Naveen Singla

Iterative detection and decoding for separable two-dimensional intersymbol interference

We introduce two detection methods for uncoded two-dimensional (2-D) intersymbol interference (ISI) channels. The detection methods are suitable for a special case of 2-D ISI channels where the channel response is separable. In this case, the 2-D ISI is treated as the concatenation of two one-dimensional ISI channels. The first method uses equalization to reduce the ISI in one of the two dimensions followed by use of a maximum a posteriori (MAP) detector for the ISI in the other dimension. The second method employs modified MAP algorithms to reduce the ISI in each dimension. The implementation complexity of the two methods grows exponentially in the ISI length in either the row or column dimension. We develop two iterative decoding schemes based on these detection methods and low-density parity-check codes as error correction codes. Simulation results show that the bit-error-rate performance loss caused by the 2-D ISI for the separable channel response considered is less than 1 dB over a channel without ISI. This motivates equalizing a general 2-D ISI channel response to a nearby separable matrix.

Iterative decoding and equalization for 2-D recording channels

Summary form only given. As conventional magnetic recording challenges physical limits, we are motivated to consider 2-dimensional (2-D) data storage techniques. Further motivation is provided by the fact that data in 2-D recording may be arranged in bigger sectors than in 1-D and error correcting codes (ECC) such as low density parity check codes (LDPCC) get arbitrarily close to capacity for large enough block lengths. In this paper we consider the use of LDPCC as an ECC in conjunction with equalization methods, iterative and otherwise, for a 2-D recording medium with 2-D ISI. Equalization methods for 2-D recording are discussed as is iterative detection.

Laser Doppler Vibrometry Measures of Physiological Function: Evaluation of Biometric Capabilities

A novel approach for remotely sensing mechanical cardiovascular activity for use as a biometric marker is proposed. Laser Doppler Vibrometry (LDV) is employed to sense vibrations on the surface of the skin above the carotid artery related to arterial wall movements associated with the central blood pressure pulse. Carotid LDV signals are recorded using noncontact methods and the resulting unobtrusiveness is a major benefit of this technique. Several recognition methods are proposed that use the temporal and/or spectral information in the signal to assess biometric performance both on an intrasession basis, and on an intersession basis where LDV measurements were acquired from the same subjects after delays ranging from one week to six months. A waveform decomposition method that utilizes principal component analysis is used to model the signal in the time domain. Authentication testing for this approach produces an equal-error rate of 0.5% for intrasession testing. However, performance degrades substantially for intersession testing, requiring a more robust approach to modeling. Improved performance is obtained using techniques based on time-frequency decomposition, incorporating a method for extracting informative components. Biometric fusion methods including data fusion and information fusion are applied to train models using data from multiple sessions. As currently implemented, this approach yields an intersession equal-error rate of 6.3%.

Joint equalization and decoding for nonlinear two-dimensional intersymbol interference channels

An algorithm that performs joint equalization and decoding for channels with nonlinear two-dimensional intersymbol interference is presented. The algorithm performs sum-product message-passing on a factor graph that represents the underlying system. The two-dimensional optical storage (Two-DOS) technology is an example of a system with nonlinear two-dimensional intersymbol interference. Simulations for the nonlinear channel model of TwoDOS show significant improvement in performance over uncoded performance. Noise tolerance thresholds for the TwoDOS channel computed using density evolution are also presented

Laser Doppler vibrometry measures of physiological function: evaluation of biometric capabilities

A novel approach using mechanical physiological activity as a biometric marker is described. Laser Doppler Vibrometry is used to sense activity in the region of the carotid artery, related to arterial wall movements associated with the central blood pressure pulse. The non-contact basis of the LDV method has several potential benefits in terms of the associated non-intrusiveness. Several methods are proposed that use the temporal and/or spectral information in the signal to assess biometric performance both on an intra-session basis, and on an intersession basis involving testing repeated after delays of 1 week to 6 months. A waveform decomposition method that utilizes principal component analysis is used to model the signal in the time domain. Authentication testing for this approach produces an equal-error rate of 0.5% for intra-session testing. However, performance degrades substantially for inter-session testing, requiring a more robust approach to modeling. Improved performance is obtained using techniques based on time-frequency decomposition, incorporating a method for extracting informative components. Biometric fusion methods including data fusion and information fusion are applied in multi-session data training model. As currently implemented, this approach yields an inter-session equal-error rate of 9%.

Iterative decoding for two-dimensional intersymbol interference channels

We study iterative decoding and equalization for information storage systems that have two-dimensional (2-D) intersymbol interference (ISI) during read-back. Four iterative schemes for 2-D equalization are introduced and evaluated. Two schemes are based on turbo equalization, the third on minimum mean squared error estimation, and the fourth on message passing on the combined graph of the channel ISI and the error correction code.

Decoding for magnetic recording media with overlapping tracks

Increasing recording track density by allowing overlap of adjacent tracks can lead to a substantial increase in storage density for magnetic recording. However, track overlap may cause severe intertrack interference (ITI) and result in loss of performance. Sophisticated signal processing techniques must then be used to recover this loss. We study the use of joint equalization and decoding for magnetic recording with overlapping tracks. We present results for a scheme that uses minimum mean-squared-error (MMSE) equalization in conjunction with error-correction coding using low-density parity-check (LDPC) codes. The recording process is simulated using a micromagnetic model for longitudinal magnetic recording. We use a three-track system to study the track overlap. The outer two tracks are allowed to overlap on the middle track to simulate ITI. Bit-error rate simulations show that the MMSE-LDPC decoding scheme incurs negligible loss when each of the outer tracks overlaps 10% on the middle track. By varying the recording parameters, the tradeoff between storage density and performance is also studied. We show that by a judicious choice of LDPC codes, a recording with track overlap can have better performance than when there is no overlap. Hence, a higher storage density can be obtained without loss in performance.

Minimum mean square error equalization using priors for two-dimensional intersymbol interference

Joint iterative equalization and decoding schemes are proposed for two-dimensional inter-symbol interference channels. Equalization is performed using the minimum mean squared error criterion. Three linear equalizers are proposed. The exact equalizer, a spatially and temporally varying equalizer, has performance similar to schemes based on message-passing and has lower complexity. To save further on computational cost, time-invariant implementations of the exact equalizer are also proposed. Extrinsic information transfer charts are used to analyze the equalizers. A density evolution algorithm using a Gaussian approximation is proposed and used to study the trade-off between computational cost and performance for different decoding schedules.