Qualification: 
Ph.D, M.Tech
Email: 
r_ramanathan@cb.amrita.edu

Dr. R. Ramanathan joined the Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham in the year 2006, where he is currently an Assistant Professor (Selection Grade). He received his B.E. degree in Electronics and Communication from Bharathiyar University, Coimbatore, India in 2004. He received his M.Tech degree in Computational Engineering and Networking and Ph. D. degree in Electronics and Communication from Amrita Vishwa Vidyapeetham, Coimbatore, India in 2011 and 2015 respectively.  Dr. Ramanathan is the recipient of Best Outgoing Student in High School in 2000 and Best Outgoing Student in college (undergraduate level) in 2004. Prior to joining Amrita, he was working as Senior Engineer – Transmissions for Nokia projects in Hutch Essar ./ Vodafone for two years.

His areas of research include optimization and signal processing for wireless communication and networks, MIMO and OFDM communications, Bio-inspired Computing, Wireless Sensor Networks, Physical layer signal design and security and Convex Optimization. He has authored around 26 technical papers in reputed conferences and journals indexed in Scopus. He has coauthored a book “Digital Signal and Image Processing- The Sparse way” published by Elsevier India in 2012.

He is a member of Institution of Electronics and Telecommunication Engineers (IETE) and Association of Communication, Electrical and Electronics Engineers (ACEEE). He is the reviewer for the journals IET Signal Processing, IET Communications and Wiley Computer Applications in Engineering Education.

 Research Expertise

  •  Physical Layer Security in Energy Harvesting Wireless Networks
  •  Device free localization in Wireless Sensor Networks
  •  Compressed Sensing in Massive MIMO systems
  •  Localization in 3D Wireless Sensor Networks
  •  Design and development of Protocols in Energy Harvesting Wireless Networks
  •  MIMO Radar Signal Processing
  •  Full Duplex D2D communication
  •  Massive 5G wireless communication systems
  •  Vehicular Networks and Communications

 

 Teaching

  •  Wireless Communication & Networks
  •  Mathematical Methods for Communication Engineering
  •  Digital Communication
  •  Convex Optimization
  •  MIMO and Multicarrier Communications
  •  Signal Processing
     

Publications

Publication Type: Conference Paper

Year of Publication Title

2021

Bhavitha B., Divyaprakash R., Vedha T. Selvam, V Vinith Kumar, and Dr. Ramanathan R., “Improved Real-Time Approach to Static Hand Gesture Recognition”, in 2021 11th International Conference on Cloud Computing, Data Science Engineering (Confluence), 2021.[Abstract]


A real-time hand detection and tracking system is developed in this work in which the gestures are recognized by counting the number of fingers. More than fifteen kinds of hand gestures are recognized in this system and these gestures are then mapped with the keyboard keys. For background Subtraction we used Grayscale color space followed by. contour of hand, which is developed using Canny's Algorithm to which we applied Chan's algorithm to obtain the convex hull. From the defect points of Convex Hull, we obtained the center point of the hand. Using this, we counted the fingers and thereby recognizing the gestures. We performed several trials to validate the feasibility and applicability of the proposed system, and confirmed the accuracy of 93.20%.

More »»

2019

A. Suraj S, A, G., S, S. Chakravart, and Dr. Ramanathan R., “Routing in Wireless Sensor Network Based on Swarm Intelligence”, in 3rd International Conference on Trends in Electronics and Informatics (ICOEI 2019), 2019.[Abstract]


Routing is one of the imperative methodologies for building up an effective network, expanding the lifetime of WSN with constrained battery drain, helps the WSN to work legitimately during traffic heterogeneity. The inefficiency in picking an appropriate routing strategy may prompt loss of time, energy and thus the cost. In this paper, we propose three routing strategies based on swarm insight by which we recognize the proficient directing strategy as per the issue distinguished. The simulation results corroborate the efficacy of proposed algorithms and provide possible directions to entail further research.

More »»

2019

S. S. Aswanth, Gokulakannan, A., Sibi, C. S., and Dr. Ramanathan R., “Investigation of Cluster Header Selection Methods in Hierarchical Wireless Sensor Networks”, in 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India, India, 2019.[Abstract]


One of the most important approaches for increasing the lifetime of wireless sensor networks is clustering. The inefficiency in choosing a suitable clustering technique for the given Wireless Sensor Network may lead in loss of time and energy and thus the cost. In this paper, we present four strategies for clustering techniques which can be used in a hierarchical wireless sensor networks. The numerical results are presented to validate the effectiveness of the proposed clustering techniques in terms of providing energy efficient network with better node live time.

More »»

2019

S. S. Aswanth, Gokulakannan, A., Sibi, C. S., and Dr. Ramanathan R., “Performance Study of Bio-Inspired Approach to Clustering in Wireless Sensor Networks”, in 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), 2019.[Abstract]


Wireless sensor networks experience an urgent need to deliver maximum efficiency in order to sustain their massive deployment. Clustering has been regarded as an effective technique to enhance efficiency of sensor nodes by suitably distributing them over the network region. Bio-inspired algorithms, with their ability to optimize complex problems with no well-defined solution, have been considered as perfect tool to aid this form of centralized clustering. In this paper we perform a study on the recently developed biologically inspired algorithms namely, firefly algorithm, symbiotic organism search algorithm and the bat algorithm and analyze the same against the meta-heuristic harmony search algorithm and the deterministic k-means algorithm for clustering the sensor nodes. Here, the intra-cluster communication cost has been considered as the optimization function orchestrating the clustering process. It is found that firefly algorithm displays a superior performance in terms of optimization owing to its unique ability to explore and exploit the solution set appropriately.

More »»

2019

H. Surej I and Dr. Ramanathan R., “A Performance Study of Bio-Inspired Algorithms in autonomous landing of Unmanned Aerial Vehicle”, in Third International Conference on Computing and Network Communications (CoCoNet'19), 2019.[Abstract]


The complete operational automation of fixed wing Unmanned Aerial Vehicle (UAV) involves the autonomous operations across take-off, cruising and landing. Among all these stages the landing stage is the most crucial one. During landing, it is important for the UAV to maintain a constant speed and glide slope to ensure the stability and a successful touchdown on the runway. Also, it is important for a UAV to estimate the accurate point of landing in a minimal amount of time. Embedding Bio-inspiring algorithms in UAV control systems helps in accurate estimation of the landing point in a minimal amount of time. In this research work, the Bio-inspired optimization algorithms Bats Optimization Algorithm, Moth Flame Optimization Algorithm and Artificial Bee Colony Algorithm are used in determining the coordinates (points) of the computed path and to determine the optimal point of landing which ensures the above said parameters are within the operational limits of the UAV. The objective of this research work is to determine the path from the computed points and to find the optimal landing point in a minimal amount of time. The difference between the original points of the actual path and the derived computed points of the estimated path is measured as the error rate. The performance of the algorithms is analyzed in terms of two trade-off parameters, the time taken to compute the landing point and the accuracy in predicting the landing point. The empirical results show that the Moth Flame Optimization Algorithm takes less time to compute the optimal point with minimal error among the three optimization algorithms taken up for the study.

