Papers by Kandarpa Kumar Sarma
Bit Error Rate (BER) performance of the modified structure of a Digital Phase Locked Loop (DPLL) ... more Bit Error Rate (BER) performance of the modified structure of a Digital Phase Locked Loop (DPLL) based system for dealing with Nakagami-m fading with coded and un-coded channel is presented here. The emphasis of the work is the implementation of Bose, Chaudhuri and Hocquenghem (BCH) channel coding and decoding technique. The performance of the DPLL for carrier reception with signal under certain modulation transmitted through Nakagami-m channels is compared with coded and un-coded conditions. The results of simulation of the proposed DPLL with Nakagami -m fading and QPSK modulation shows that the performance of the system improves significantly upon application of BCH channel coding..
All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decisi... more All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2 × 2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation.
Multi input multi output system (MIMO) has become a viable option to meet the demand of high data... more Multi input multi output system (MIMO) has become a viable option to meet the demand of high data rate wireless communication. But MIMO system performance is severely affected by the presence of co-channel interference (CCI). CCI cancellation in MIMO channel therefore is a challenging area of research. This paper provides a Kalman Filter based CCI cancellation approach. In the severely faded Rayleigh channel in coded MIMO set-up, experimental results show that Kalman filter based approach for CCI cancellation provides satisfactory results and can thus prove to be a reliable CCI cancellation technique in future.
Frequency response analysis is having significant importance in amplifier design. In some applica... more Frequency response analysis is having significant importance in amplifier design. In some applications along with the frequency response evaluation it is also important to extend the bandwidth of an amplifier. Extending the bandwidth means increasing the upper 3 dB frequency and decreasing the lower 3 dB limit. Although there are different means by which this extension can be achieved, we have chosen the application of negative feedback for the purpose. We have derived two new topologies using three blocks representation from existing topologies, which fulfill our bandwidth requirements. We specially describe the use of cascading three different types of individual feedback amplifiers as a composite block. In this paper, we are presenting a comparative approach between the two newly derived three stage feedback topologies based on the individual standard topologies and the two stage derived [3] topologies which extend the bandwidth of the amplifier around 26%.
One of the challenging issues in Spread-Spectrum Modulation (SSM) is the design of the Pseudo -Ra... more One of the challenging issues in Spread-Spectrum Modulation (SSM) is the design of the Pseudo -Random or Pseudo -Noise (PN) sequence generator. Though several approaches are available that deals with the PN -sequence generator, there always exists the possibility of exploring the use of innovative methods through which shortcomings of the known techniques can be minimized and the performance of communication systems using SSM improved. This work is related to the use of Artificial Neural Network (ANN) for generation of the PN sequence during transmission and reception of a SSM based system. The benefit of the ANN -assisted PN generator shall be that it will simplify the design process of the PN -generator and yet provide high reliability against disruptions due to intentional disruptions and degradation of signal quality resulting out of variations in channel condition. The experiments carried out show that the ANN -assisted system is robust enough to deal with the unpredictability in the wireless channels and provide satisfactory performance under Gaussian and Rayleigh /Rician fading. The performance of the SSM system can be further enhanced by the use of coding. Hamming and cyclic redundancy check (CRC) codes have been used here with the data stream to explore if performance of the SSM system is improved further.
Multi input multi output system (MIMO) has become a viable option to meet the demand of high data... more Multi input multi output system (MIMO) has become a viable option to meet the demand of high data rate wireless communication. But MIMO system performance is severely affected by the presence of co-channel interference (CCI). CCI cancellation in MIMO channel therefore is a challenging area of research. This paper provides a Kalman Filter based CCI cancellation approach which is connected to phase tracking performance of the system. Experimental result in the severely faded Rayleigh channel show that Kalman filter based approach for CCI cancellation in the considered MIMO channel provides reliable results and can thus prove to be a satisfactory CCI cancellation technique in future.
Cosmic showers generate secondary particles called Extensive Air Shower (EAS) while they enter th... more Cosmic showers generate secondary particles called Extensive Air Shower (EAS) while they enter the atmosphere of the earth. Several constraints are associated with the analysis of these EASs resulting in inaccuracies in measurements for which there exist a necessity to develop a readily available system based on soft-computational approaches. This is due to the fact that soft computational tools like the Artificial Neural Network (ANN)s can be trained as classifiers to adapt and learn the surrounding variations. But single classifiers fail to reach optimality of decision making for which Multiple Classifier System (MCS) are preferred. This work describes the formation of an MCS using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN) for EAS primary energy prediction and location determination. The results show that the set-up can be adopted for real time practical applications involving EAS from density values captured using detectors in a circular grid.
