Qualification: 
M.Tech
Email: 
p_sudheesh@cb.amrita.edu
Phone: 
9443193913

Sudheesh P. currently serves as Assistant Professor at Department of Electronics and Communication Engineering, Amrita School of Engineering, Coimbatore Campus. He received his B.Tech in Electronics and Communication Engineering from College of Engineering, Trivandrum, India and M.Tech in Digital Systems and Communication Engineering from Regional Engineering College, Calicut, India. His area of interests includes digital system design, signal processing and wireless communication.

Research Expertise

  • UKF for channel estimation for high mobility system. (UG)
  • EKF for channel estimation combined with decision feedback equalizer for high mobility system. (PG)
  • Low complex fuzzy based kalman filter for fast time varying MIMO-OFDM systems. (UG)
  • Joint CFO and Channel estimation for fast time varying channels in MIMO-OFDM systems. (UG)

Teaching

  • Analog communication
  • Digital communication
  • Wireless communication
  • Communication theory
  • Signal processing

Publications

Publication Type: Journal Article

Year of Publication Publication Type Title

2016

Journal Article

Dr. Anita J. P. and Sudheesh, P., “Test power reduction and test pattern generation for multiple faults using zero suppressed decision diagrams”, International Journal of High Performance Systems Architecture, vol. 6, pp. 51-60, 2016.[Abstract]


An algorithm of test pattern generation for multiple faults is proposed using the zero suppressed decision diagrams (ZBDDs). Test pattern generation plays a major role in the design and testing of any chip. The proposed ZBDD is generated from its corresponding binary decision diagram (BDD). A test ZBDD is obtained from the true and faulty ZBDDs and the test patterns are generated from the test ZBDD. The obtained patterns are reordered because the order in which these patterns are used to test the chip is immaterial as far as the faults are concerned but the transitions between the test patterns affect the test power. Hence, the primary objective of the proposed work is the generation of test patterns for a given set of multiple faults. The next objective is to reduce the test power which is the power consumed during testing. © 2016 Inderscience Enterprises Ltd.

More »»

2015

Journal Article

H. Damodaran, Sudheesh, P., and Dr. Jayakumar M., “Extended kalman filter for channel estimation combined with decision feedback equalizer for very high mobility system”, International Journal of Applied Engineering Research, vol. 10, pp. 33914-33918, 2015.[Abstract]


Training sequence based channel estimation in combination with Decision Feedback Equalizer (DFE) is used for OFDM based communication receivers. Channel estimation is performed based on Extended Kalman Filter (EKF) algorithm where a two-step predictor corrector mechanism is carried out. In very high mobility environment for LTE downlink usual channel estimation algorithms are incapable due to its nonlinear nature. So an EKF is used for the estimation of complex-valued channel impulse response from the received signal in the non linear environment where the velocity is very large. EKF jointly estimates both time varying channel parameters as well as time correlation coefficients.. Furthermore a DFE is also modeled for eliminate the Inter Symbol Interference (ISI) and for better performance. Performance is evaluated by plotting Mean Square Error (MSE) as well as Bit Error rate (BER). © Research India Publications.

More »»

Publication Type: Conference Paper

Year of Publication Publication Type Title

2016

Conference Paper

M. M.G., Sudheesh, P., and Dr. Jayakumar M., “Channel Estimation for a high mobility MIMO system using Particle filter”, in International Conference on Recent Trends in Information Technology 2016 (ICRTIT 2016), 2016.

2015

Conference Paper

V. Gutta, Anand, K. K. T., Movva, T. S. V. S., Korivi, B. R., Killamsetty, S., and Sudheesh, P., “Low complexity channel estimation using fuzzy Kalman Filter for fast time varying MIMO-OFDM systems”, in 2015 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015, 2015, pp. 1771-1774.[Abstract]


Estimation of channel is a significant issue in wireless communication. In this paper, TS fuzzy Kalman Filter based channel impulse response(CIR) estimation, for the time varying velocity of the receiver in a Multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) system is being proposed. The channel is being modeled using second order auto regressive (AR) random model. Linearization of channel estimation is done using fuzzy logic and Kalman filter is used to estimate the channel. For fast time varying channel, fuzzy based channel impulse response estimation is a low complex technique when compared to conventional filters. © 2015 IEEE.