More »»

2019

D. Kumar G, Menon, S. R., M, P., and Dr. Ramanathan R., “Metaheuristic Approach to Optimal Path Finding in Wireless Charging of Sensor Nodes Using Autonomous Bots”, in International Conference on Computing and Network Communications (CoCoNet'19), 2019.[Abstract]


Wireless Sensor Nodes play a prominent role in many military and civilian applications. They are used to collect data for various disciplines from diverse environments. The main drawback of this technology is the decrease in energy of the wireless sensor nodes as time progresses. A significant amount of works has been done and justified in using an autonomous bot to charge the wireless sensor nodes. There are a lot of difficulties to overcome to implement the concept of using an autonomous bot to charge the independent wireless sensor nodes. One such cumbersome issue is the scheming of an optimal path for the autonomous bot to charge these wireless sensor nodes efficiently. In this paper, we present a comparative study of various methods Ant Colony Optimization algorithm, Simulated Annealing and Tabu search to compute the tour of the Autonomous bot to recharge the nodes, considering the tour length and the time taken to compute the tour length. The result of this study gives which algorithm is best suited for a given network with a given number of nodes with respect to tour length and time taken to compute the tour.

More »»

2019

K. Saravanamuthu and Dr. Ramanathan R., “Sparsity Exploiting Detection in Massive MIMO Systems via Separable Approximation Technique”, in 2019 6th International Conference on Signal Processing and Integrated Networks, SPIN 2019, 2019, pp. 156-161.[Abstract]


In this paper, we propose a separable approximation method for detection in Massive MIMO systems employing spatial modulation. Spatial Modulation is becoming a viable technique for wireless communication which in turn introduces a kind of sporadic nature into the communication environment. The antenna element is also taken as additional information other than the traditional communication system in the SM. The sporadic nature enables us to use compressed sensing algorithms in this scenario for a massive system where an efficient detection algorithm is imperative. The Bit error rate performance and running time complexity are analyzed for the proposed technique considering all constellation formats and sporadicity. The results are encouraging and substantiates that this approach is a suitable candidate for further research. © 2019 IEEE.

More »»

2018

K. Saravanamuthu and Dr. Ramanathan R., “A Particle Swarm Approach to Target Detection in MIMO Radar”, in International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2018.[Abstract]


Devising target detection techniques for Multiple Input Multiple Output (MIMO) Radar systems is the main theme of this paper. A novel Particle Swarm Optimization algorithm based framework for superior target detection and grid localization for MIMO Radar is proposed. PSO algorithm finds effective utility in large signal spaces for multiple target detection and is easy to implement. The signal model characterizing the clutter and clutter-free environments are modelled. We adopt Orthogonal Matching Pursuit (OMP) algorithm as a benchmark for comparison. Mathematical interpretation of the OMP algorithm for multiple target detection is provided. Simulation results which prove the optimality of the proposed PSO approach are presented. The variation of Mean Squared Error (MSE) with Signal-to-Noise Ratio is used as a performance metric for analysis. Time complexity analyses of the PSO and OMP algorithms are also presented. The proposed approach is also extended for estimation of target characteristics.

More »»

2018

V. Anjali and Dr. Ramanathan R., “Improved Iterative Thresholding Technique for Detection in Sporadic Large-Scale Multiuser MIMO Systems”, in International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2018.[Abstract]


Compressed sensing based detection technique has emerged to be a promising solution for large-scale sporadic multi-user MIMO systems. However, their performance significantly degrades with a decrease in sparsity, increased constellations and imperfect channel estimation. In this paper, an improved iterative thresholding technique is proposed to resolve the above problems. Bit error rate performance and computational complexity characteristics for varying MIMO configurations are presented. Results substantiate that the proposed technique offers a gain of around 2 dB compared to conventional compressed sensing algorithm. The proposed technique seems to be a viable solution to improve the performance without compromising the complexity.

More »»

2018

V. Anjali and Dr. Ramanathan R., “Detection in Sporadic Multiuser Systems over 3GPP LTE Networks”, in International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2018.[Abstract]


In this paper, we study the employability of compressed sensing algorithms in the context of multiuser detection in machine to machine systems over 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE) framework. The key idea of this work is to exploit the sparsity in the Machine to Machine (m2m) communication which is rendered by the sporadic nature of the transmission by the machines. We have analyzed the Bit Error Rate (BER) performance for various signal to noise ratio conditions and the impact of sparsity indicated by the probability of activity, operational frequencies and antenna spacing at the base station on the detection performance of the system. Through the results, we substantiate that the compressed sensing algorithms prove to be a viable choice for multiuser detection and practical implementation.

More »»

2018

C. S. Pradeep and Dr. Ramanathan R., “Investigation of secret key capacity in MIMO-OFDM wireless systems”, in Procedia Computer Science, 2018, vol. 143, pp. 776-785.[Abstract]


MIMO and MIMO-OFDM systems are the enabling technologies for the next generation wireless systems. However, the radio signals transmitted are available for reception by a illegitimate user leading to eavesdropping. This raises severe concerns on the security of the transmission. Physical Layer security aims to exploit the wireless channel characteristics and in turn provide secure transmission robust against eavesdropping. In this paper, we investigate the Secret Key Capacity (SKC) in MIMO-OFDM systems. We derive expressions for SKC in MIMO systems and extend further to OFDM waveforms. Numerical simulations are performed for various transmit and receive antenna configurations without any estimation errors. © 2018 The Authors. Published by Elsevier B.V.

More »»

2018

S. J. Sreeraj and Dr. Ramanathan R., “Improved geometric filter algorithm for device free localization”, in Proceedings of the 2017 International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2017, 2018, vol. 2018-January, pp. 914-918.[Abstract]


Device Free Localization (DFL) is one of the emerging applications of Wireless Sensor Networks, which can find people or objects in a monitored area - even through walls. 'Device Free' - which states that the method can localize a person or target, without the target using any Passive or active devices such as RFID tags or GPS devices. 'Tracking through walls'- which make the method unique than other device free monitoring methods like the ones employing Image/Video processing or with Infrared or Light rays. This method uses Radio signals to scan an area to localize the target. The Geometric Filter (GF) algorithm discussed in this paper is one of the approaches which uses Received Signal Strength (RSS) in the links as a metric and gives better tracking performance using only simple computations based on geometric objects. This method performs better than others with lower tracking errors and with huge improvement in average execution time. This paper analyses the Geometric Filter algorithm with performance evaluation in different number of nodes and with measurement noise. An improvement is also suggested. © 2017 IEEE.

More »»

2018

S. Mane and Dr. Ramanathan R., “Investigation of greedy forwarding strategies for three dimensional vehicular ADHOC networks”, in Proceedings of the 2017 International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2017, 2018, vol. 2018-January, pp. 1339-1343.[Abstract]


This paper emphasizes on importance of the routing protocol compatibility with three-dimensional road scenarios like viaducts, flyovers & road ramps. To highlight the impact of compatibility issue we analyze performance variation of greedy forwarding techniques designed to work with 2D co-ordinates and 3D co-ordinates. In this paper we mention these strategies as 2D greedy forwarding and 3D greedy forwarding. In the end we conduct the comparison between performance of 2D greedy algorithm and 3D greedy algorithm on NS2 platform and we present the result in graphical format. Results shows that performance of 3D greedy forwarding technique is superior to 2D forwarding technique. 3D greedy forwarding is more suitable with three-dimensional road structures than traditional greedy forwarding working with 2D co-ordinates. © 2017 IEEE.