Till now in mobile communication, we have seen several techniques to eliminate the fading effects... more Till now in mobile communication, we have seen several techniques to eliminate the fading effects. One of the less exploded techniques is based on the physical parameter of the transmitter by varying the physical dimension of the transmitting antenna. This paper deals with a simple method to eliminate severe fading effects in different multi antenna setups by dynamically varying the affective aperture of the transmitting antenna. We consider here Single input-single output (SISO), Single input-multi output (SIMO), Multi input-single output (MISO), and Multi input-multi output (MIMO) system with three different modulation schemes -BPSK, DPSK and QAM. The data stream is transmitted through severely faded Rayleigh channels and before modulation, it is encoded using Hamming coding for significant performance improvement. Finally, mean Bit Error Rate (BER) for variable effective aperture is calculated and the system performance is analyzed for the different set-ups. We will see that our results show significantly better performance.
Artificial Neural Network (ANN)s are efficient means of prediction, optimization and recognition.... more Artificial Neural Network (ANN)s are efficient means of prediction, optimization and recognition. The ability of the ANN to learn given patterns makes them suitable for such applications. Fingerprint recognition is one such area that can be used as a means of biometric verification where the ANN can play a critical rule. An ANN can be configured and trained to handle such variations observed in the texture of the fingerprint. The specialty of the work is associated with the fact that if the ANN is configured properly it can tackle the variations in the fingerprint images and that way provide the insights for developing a system which requires these samples for verification and authorization. A system is designed to provide authentication decision using the fingerprint inputs can be a reliable means of verification. Such a system designed using ANN and using fingerprint inputs is described here. Experimental results show that the system is reliable enough for considering it as a part of a verification mechanism.
Artificial Neural Network (ANN)s are efficient means of prediction, optimization and recognition.... more Artificial Neural Network (ANN)s are efficient means of prediction, optimization and recognition. Retina is a unique biometric pattern that can be used as part of a verification system. An ANN can be configured and trained to handle such variations observed in the texture of the retina. The specialty of the work is associated with the fact that if the ANN is configured properly it can tackle the variations in the retinal images and that way provides the insights for developing a system which requires the samples for verification and authorization. A system designed to provide authentication decision using the input can be a reliable means of verification. Such a system designed using ANN and using retina input is described here. Experiemtnal results show that the system is reliable enough for considering it as a part of a verification mechanism.
Artificial Neural Network (ANN)s are efficient means of prediction, optimization and recognition.... more Artificial Neural Network (ANN)s are efficient means of prediction, optimization and recognition. Retina is a unique biometric pattern that can be used as part of a verification system. An ANN can be configured and trained to handle such variations observed in the texture of the retina. The specialty of the work is associated with the fact that if the ANN is configured properly it can tackle the variations in the retinal images and that way provides the insights for developing a system which requires the samples for verification and authorization. A system designed to provide authentication decision using the input can be a reliable means of verification. Such a system designed using ANN and using retina input is described here. Experiemtnal results show that the system is reliable enough for considering it as a part of a verification mechanism.
Artificial Neural Network(ANN)s are efficient means of prediction, optimization and recognition. ... more Artificial Neural Network(ANN)s are efficient means of prediction, optimization and recognition. Retina is an unique biometric pattern that can be used as part of a verification system. An ANN can be configured and trained to handle such variations observed in the texture of the fingerprint and retina. Fingerprint recognition is one such area that can be used as a means of biometric verification where the ANN can play a critical rule. The specialty of the work is associated with the fact that if the ANN is configured properly it can tackle the variations in the retinal and fingerprint images and that way provides the insights for developing a system which require these samples for verification and authorization. A system designed to provide authentication decision using these two inputs can be a reliable means of verification. Such a system designed using ANN and using retina and fingerprint inputs is described here. Experimental results show that the system is reliable enough for considering it as a part of a verification mechanism.
Artificial Neural Network(ANN)s are efficient means of prediction, optimization and recognition. ... more Artificial Neural Network(ANN)s are efficient means of prediction, optimization and recognition. Retina is an unique biometric pattern that can be used as part of a verification system. An ANN can be configured and trained to handle such variations observed in the texture of the fingerprint and retina. Fingerprint recognition is one such area that can be used as a means of biometric verification where the ANN can play a critical rule. The specialty of the work is associated with the fact that if the ANN is configured properly it can tackle the variations in the retinal and fingerprint images and that way provides the insights for developing a system which require these samples for verification and authorization. A system designed to provide authentication decision using these two inputs can be a reliable means of verification. Such a system designed using ANN and using retina and fingerprint inputs is described here. Experimental results show that the system is reliable enough for considering it as a part of a verification mechanism.