More »»

2012

Conference Paper

G. Ignatius, U. Varma, M. Krishna, Krishna, N. S., Sachin, P. V., and Sudheesh, P., “Extended Kalman filter based estimation for fast fading MIMO channels”, in 2012 International Conference on Devices, Circuits and Systems, ICDCS 2012, Coimbatore, 2012, pp. 466-469.[Abstract]


This paper presents an algorithm for performing effective channel estimation for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems when they encounter a fast fading environment. The algorithm models the parameters to be estimated using an auto-regressive model which is implemented using Burg Method. The channel estimation is performed using an Extended Kalman Filter (EKF). The effect of intercarrier interference (ICI) is removed by QR decomposing the channel matrix, which effectively leads to estimation of the data symbol. The channel is modeled as L-path parametric Rayleigh flat fading. The Rayleigh complex amplitudes (CA) and carrier frequency offset are jointly estimated for this channel. © 2012 IEEE.

More »»

2012

Conference Paper

G. Ignatius, Murali, K. V. U., Krishna, N. S., Sachin, P. V., and Sudheesh, P., “Extended Kalman filter based estimation for fast fading MIMO channels”, in 2012 International Conference on Devices, Circuits and Systems, ICDCS 2012, Coimbatore, 2012, pp. 157-161.[Abstract]


This paper presents an algorithm for performing effective channel estimation for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems when they encounter a fast fading environment. The algorithm models the parameters to be estimated using an auto-regressive model which is implemented using Burg Method. The channel estimation is performed using an Extended Kalman Filter (EKF). The effect of intercarrier interference (ICI) is removed by QR decomposing the channel matrix, which effectively leads to estimation of the data symbol. The channel is modeled as L-path parametric Rayleigh flat fading. The Rayleigh complex amplitudes(CA) and carrier frequency offset are jointly estimated for this channel. © 2012 IEEE.

More »»

2012

Conference Paper

P. Sudheesh, Jayakumar, A., Siddharth, R., Srikanth, M. S., Bhaskar, N. H., Dr. Sivakumar V., and Sudhakar, C. K., “Cyclic prefix assisted sparse channel estimation for OFDM systems”, in 2012 International Conference on Computing, Communication and Applications, Dindigul, Tamilnadu, 2012.[Abstract]


In this paper an efficient algorithm is presented for the estimation of a channel modelled as sparse for an OFDM system. Conventional Pilot-Based techniques and blind estimation techniques require a large number of pilot tones and complex mathematical computations respectively to estimate the channel vector. This drawback is particularly pronounced in sparse systems where the effective channel vector has a very few number of taps. The proposed method uses a modification made to the Cyclic Prefix to detect the position of the most significant taps (MST) for a sparse channel. Least Square estimation method is then used to effectively estimate the channel vector. Prior knowledge of the most significant tap positions obtained from the cyclic prefix ensures spectral and computational efficiencies. More »»

2011

Conference Paper

S. Bharadwaj, Krishna, B. M. Nithin, Sutharshun, V., Sudheesh, P., and Jayakumar, M., “Low complexity detection scheme for NOFDM systems based on ML detection over hyperspheres”, in 2011 International Conference on Devices and Communications, ICDeCom 2011 - Proceedings, Mesra, 2011.[Abstract]


Nonorthogonal Frequency Division Multiplexing (NOFDM) is a digital modulation technique that promises to provide extremely high spectral efficiencies. However, this modulation scheme is seldom used in practice due to the high computational complexity involved in decoding the received signal in the presence of noise. The basic aim of this paper is to reduce this decoding complexity. Here, we propose a low complexity detection algorithm which makes use of maximum likelihood (ML) decoding not over the entire signal constellation but over a proper subset of the constellation that lies on a hypersphere thereby reducing the computational complexity for decoding. Computational complexity has been evaluated for various values of transmitted power and the result has been plotted for both ML detection algorithm and the proposed algorithm at a fixed data rate. The BER performance for both the algorithms has also been compared at a fixed data rate and the result has been plotted. The results show that the proposed algorithm is far superior to ML detection algorithm in terms of computational complexity. © 2011 IEEE.

More »»

Publication Type: Conference Proceedings

Year of Publication Publication Type Title

2014

Conference Proceedings

L. Narayanan V, Sellappan, D. Kumar, Kodakandla, V. Kumar, V, A., M, P. K., and Sudheesh, P., “Basis Expansion Models for Low Complex Parametric Type Channel Estimation for MIMO-OFDM Systems”, Proceedings of the 5th National Conference on Recent Trends in Communication Computation and Signal Processing RTCSP-2014. pp. pp. 35- 37, 2014.

207
PROGRAMS
OFFERED
5
AMRITA
CAMPUSES
15
CONSTITUENT
SCHOOLS
A
GRADE BY
NAAC, MHRD
9th
RANK(INDIA):
NIRF 2017
150+
INTERNATIONAL
PARTNERS