More »»

2018

P. Yadav and Dr. Ramanathan R., “Dynamic key generation using single threshold multiple level quantization scheme for secure wireless communication”, in Proceedings of the 2017 International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2017, 2018, vol. 2018-January, pp. 34-38.[Abstract]


Quantized bits per sample contributes to the total length of the key generated from samples. Each quantized bit provides security against brute force attack. Ideally, the quantized bits per sample depend on either threshold levels or data range. In this paper, we are proposing a quantization method, which assigns multiple bits to samples using a single threshold and quantized bits per sample are independent of both threshold levels and data range. This quantization technique will be helpful to methods that have low quantized bits per sample. Quantization process is critical in multiple areas of communication. Quantization process highly impacts the number and agreement of quantized bits generated at transmitter and receiver. An efficient quantization method will reduce the effort of consecutive blocks for error correction and a sufficient number of quantized bits will satisfy criteria of minimum quantized bits and limitation of any domain. A well-designed quantization technique will offer more quantized bits per sample and less bit disagreement between transmitter and receiver. Quantization technique will have a high impact on future technology, which uses channel reciprocity and randomness for a dynamic key. © 2017 IEEE.

More »»

2018

M. S. Kumar and Dr. Ramanathan R., “Impact of anchor position errors on WSN localization using mobile anchor positioning algorithm”, in Proceedings of the 2017 International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2017, 2018, vol. 2018-January, pp. 1924-1928.[Abstract]


Localization of sensor node is imperative in Wireless Sensor Networks (WSN) as data gathered at the user end become meaningless without location information of the node. In this work, impact of anchor position errors on WSN localization using Mobile Anchor Positioning (MAP) Algorithm has been investigated by evaluating two deployment strategies. In deployment I sensor nodes are randomly spread in the entire chosen area (1000 χ 1000) whilst deployment II has nodes spread in the central region of the chosen area. Firstly, MAP Algorithm employing three anchor nodes is investigated for the two deployments. To study the impact of mobile anchors on MAP, anchor number is increased to four and the two deployments are investigated again. Further, this work also investigates the effect of anchor position errors on localization accuracy of sensor nodes. Error term is modelled using Additive White Gaussian Noise (AWGN) Model. Performance metrices considered for validation are Average Root Mean Square Error and Execution time. © 2017 IEEE.

More »»

2017

S. Vijayaraghavan, Ramnath, D., Deepak, T., Krishnakumar, K., and Dr. Ramanathan R., “An improved secret key update for multiple intersymbol obfuscation in physical layer security”, in 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, 2017, vol. 2017-January, pp. 191-197.[Abstract]


Communications security has become an integral part of wireless networks. A commonly known method to attain secrecy of information is done by addition of noise to corrupt the intruder's channel. In this paper, we undertake the principle of multiple inter-symbol obfuscation (MIO) method to improve security in wireless based communication in the last level of the OSI (Open System Interconnect) model, i.e. the physical layer. On encryption using the concept of MIO, an arbitrary subgroup of the respective symbols are put into data packets that are obscured with a group of artificially included noise symbols, commonly known as the symbols key. This tends to corrupt the third party's quality of the channel and make it worse than the genuine receiver. Hence he cannot unravel the information correctly without knowledge of the symbols key used in encryption. A self-updating process for the key is designed for automatic update of the key to enhance the encryption process. With the help of a dynamic key update process the legitimate receiver is able to encrypt the given information from the transmitter and protect it from the intruders who try to extract the message. Hence this method can deliver secrecy against passive eavesdropping and computational discretion against the fake packet injection attacks. This paper has been implemented using tools such as MATLAB and simulations have been carried out to determine the efficacy of MIO in wireless communication. © 2017 IEEE.

More »»

2017

M. Sundaram, Dr. Ramanathan R., and M., G., “Performance optimization of RF energy harvesting wireless sensor networks”, in Procedia Computer Science, 2017, vol. 115, pp. 831-837.[Abstract]


We consider a single-input-multiple-output (SIMO) system where power radiated from the transmitter is received and harvested at the receiver. In the proposed algorithm, we study the influence of Channel State Information (CSI) on the maximum harvestable power at the receiver along with the optimization of receiver architecture, adaptive transmit beam forming, and receiver operation policy. On keen observation of the output response, our simulations results show that adaptive transmit beam forming with optimal time allocation for channel estimation will be favourable for maximization of harvested energy. © 2017 The Author(s).

More »»

2017

G. J. Vignesh, Vikranth, S., Dr. Ramanathan R., and M., G., “A novel fuzzy based approach for multiple target detection in MIMO radar”, in Procedia Computer Science, 2017, vol. 115, pp. 764-770.[Abstract]


This paper deals with the problem of multiple target detection in MIMO Radar systems. We propose a novel fuzzy-based approach for detecting multiple targets when conventional Compressive Sensing algorithms fall short. Ease of interpretability, modeling, limited training data requirement and implementation are some of the benefits of the Fuzzy-Logic based approach. The variation of the probability of detection, the probability of false alarm and the Mean Squared Error with the Signal-to-Noise ratio are studied. Also, the time complexity of the proposed Fuzzy-based approach is measured. © 2017 The Author(s).

More »»

2015

T. C. Snehith, Anil, K. K., Raju, A. K., and Dr. Ramanathan R., “Impact of channel estimation errors on lattice reduction gains in MIMO systems”, in Advance Computing Conference (IACC), 2015 IEEE International, 2015.[Abstract]


In this paper, we propose an approach based on Lattice Reduction (LR) algorithm which preserves the channel norm in the presence of estimation errors. We analyze the channel norm of perfect and imperfect channel by employing LR algorithm on both perfect and imperfect channels in MIMO systems with 2, 4, 8 and 16 antennas for various error variances. We conclude that effective detection can be achieved even with imperfect channel by employing LR on those channels.

More »»

2015

K. K. Anil, Raju, A. K., Snehith, T. C., and Dr. Ramanathan R., “Likelihood Ascent-Gibbs Sampling for efficient MIMO detection”, in Advance Computing Conference (IACC), 2015 IEEE International, 2015.[Abstract]


In this paper, we propose a hybridized Likelihood Ascent-Mixed Gibbs Sampling (LAS-MGS) for effective detection with channel estimation error. We analyze its performance in the presence of channel estimation error for 2×2 and 4×4 MIMO systems employing BPSK modulation scheme. At low SNRs, performance of ZF-MGS and LAS-MGS is similar but at high SNRs, LAS-MGS performs significantly better. LAS-MGS outperforms conventional Mixed Gibbs Sampling (MGS) and we are able to harness similar gain even with channel estimation errors. We conclude that LAS-MGS is a worthy candidate for further research.

