significantly less overhead than pilot-based estimation of the space-time channel from each mobile to the base station. Noncoherent communication techniques are particularly well suited to outdoor cellular systems for which channel time variations are significant due to mobility at vehicular speeds

Practical cooperative coding for Half-Duplex relay channels

Simple variations on rate-compatible channel codes are shown to achieve cooperative coding gains for the half-duplex relay channel without the complexity of capacity approaching codes. The simulated performance of an optimized irregular low density parity check code is provided.

Code and constellation optimization for efficient noncoherent communication

We consider noncoherent communication techniques with large signal alphabets, where explicit (i.e., pilot symbol based) channel estimates are not required by the receiver and iterative soft information exchange between noncoherent demodulator and channel decoder is employed for approaching Shannon-theoretic limits. Extrinsic Information Transfer (EXIT) functions are used to characterize convergence of the iterative receiver, enabling joint optimization of the inner modulation code constellation and symbol mapping with an outer binary channel code. We find that QAM constellations classically employed over the AWGN channel are inferior to modified constellation shapes based on aligned PSK rings with Gray-like amplitude/phase bit maps. EXIT analysis of turbo noncoherent communication further shows that standard convolutional codes are near optimal in serial concatenation with a unit-rate inner modulation code. The overall system is within 2.4 dB of Shannon capacity for the block fading channel at 1.8 bits/channel use, demonstrating that bandwidth-efficient noncoherent communication systems with reasonable complexity are now within reach.

Towards Shannon-theoretic limits on wireless time-varying channels

We survey our recent results on approaching the performance limits of wireless time-varying channels. In current practice, transceivers for such channels employ a large fraction of training or pilot overhead for channel estimation and tracking, together with coherent reception assuming that the channel estimates are accurate. In this paper, we discuss our progress in developing an alternative noncoherent approach, in which the channel and data are estimated jointly, heavily leveraging iterative decoding techniques.

Noncoherent eigenbeamforming and interference suppression for outdoor OFDM systems

We investigate a new approach to uplink communications in wideband outdoor cellular systems that can take advantage of multiple antennas at the base station in a scalable manner, while eliminating or minimizing overhead for channel estimation. The proposed techniques, which focus on exploiting correlated channels with the use of closely spaced antenna arrays, are applicable to emerging Orthogonal Frequency Division Multiplexing (OFDM) based Wireless Metropolitan Area Network (WMAN) systems, such as those based on the IEEE 802.16/20 standards. Outdoor channels frequently have a small number of dominant spatial modes, which can be learned from overhead-free estimation of the spatial covariance matrix by averaging across subcarriers. We describe an eigenbeamforming receiver which projects the received signal along the dominant spatial modes, yielding a beamforming gain that scales up with the number of receive elements and a diversity level depending on the number of dominant spatial modes. Shannon limits are first computed for block fading approximations to time- and frequency-selective channels. The suboptimal noncoherent diversity-combining receiver is shown to approach these limits, with linear complexity in the number dominant modes. Further, for dealing with spatially non-white interfering signals, adaptive suppression techniques are shown to mitigate strong interference with minimal training overhead.