Animal-human conflict is now one of the most burning issues. All over the world animals are losin... more Animal-human conflict is now one of the most burning issues. All over the world animals are losing their lives due to deforestation and other factors. One of the most significant factors is railway line. A huge number of animals are being faced accident on railways track. Among them elephants are the most common victims. Nowadays pattern recognition techniques have been used to design anti collision device. The primary objectives of the application of pattern recognition techniques are to provide a machine the ability to recognize an input, provide a decision and perform a process control in subsequence stages. A generic pattern recognition system requires an input, pre-processing, feature extraction, classifier and decision device. The system first needs to be trained and subsequently tested. The formulation of the decision device classification stage is critical. Among a range of classifiers the soft computational classifiers like Artificial Neural Network (ANN) s have the ability to perform non linear processing and map inputs to multi-class situations. This work focuses on the design of a traffic control system based on pattern recognition techniques with appropriate modifications for applications to minimize train-elephant conflicts.
Animal-human conflict is now one of the most burning issues. All over the world animals are losin... more Animal-human conflict is now one of the most burning issues. All over the world animals are losing their lives due to deforestation and other factors. One of the most significant factors is railway line. A huge number of animals are being faced accident on railways track. Among them elephants are the most common victims. Nowadays pattern recognition techniques have been used to design anti collision device. The primary objectives of the application of pattern recognition techniques are to provide a machine the ability to recognize an input, provide a decision and perform a process control in subsequence stages. A generic pattern recognition system requires an input, pre-processing, feature extraction, classifier and decision device. The system first needs to be trained and subsequently tested. The formulation of the decision device classification stage is critical. Among a range of classifiers the soft computational classifiers like Artificial Neural Network (ANN) s have the ability to perform non linear processing and map inputs to multi-class situations. This work focuses on the design of a traffic control system based on pattern recognition techniques with appropriate modifications for applications to minimize train-elephant conflicts.
In this paper, we describe the design and implementation of a rake receiver for use with (UWB) sy... more In this paper, we describe the design and implementation of a rake receiver for use with (UWB) systems. The rake receiver uses spread spectrum modulation (SSM) aided by kasami sequence generator .The combination is found to be effective in dealing with multipath fading and signal to noise ratio. The design is initially simulated using MATLAB 7.5 and is implemented using a HDL coder .The design is also implemented in a FPGA kit and is found to be effective in interference mitigation as part of a CDMA framework.
In this paper, we describe the design and implementation of a rake receiver for use with (UWB) sy... more In this paper, we describe the design and implementation of a rake receiver for use with (UWB) systems. The rake receiver uses spread spectrum modulation (SSM) aided by kasami sequence generator .The combination is found to be effective in dealing with multipath fading and signal to noise ratio. The design is initially simulated using MATLAB 7.5 and is implemented using a HDL coder .The design is also implemented in a FPGA kit and is found to be effective in interference mitigation as part of a CDMA framework.
In this paper, we describe the design and implementation of a rake receiver for use with ultra wi... more In this paper, we describe the design and implementation of a rake receiver for use with ultra wide band (UWB) systems. The rake receiver uses spread spectrum modulation (SSM) aided by kasami sequence generator .The combination is found to be effective in dealing with multipath fading and signal to noise ratio. The design is initially simulated using MATLAB 7.10 and is implemented using a HDL coder .The design is also implemented in a FPGA kit and is found to be effective in interference mitigation as part of a CDMA framework.
In this paper, we describe the design and implementation of a rake receiver for use with ultra wi... more In this paper, we describe the design and implementation of a rake receiver for use with ultra wide band (UWB) systems. The rake receiver uses spread spectrum modulation (SSM) aided by kasami sequence generator .The combination is found to be effective in dealing with multipath fading and signal to noise ratio. The design is initially simulated using MATLAB 7.10 and is implemented using a HDL coder .The design is also implemented in a FPGA kit and is found to be effective in interference mitigation as part of a CDMA framework.
The customary practice of identifying industrial sickness is a set traditional techniques which r... more The customary practice of identifying industrial sickness is a set traditional techniques which rely upon a range of manual monitoring and compilation of financial records. It makes the process tedious, time consuming and often are susceptible to manipulation. Therefore, certain readily available tools are required which can deal with such uncertain situations arising out of industrial sickness. It is more significant for a country like India where the fruits of development are rarely equally distributed. In this paper, we propose an approach based on Artificial Neural Network (ANN) to deal with industrial sickness with specific focus on a few such units taken from a less developed north-east (NE) Indian state like Assam.
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Papers by Kandarpa Kumar Sarma