More »»

2015

I. Aravindan, K. Antony, R., K. Kumar, A., Snehith, T. C., Padmakumar, A., and Dr. Ramanathan R., “A performance study of MIMO detectors in the presence of channel estimation errors”, in Proceedings - 2015 International Conference on Communication, Information and Computing Technology, ICCICT 2015, 2015.[Abstract]


In this paper, we investigate the performance of the low-complexity algorithms based on Likelihood Ascent Search (LAS) and Tabu Search (TS) for detection in MIMO systems with channel estimation errors. Here, we briefly review the algorithms for LAS and TS and their variants and subsequently compare them for various MIMO settings. We provide the simulation results for BER performance in 2× 2, 4× 4 and 8× 8 MIMO systems. From the results, we conclude that Tabu Search shows no degradation in BER up to an estimation error variance of 0.05 in lower order systems, while LAS offers the same advantage in higher order systems. However, this trend is also valid for LAS in lower order systems, in the low SNR regime. We corroborate that LAS and TS are worthy candidates for further research. © 2015 IEEE.

More »»

2011

N. Ashish, Srivatsan, K. R. Atul, Karthikeyan, N., Pasupuleti, R. T., Gutta, S., Raman, A. A., and Dr. Ramanathan R., “A novel channel estimation technique for MIMO-OFDM systems for Frequency Selective Ricean channel”, in 2011 International Conference on Emerging Trends in Electrical and Computer Technology, ICETECT 2011, Chunkankadai, 2011, pp. 671-675.[Abstract]


The MIMO system convincingly promises a better bit rate in comparison with a SISO system. The system gets even efficient when OFDM is implemented with MIMO to obtain better data rates even in hostile channel environment. Research establishes OFDM as a potential candidate for use in MIMO systems for the reasons like inherent FFT, waveform adaptation, advanced antenna techniques, multiple access, interoperability, etc. Since, channel estimation is an integral part of OFDM system; it stands to demand a technique that can offer accurate channel characterization for effective equalization to follow. In addition, there exists a tradeoff between accuracy of estimation and complexity of the technique. In this paper, a combined channel estimation technique, which combines the virtues of Least Squares and LMMSE estimators with SVD in MIMO-OFDM systems. This combined strategy increases the estimate accuracy without much increase in complexity or computation considering a Ricean Frequency Selective channel environment. The proposed technique is explicated with necessary mathematics and the theory is well substantiated with simulations. The technique is fitted into the OFDM framework and the simulation results indicate a good estimate of the channel. The theory and results are presented and discussed in the paper. © 2011 IEEE. More »»

2011

A. Chandran, R. Karthik, A., A. Kumar, Naidu, R. C., M. Siva, S., Iyer, U. S., and Dr. Ramanathan R., “A novel spectrum sensing technique for low Signal to Noise Ratio conditions”, in 2011 International Conference on Emerging Trends in Electrical and Computer Technology, ICETECT 2011, Chunkankadai, 2011, pp. 681-685.[Abstract]


Wireless communication is an emerging and evergreen field of research and will continue to be so in the future. Increased demands in spectrum and users eventually result in spectral congestion. Cognitive Radio systems provide an intelligent and an attractive solution to this problem. Spectrum Sensing is the main key for the functioning of Cognitive Radio and helps in efficient spectrum utilization. Wavelets provide a new dimension to tackle spectrum sensing when compared to the conventional methods. In real time applications, loss of signal is prominent in low SNR conditions and hence a system capable of working under such conditions will prove to be an asset. In this paper, a wavelet based approach to spectrum sensing at low SNRs is dealt with. A new algorithm for spectrum sensing has been proposed here which emphasizes more on the functioning of systems in low SNR conditions. © 2011 IEEE. More »»

2011

N. Ashish, Srivatsan, K. R. Atul, Karthikeyan, N., Pasupuleti, R. T., Gutta, S., Raman, A. A., and Dr. Ramanathan R., “A novel channel estimation technique for MIMO-OFDM systems for frequency selective rayleigh channel”, in 2011 International Conference on Devices and Communications, ICDeCom 2011 - Proceedings, Mesra, 2011.[Abstract]


The MIMO system convincingly promises a better bit rate in comparison with a SISO system. The system gets even efficient when OFDM is amalgamated with MIMO to obtain better data rates even in hostile channel environment. Research establishes OFDM as a potential candidate for use in MIMO systems for the reasons like inherent FFT, waveform adaptation, advanced antenna techniques, multiple access, interoperability, etc. Since, channel estimation is an integral part of OFDM system; it stands to demand a technique that can offer accurate channel characterization for effective equalization to follow. In addition, there exists a tradeoff between accuracy of estimation and complexity of the technique. In this paper, a combined channel estimation technique, which combines the virtues of Least Squares and LMMSE estimators with SVD in MIMO-OFDM systems. This combined strategy increases the estimate accuracy without much increase in complexity or computation considering a Rayleigh frequency-selective channel environment. The proposed technique is explicated with necessary mathematics and the theory is well substantiated with simulations. The technique is fitted into the OFDM framework and the simulation results indicate a good estimate of the channel. The theory and results are presented and discussed in the paper. © 2011 IEEE. More »»

2011

A. Chandran, R. Karthik, A., A. Kumar, M. Siva, S., Iyer, U. S., Dr. Ramanathan R., and Naidu, R. C., “Discrete wavelet transform based spectrum sensing in futuristic cognitive radios”, in 2011 International Conference on Devices and Communications, ICDeCom 2011 - Proceedings, Mesra, 2011.[Abstract]


With the advent of an era of wireless communication, the number of users is on the rise, the result of which is spectral congestion. Cognitive Radio systems provide an intelligent and an attractive solution to this technical crisis. Spectrum Sensing is indispensable for the functioning of Cognitive Radio and helps in efficient spectrum utilization. In this paper, a wavelet based approach to spectrum sensing is dealt with. Wavelets provide a new dimension to tackle spectrum sensing. This method is comparatively easier and more reliable than the conventional energy detector. An algorithm for spectrum sensing has been proposed and the results obtained for various scenarios are tabulated. A comparison with the conventional energy detector has been performed to substantiate the proposal. Some important conditions are also specified. © 2011 IEEE. More »»

2010

D. M. Chinnam, Madhusudhan, J., Nandhini, C., Prathyusha, S. N., Sowmiya, S., Dr. Ramanathan R., and Dr. Soman K. P., “Implementation of a Low Cost Synthetic Aperture Radar using Software Defined Radio”, in 2010 2nd International Conference on Computing, Communication and Networking Technologies, ICCCNT 2010, Karur, 2010.[Abstract]


GNU radio is a free open-source software toolkit for building software radios, in which software defines the transmitted waveforms and demodulates the received waveforms. In this paper an attempt has been made to explore the means to use a Software Defined Radio (SDR) to implement a basic radar system and then synthetic aperture radar. An experiment where in readings at two different scenarios (free environment and metal object) are taken into account and their plots are also given. This has been attempted keeping in mind the exponential increase in chip computing power and the ability to upgrade a radio transceiver via software updates with a marginal investment, the two features which makes such a foray attractive, technology wise and cost wise. This attempt also takes us a step closer to establishing the concept of a Cognitive radar which is software signal processing intensive.

