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We consider the problem of designing a bandwidth-efficient, power-limited digital communication system for transmitting information from a source with known statistics over a noisy waveform channel. Each output vector of the source is encoded by a block encoder to one of a finite number of signals in a modulation signal set. The received waveform is processed in the receiver by an estimation-based decoder. The goal is to design an encoder, decoder and modulation signal set so as to minimize the mean squared-error (MSE) between the source vector and its estimate in the receiver. For highly noisy gaussian channels we justify restricting the estimator to the class of linear estimators. With this restriction, we derive necessary conditions for optimality of the encoder, decoder and the signal set and develop a convergent algorithm for solving these necessary conditions. We prove that the MSE of the digital system designed here is bounded from below by the MSE of an analog modulation system. Performance results for the digital system and signal constellation designs are presented for first- order Gauss-Markov sources and a white Gaussian channel. Comparisons are made against a standard vector quantizer (VQ)- based system, the bounding analog modulation system and the optimum performance theoretically attainable. The results indicate that for a correlated source, a sufficiently noisy channel and specific source block sizes and bandwidths, the digital system performance coincides with the optimum performance theoretically attainable. Further, significant performance improvements over the standard VQ-based system are demonstrated when the channel is noisy. Situations in which the linearity assumption results in poor performance are also identified.

The two-dimensional block transform coding scheme based on the discrete cosine transform has been studied extensively for image coding applications. While this scheme has proven to be efficient in the absence of channel errors, its performance degrades rapidly over noisy channels. In this paper we present a method for the joint source-channel coding optimization of a scheme based on the 2-D block cosine transform when the output of the encoder is to be transmitted via a memoryless binary symmetric channel. Our approach involves an iterative algorithm for the design of the quantizers (in the presence of channel errors) used for encoding the transform coefficients. This algorithm produces a set of locally optimum (in the mean squared- error sense) quantizers and the corresponding binary code assignment for the assumed transform coefficient statistics. To determine the optimum bit assignment among the transform coefficients, we have used an algorithm based on the steepest descent method, which under certain covexity conditions on the performance of the channel-optimized quantizers, yields the optimal bit allocation. Comprehensive simulation results for the performance of this locally optimum system over noisy channels have been obtained and appropriate comparisons against a reference system designed for no channel errors have been rendered. It is shown that substantial performance improvements can be obtained by using this scheme. Furthermore, theoretically predicted results for an assumed 2-D image model are provided.

In this report we provide a complete documentation of the software developed in the Communications and Signal Processing Laboratory (CSPL) during the period July 1985 - March l986. Utility programs and subroutines that are developed for a user- friendly image and speech processing environment are described. Additional programs for data compression for image and speech type signals are included. Also, programs for the zero-memory and block transform quantization in the presence of channel noise are described. Finally, several routines for simulating the performance of image compression algorithms are included.

The Railway route through south-west part of India (Konkan Railway) is passing through a hilly terrain. The route is developed by cutting the mountains in slopes and construction of tunnels. Many slopes along this route are very deep and steep. The region is characterized by lateritic soil. A heavy monsoon initiates some of the deep slope failures resulting in large magnitude of loss – both in money and life. The initial failure of one of the slope at Chainage 344/900 Km was stabilized by Gabion walls. West side of the Soil cutting was about 100 m long and a lateritic hilly slope steeply rises to 20 m above the track level at the collapse location. Initially the cutting line was 15m away from external track edge. However, after the heavy monsoon in June 2000, the soil slope collapses causing the lateral movement of the gabion wall and lateral shifting of the nearby railway track. The investigation was carried out to study the failure. The scheme of combination of conventional Soil Nails and Micropiles in addition to Gabion wall was proposed. The scheme was executed in Jan 2001 to May 2001. Load Tests were performed on Micropiles and Nails to verify the design. The slope is successfully stable for last 10 years.