More »»

2010

D. M. Chinnam, Madhusudhan, J., Nandhini, C., Prathyusha, S. N., Sowmiya, S., Dr. Ramanathan R., and Soman, K. P., “Intrusion detection using software defined noise radar”, in 2010 2nd International Conference on Computing, Communication and Networking Technologies, ICCCNT 2010, Karur, 2010.[Abstract]


The need for reliable systems for detecting intrusions into a given area has given rise to the research and use of random noise radars. This paper deals with the issues regarding the use of such systems. The advantages of the use of such radar are illustrated followed by the actual mode of implementing the system itself. The novelty in this approach is the use a software defined radio as the platform for the system as it has a number of added advantages as have been detailed Subsequently, the intrusion detection can be viewed as a classification problem and solved using any machine learning algorithm. The paper also investigates the use of support vector machines (SVM) for the above said problem and derives a suitable model for classification. The training and testing of SVM model is in progress. ©2010 IEEE. More »»

2010

A. Chandran, R. Karthik, A., A. Kumar, Naidu, R. C., M. Siva, S., Iyer, U. S., and Dr. Ramanathan R., “Evaluation of energy detector based spectrum sensing for OFDM based cognitive radio”, in Proceedings of 2010 International Conference on Communication and Computational Intelligence, INCOCCI-2010, Perundurai, Erode, 2010, pp. 163-167.[Abstract]


With congested wireless spectrum and increasing number of users, cognitive radio serve as a panacea for efficient spectrum utilization. This stands to substantiate the amount of research happening in this area. Spectrum sensing is indubitably a key functionality in cognitive radio, which helps determining the spectral holes and white spaces for the secondary users to communicate. In this paper, the energy detector based spectrum sensing for OFDM based cognitive radio is studied and evaluated for various Signal and Noise conditions. The threshold which is a determining factor in energy detector is computed using a divide and conquer approach which is also a novelty of this paper. The bound for minimum width of the white space that is detectable by an energy detector in the case of real time multiple primary user scenario is well established through convincing simulations. The influence of SNR on the spectrum sensing is also presented with regard to the accuracy of sensing or probability of detection. Certain indispensable conditions for implementation of this detector are also discussed. © 2010 Kongu Engineering College. More »»

2010

C. Manoj, Narayanan, K. A., Kota, B. A., Shivaram, P. A., Prasad, A. S., and Dr. Ramanathan R., “Investigation of various channel models for application of constant power water filling algorithm”, in 2010 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2010, Coimbatore, 2010, pp. 581-587.[Abstract]


The increasing demand for portable and mobile communication devices has made wireless communication an indispensable field of research. The performance of any wireless communication system is determined to a large extent by the characteristics of the channel. For the purpose of system design and development, it is advantageous to have knowledge of the characteristics of the channel. In this paper, we discuss the various channel models that are in use today. We also present an overview of the various estimation and equalization algorithms that are widely employed. We then present the results of the simulations of the various channel models, and the observations made from these simulations. Finally, we describe the theory of constant power water filling algorithm and how it can applied to maximize the capacity of a Rayleigh fading channel. © 2010 IEEE. More »»

2009

Dr. Ramanathan R., Valliappan, N., Mathavan, S. P., Gayathri, M., Priya, R., and Dr. Soman K. P., “Generalised and channel independent SVM based robust decoders for wireless applications”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009.[Abstract]


Emerging applications in wireless communications and Software Defined Radio require robust and generalized decoders with a very good efficiency. This paper aims at introducing a novel and powerful method of implementing a decoder using Support Vector Machines (SVM) to exhibit good performance irrespective of the channel model. The method proposed also ensures a generalization in the design of decoder, which can be easily adaptable for any type of coding technique used. In addition, this method overcomes the demerits of the traditional decoders like Viterbi and other decoders using Neural Networks. The error correction codes like Hamming and Convolutional codes are considered for experimentation. Using SVM, which is a class of machine learning algorithm, this process is viewed as a multi-class classification problem and error correction is achieved in a simpler way. An extensive analysis with regard to the effect of channel and modulation techniques is also made and presented. The proposed SVM model is sufficiently cross validated and found to be an effective replacement for the existing counterparts. © 2009 IEEE.

More »»

2009

Dr. Ramanathan R., Ponmathavan, S., Thaneshwaran, L., A. S. Nair, Valliappan, N., and Dr. Soman K. P., “Tamil font recognition using gabor filters and support vector machines”, in ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies, Trivandrum, Kerala, 2009.[Abstract]


Tamil Font Recognition is one of the Challenging tasks in Optical Character Recognition and Document Analysis. Most of the existing methods for font recognition make use of local typographical features and connected component analysis. In this paper, Tamil font recognition is done based on global texture analysis. The main objective of this proposal is to employ support vector machines (SVM) in identifying various fonts in Tamil. The feature vectors are extracted by making use of Gabor filters and the proposed SVM is trained using these features. The method is found to give superior performance over neural networks by avoiding local minima points. The SVM model is formulated tested and the results are presented in this paper. It is observed that this method is content independent and the SVM classifier shows an average accuracy of 92.5%. © 2009 IEEE.

More »»

2009

Dr. Ramanathan R., A. S. Nair, Thaneshwaran, L., Ponmathavan, S., Valliappan, N., and Dr. Soman K. P., “Robust feature extraction technique for optical character recognition”, in ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies, Trivandrum, Kerala, 2009.[Abstract]


Optical Character Recognition (OCR) is a classical research field and has become one of most thriving applications in the field of pattern recognition. Feature extraction is a key step in the process of OCR, which in fact is a deciding factor of the accuracy of the system. This paper proposes a novel and robust technique for feature extraction using Gabor Filters, to be employed in the OCR. The use of 2D Gabor filters is investigated and features are extracted using these filters. The technique generally extracts fifty features based on global texture analysis and can be further extended to increase the number of features if necessary. The algorithm is well explained and is found that the proposed method demonstrated better performance in efficiency. In addition, experimental results show that the method gains high recognition rate and cost reasonable average running time. © 2009 IEEE.

More »»

2009

Dr. Ramanathan R., A. S. Nair, Sagar, V. V., Sriram, N., and Dr. Soman K. P., “A support vector machines approach for efficient facial expression recognition”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009.[Abstract]


Current scenario in computer vision demands an efficient and robust technique for facial expression recognition. There is also a need for a generalized technique that can even be used for content based image retrieval and analysis. This paper introduces a novel methodology of facial expression recognition using Support Vector Machines. An efficient model is trained and developed using the necessary features extracted by employing 2D Gabor filters. Practically, six different methods for handling the feature vectors are discussed and extensively analyzed in this paper. The developed model is tested and cross validated and the detailed results are presented. It is observed that the proposed method offers a consistent and good accuracy (83.3%) for all the six basic expressions considered. In addition, the implementation complexity is reduced by minimizing the number of support vectors, unlike the traditional counterparts. The proposed method shall definitely turn out to be an effective alternative for the existing methods. © 2009 IEEE.

More »»

2009

Dr. Ramanathan R., Thaneshwaran, L., Viknesh, V., Arunkumar, T., Yuvaraj, P., and Dr. Soman K. P., “A novel technique for english font recognition using support vector machines”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009.[Abstract]


Font Recognition is one of the Challenging tasks in Optical Character Recognition. Most of the existing methods for font recognition make use of local typographical features and connected component analysis. In this paper, English font recognition is done based on global texture analysis. The main objective of this proposal is to employ support vector machines (SVM) in identifying various fonts. The feature vectors are extracted by making use of Gabor filters and the proposed SVM is trained using these features. The method is found to give superior performance over neural networks by avoiding local minima points. The SVM model is formulated tested and the results are presented in this paper. It is observed that this method is content independent and the SVM classifier shows an average accuracy of 93.54%. © 2009 IEEE.

More »»

2009

Dr. Ramanathan R., Ponmathavan, S., Valliappan, N., Thaneshwaran, L., A. S. Nair, and Dr. Soman K. P., “Optical character recognition for English and Tamil using support vector machines”, in ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies, Trivandrum, Kerala, 2009.[Abstract]


Optical Character Recognition is an evergreen area of research and is verily used in various real time applications. This paper proposes a new technique of Optical character Recognition using Gabor filters and Support Vector machines (SVM). This method proves to be very effective with the use of Gabor filters for feature extraction and SVM for developing the model. The model proposed is trained and validated for two languages - English and Tamil and the results are found to be very much encouraging. The model developed works for the entire character set in both the languages including symbols and numerals. In addition , the model can recognise the characetrs of six different fonts in English and Twelve different fonts in Tamil. The average accuracy of recognition for English is 97% and for Tamil it is 84%, which is achieved in just three iterations of training. The method can turn out to be a suitable candidate for future applications in this area. © 2009 IEEE.

More »»

2009

Dr. Ramanathan R., Rohini, P. A., Dharshana, G., and Dr. Soman K. P., “Investigation and development of methods to solve multi-class classification problems”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009.[Abstract]


Most of the classification problems frequently encounter a multi class predicament and offers a good scope for research. This paper has a comprehensive approach to the available multi-class technique using Artificial Neural Networks and then introduces a new algorithm to overcome the demerits of the former. In addition, a new algorithm combining ANN and chameleon clustering is suggested and validated. An SVM model for the above is also proposed and sufficiently tested with a typical example i.e. Image Segmentation. Also, the permutation effects prevailing in Half -against-Half multi class algorithm of SVM is efficiently tackled by developing an algorithm using "circular shift strategy" and employing the same. The use of clustering methods with SVM to improve its efficiency is also discussed. All the above mentioned models are extensively analyzed and the results are presented. It is found that the proposed method is an effective alternative for existing methods and offers consistent performance. © 2009 IEEE.

More »»

Publication Type: Journal Article

Year of Publication Title

2021

Megha. S. Kumar, Dr. Ramanathan R., and Dr. Jayakumar M., “An Investigation of Secret Key Generation for Physical Layer Security Using Wavelet Packets”, Wireless Personal Communications, Springer Publishers, 2021.[Abstract]


This work investigates the effectiveness of wavelet packets in dynamic secret key generation (DSKG) for physical layer security (PLS). Preprocessing channel coefficients before quantization is highly essential in DSKG, as noisy measurements on direct quantization produces distinct keys at the transmitter and receiver. Secret keys generated will be having high key disagreement. The performance of different wavelets namely, Daubechies, Symlet and Coiflet, of orders 3 and 5, are studied using Spearman correlation coefficient, bit disagreement rate and NIST randomness tests. NIST tests are evaluated for different bit sequence lengths and as an outcome of the experiment, the best performing wavelet is identified. Further, the proposed work is compared with an existing scheme. It is inferred that, along with maintaining higher correlation coefficient, wavelet packet based DSKG scheme ensures an enhancement in PLS.

More »»

2021

Megha S. Kumar, Dr. Ramanathan R., Dr. Jayakumar M., and Devendra Kumar Yadav, “Physical layer secret key generation using discrete wavelet packet transform”, Ad Hoc Networks, vol. 118, p. 102523, 2021.[Abstract]


Physical layer secret key generation leveraging reciprocity principle of the wireless channel is a promising substitute for traditional cryptography. However, in certain scenarios, the channel measurements extracted by the wireless transceivers are of high correlation but not similar. Therefore, preprocessing channel measurements prior to quantization is highly essential to facilitate successful generation of shared secret keys at the transceivers. In this paper, we put forth the idea of employing discrete wavelet packet transform (DWPT) for dynamic secret key generation in indoor environments. We propose two schemes which are employed at both the transceivers. Proposed method 1 (Prop. method-1) involves fixing the wavelet packet coefficients of selected terminal nodes in the wavelet packet tree to zero and proposed method 2 (Prop. method-2) involves compression of wavelet packet coefficients of selected terminal nodes. The performance of the proposed methods are evaluated using Pearson correlation coefficient, bit disagreement rate (BDR) and NIST randomness tests. Simulation results demonstrate that, Prop. method-1 performs well in terms of cross-correlation, especially when the measurement error variance is high. In contrast to Prop. method-1, Prop. method-2 renders better randomness at the expense of slightly reduced cross-correlation whilst both methods pass all eight NIST randomness tests. The tradeoff between cross-correlation and randomness can be improved owing to the richer signal analysis offered by DWPT. The simulation results are compared against existing works for validating performance of the proposed methods. Simulation results demonstrate that, DWPT based preprocessing is a highly promising solution for successful physical layer secret key generation.

More »»

2020

K. S. Anusha, Dr. Ramanathan R., and Dr. Jayakumar M., “Link distance-support vector regression (LD-SVR) based device free localization technique in indoor environment”, Engineering Science and Technology, an International Journal, vol. 23, pp. 483 - 493, 2020.[Abstract]


Indoor localization using device free localization (DFL) in wireless sensor networks is gaining momentum nowadays due to the potential benefits of DFL. The techniques used in DFL can be broadly classified as statistical methods, compressive sensing, machine learning, radio tomographic method etc. Whenever loss factor and noise involved in the setup is unpredictable, techniques based on machine learning for target detection improves the result to a greater extend. The adaptability nature of support vector machines eased our choice of machine learning algorithm and support vector machine regression (SVR) is the proposed machine learning approach to address prediction of target position. Proposed link distance-support vector machine (LD-SVR) model uses link distance based DFL of single and multiple targets in indoor environment. Performance of the proposed model using SVR is analysed using parameters mean error and probability distribution function of mean error for various number of nodes and targets by imparting measurement error. The simulation results are found to be very much promising in a 3D room environment. The maximum value of mean error due to measurement error effect on link distance is less than 1 m.

More »»

2020

V. G., Dr. Ramanathan R., and Dr. Jayakumar M., “Convex Optimization Approach to Joint Interference and Distortion Minimization in Energy Harvesting Wireless Sensor Networks”, Arabian Journal for Science and Engineering, Springer Publishers, vol. 45, no. 3, pp. 1669 - 1684, 2020.[Abstract]


In this paper, we solve a problem of interference and distortion minimization as a joint optimization problem in energy harvesting wireless sensor networks with resource allocation constraints. The problem is initially cast as a non-convex problem involving a quadratic sum of ratios. We then transform the problem into convex posed as a sum of difference problem. Further, a solution is obtained via a modified Newton’s method. Numerical simulations for the proposed strategy are conducted, and the parameters analyzed include error variance and energy available for harvesting. The results corroborate the effectiveness of the proposed strategy even with channel estimation errors.

More »»

2019

R. G. Reddy and Dr. Ramanathan R., “Performance analysis of clustering for message classification and congestion control in DSRC/ WAVE-based vehicular ad-hoc networks”, International Journal of Vehicle Information and Communication Systems, vol. 4, no. 1, pp. 55-77, 2019.[Abstract]


Vehicular Ad-Hoc Networks (VANETs) play a significant role in Intelligent Transportation Systems (ITS). The vehicles exchange awareness and safety information with surrounding vehicles using IEEE 802.11p Dedicated Short Range Communications (DSRC) and IEEE 1609 Wireless Access in Vehicular Environment (WAVE)-based short-range communication networks in 5.9 GHz band. These safety messages include periodic beacon messages and event driven emergency messages that are shared in Control Channel (CCH). By collecting these messages and applying clustering we can facilitate new applications like network congestion control, traffic control etc. The partitioning-based clustering methods like k-means and the Partitioning Around Medoids (PAM) are well known in data science. This paper focuses on understanding the message clustering intuitively. The clustering quality is measured using silhouette plot and average silhouette width. The simulation is carried out in OMNeT++ and SUMO-based Veins framework. A simple approach using a package called RInside is explored for fast prototyping of machine learning algorithms in OMNeT++ simulations. © 2019 Inderscience Enterprises Ltd.

More »»

2019

Anusha K. S., Dr. Ramanathan R., and Dr. Jayakumar M., “Device Free Localisation Techniques in Indoor Environments”, Defence Science Journal (DSJ), vol. 69, no. 4, pp. 378-388, 2019.[Abstract]


The location estimation of a target for a long period was performed only by device based localisation technique which is difficult in applications where target especially human is non-cooperative. A target was detected by equipping a device using global positioning systems, radio frequency systems, ultrasonic frequency systems, etc. Device free localisation (DFL) is an upcoming technology in automated localisation in which target need not equip any device for identifying its position by the user. For achieving this objective, the wireless sensor network is a better choice due to its growing popularity. This paper describes the possible categorisation of recently developed DFL techniques using wireless sensor network. The scope of each category of techniques is analysed by comparing their potential benefits and drawbacks. Finally, future scope and research directions in this field are also summarised.

More »»

2018

S. Radhakrishnan and Dr. Ramanathan R., “A Support Vector Machine with Gabor Features for Animal Intrusion Detection in Agriculture Fields”, Procedia Computer Science, vol. 143, pp. 493 - 501, 2018.[Abstract]


Animal intrusion in agricultural fields has been a pestering problem for farmers, especially during monsoon when they try to maximize their yield. This paper puts forth an image processing and machine learning based approach to classify the animal as threat and hence alert the farmer. The image is segmented into parts using Watershed algorithm. The features are extracted from the training set by using 2D Gabor filter bank. Classification is done using Support Vector Machines algorithm. Percentage accuracy for each test image is analyzed. Training set has been increased in a step wise manner in order to find the minimum possible combination of test images and filter bank and hence increase the efficiency of the model compared to the existing models.

More »»

2018

R. Reddy G and Dr. Ramanathan R., “An Empirical study on MAC layer in IEEE 802.11p/WAVE based Vehicular Ad hoc Networks”, Procedia Computer Science, vol. 143, pp. 720 - 727, 2018.[Abstract]


Intelligent Transportation Systems use Vehicular Ad-hoc Networks to improve road safety. Dedicated Short Range Communications (DSRC or IEEE 802.11p) and Wireless Access in Vehicular Environments (WAVE or IEEE 1609 protocol suite) are the two important standards that govern communication in VANETs. However, DSRC based VANETs cannot guarantee to achieve the Quality of Service (QoS) requirements like reliability and latency under high vehicle density scenario due to network congestion. This paper studies the congestion behavior of IEEE802.11p/1609.4 based Medium Access Control by varying vehicle density in urban and highway conditions. Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) is the default medium access mechanism in WAVE MAC. The metrics chosen for evaluating the performance of CSMA/CA are the average end-to-end delay, average throughput, packet delivery ratio, packet loss ratio and the number of packets lost. The simulation is carried out for both urban and highway scenario under varying vehicle density and communication load. The Simulation is performed using Omnet++ and SUMO based veins framework. The simulation results show that under high vehicle density and high communication load, CSMA/CA fails to meet the required QoS.

More »»

2018

V. G and Dr. Ramanathan R., “Parametric Study of RF Energy Harvesting in SWIPT enabled wireless networks under downlink scenario”, Procedia Computer Science, vol. 143, pp. 835 - 842, 2018.[Abstract]


In this paper, we derive and analyze the average Energy Harvested and average achievable downlink rate expressions for the formulated SWIPT enabled system. Rician channel modeling is used for simulation because the distance between Base Station and Users are assumed to be close and thus Line of Sight component is included. After initializing appropriate parameters, definite and accurate expressions and approximate expressions are derived. Results are simulated and analyzed to validate the theory and the derived expressions, by varying efficiency, Rician factor and Path loss exponent.

More »»

2017

Dr. Ramanathan R. and Dr. Jayakumar M., “A Support Vector Regression Approach to Detection in Large-MIMO Systems”, Telecommunication Systems, vol. 64, no. 4, pp. 709 - 717, 2017.[Abstract]


We propose a support vector regression approach for symbol detection in large-MIMO systems employing spatial multiplexing. We explore the applicability of machine learning algorithms, in particular support vector machines, to address one of the recent research problem in communications.The machine learning capability is exploited to achieve fast detection in large dimension systems. The performance of the proposed method is compared with lattice reduction aided detection which is currently the popular choice and the improvement in terms of bit error rate is demonstrated. The sparse formulation of the problem matrix reduces the computational complexity and enables faster detection. The proposed detection algorithm is tailored to address both uncorrelated and correlated channel conditions as well.

More »»

2016

Dr. Ramanathan R. and Dr. Jayakumar M., “A Low Complex Sparse Formulation of Semidefinite Relaxation Detector for Large-MIMO Systems Employing BPSK Constellations”, Wireless Personal Communications, vol. 90, no. 3, pp. 1317–1329, 2016.[Abstract]


Semidefinite relaxation detector is a promising approach to large-MIMO detection but for its computational complexity. The major computational cost is incurred in solving the semidefinite program (SDP). In this paper, we propose a sparse semidefinite relaxation (S-SDR) detector by reformulating the SDP problem thereby reducing the computational complexity. We formulate the system model using a sparse approach and further introduce a regularization term inducing sparsity into the semidefinite programming model. We provide a sparse formulation requiring approximately 50 % of the computations compared to the conventional semidefinite programming approach. We apply the proposed semidefinite relaxation detector in large-MIMO channels upto 100×100 systems and compare its BER performance and complexity. We observe that the BER performance is similar to the conventional semidefinite relaxation with the proposed S-SDR detector requiring relatively fewer computations.

More »»

2015

N. S., S., T., and Dr. Ramanathan R., “Investigation of PAPR in discrete wavelet transform based multi-carrier systems”, International Journal of Engineering and Technology, vol. 7, no. 5, pp. 1625-1632, 2015.[Abstract]


The objective of the paper is to formulate a measure to reduce PAPR problem in Orthogonal Frequency Division Multiplexing. To mitigate the problem of PAPR, a Discrete Wavelet Transform based system is employed instead of conventional OFDM. For the comparative study, the PAPR in conventional OFDM is analyzed for varying number of subcarriers and for different channel taps. The result of conventional OFDM is compared with wavelet based OFDM, employing wavelets namely - 'Haar', 'Daubechies', 'Symlets' and 'Biorthogonal' wavelets. Further the PAPR is analyzed for varying levels and different length of channel impulse response. The simulation results show that wavelet based OFDM has less PAPR than conventional OFDM. With the increase in the number level, the PAPR at the demodulator side decreases in the wavelet based OFDM.

More »»

2015

S. M. and Dr. Ramanathan R., “Performance evaluation of DWT based multicarrier systems over frequency selective channels”, International Journal of Engineering and Technology, vol. 7, no. 5, pp. 1651-1658, 2015.[Abstract]


In this work, the performance of DWT based OFDM is studied and compared it with conventional FFT based OFDM over frequency selective channels in different test environments. The Bit Error Rate (BER) estimation is done to evaluate the performance of both the systems. In DWT based OFDM, different wavelet families such as haar, daubechies, coiflet and biorthogonal were used with different levels of decomposition. The simulation results show that in all channels, DWT based OFDM requires less SNR value to achieve the minimum BER of 10-3, when compared to conventional FFT based OFDM. Therefore, DWT based OFDM can be used in place of FFT based OFDM with high bandwidth efficiency.

More »»

2015

K. M.S., S., P., and Dr. Ramanathan R., “Performance evaluation of DWT based multicarrier system in time varying channels”, International Journal of Engineering and Technology, vol. 7, no. 5, pp. 1633-1641, 2015.[Abstract]


With an increase in user mobility, data rate and carrier frequencies we have to consider time variant channels. In order to overcome the impairments of the time varying channel on conventional OFDM system, a wavelet based OFDM system is investigated in place of FFT based system and its BER performance is analyzed for different Doppler frequencies. The results show that DWT based OFDM gives better performance compared to conventional OFDM system.

More »»

2015

Dr. Ramanathan R. and Dr. Jayakumar M., “A novel cuckoo search approach to detection in spatially correlated MIMO channels”, International Journal of Mathematical Modelling and Numerical Optimisation, vol. 6, no. 2, pp. 101-113, 2015.[Abstract]


In this paper, we propose a cuckoo search approach to detect the transmitted symbols in spatially correlated multiple input multiple output (MIMO) channels. Detection is considered to be a challenging task in correlated channels due to the fact that the channel matrix tends to be ill conditioned or sometimes rank deficient. Currently, lattice reduction aided detection is understood to be the best approach for detection in spatially correlated channels. We propose cuckoo search as an effective approach to solve this problem. We provide the performance comparison of the proposed detector with various other detectors including lattice reduction aided detector. Through the results, we demonstrate the efficiency of cuckoo search detector over other detectors in uncorrelated and correlated channels as well. We corroborate that cuckoo search detector is a better choice over other existing detectors especially in spatially correlated MIMO channels.

More »»

2015

Dr. Ramanathan R. and Dr. Jayakumar M., “A Performance Study of Semidefinite Relaxation Detector in Spatially Correlated and Rank Deficient Large MIMO Systems”, Wireless Personal Communications, vol. 83, no. 4, pp. 2883-2897, 2015.[Abstract]


Large MIMO detection has gained significant attention in the recent past with computational complexity as the research focus. However, they assume the channel to be i.i.d and uncorrelated, which is not a valid assumption in practice due to the fixed physical space constraints in large MIMO. Nevertheless, there is a little work carried out in these lines. In this paper, we consider the problem of detection in large spatial multiplexing MIMO systems and we investigate the semidefinite relaxation (SDR) approach to solve this problem. We investigate the applicability of SDR approach in large MIMO setting and study its performance in spatially correlated and rank deficient channel conditions. Through the simulation results, we demonstrate the superior performance of semidefinite relaxation detector over other existing methods in uncorrelated and correlated large MIMO systems especially in low SNR regime. The performance of SDR detector is noteworthy with large number of antennas despite the system being rank deficient and the average running time also scales up well for large systems. © 2015, Springer Science+Business Media New York.

More »»

2010

Dr. Ramanathan R. and Dr. Soman K. P., “A Novel Methodology for Designing Linear Phase IIR Filters”, Aceee International Journal on Communication, vol. 1, 2010.[Abstract]


This paper presents a novel technique for designing an Infinite Impulse Response (IIR) Filter with Linear Phase Response. The design of IIR filter is always a challenging task due to the reason that a Linear Phase Response is not realizable in this kind. The conventional techniques involve large number of samples and higher order filter for better approximation resulting in complex hardware for implementing the same. In addition, an extensive computational resource for obtaining the inverse of huge matrices is required...

More »»

Publication Type: Conference Proceedings

Year of Publication Title

2018

C. S. Pradeep and Dr. Ramanathan R., “An improved technique for Night-time Vehicle detection”, 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, Bangalore, India, 2018.[Abstract]


Autonomous vehicles are mainly dependent on Advanced Driver Assistance System (ADAS). One of the most important feature in ADAS is vehicle detection. There are many methods for vehicle detection at day time. However, during night-time vehicle detection, ADAS has to depend solely on tail-light of the vehicles ahead. Street lights and other bright lights are of major concern in this scenario. In developing countries like India, vehicles with only one functional tail-light are also allowed on road. In this paper, we propose two improvised methods for nighttime vehicle detection using forward facing optical camera. First method is for improving accuracy in dual tail-light functional case and the other for improving accuracy in single tail-light scenario. Vehicle with only one functional tail-light were detected using non-divergent optical flow points clustered with the functional tail-light. The proposed algorithm has been tested in actual traffic scenarios.

More »»

2010

M. Chinnam, Madhusudhan, J., Nandhini, C., Prathyusha, S. N., Sw, S., and Dr. Ramanathan R., “Signal Detection in Software Defined Radar”, Second National Conference on Recent Trends in Communications, Computing and Signal Processing. Coimbatore, pp. 71 – 74 , 2010.

2009

Dr. Ramanathan R. and , “Design and Analysis of Integrated Tunable Band Pass Filters for Phased Array Radar Receiver front ends”, National workshop on Design and Analysis of Radar Systems,DARS 2009. ISRO, Bangalore, 2009.

2009

Dr. Ramanathan R. and , “Artificial Neural Network Approach to the Design of Band Pass Filters for Integrated Wireless Transceivers”, First National Conference on Recent Trends in Communications, Computing and Signal Processing. Coimbatore, pp. 53 – 56, 2009.

2008

Dr. Ramanathan R. and , “Investigation of Reconfigurable Slot Antennas for WLAN Applications”, The National Conference on Broad Band Technologies (BROADBAND-08). Mar Baselios College of Engineering and Technology, Thiruvananthapuram, 2008.

2008

Dr. Ramanathan R. and , “Design Analysis of Printed Dual- Band Antenna for Wireless Application”, The Fourth National Conference on Recent Trends in Communication Techniques, NATCON -08. Nagercoil, 2008.

2008

Dr. Ramanathan R. and , “Novel Technique for Designing a Planar Antenna for Broadband applications”, National Conference on VLSI, Embedded Systems, Signal Processing and Communication Technologies (NCESCOM 08). Chennai, 2008.

2008

Dr. Ramanathan R. and , “Design and Analysis of Compact and Highly Selective Band Pass Filter for use in non invasive Bio Medical sensing using Ultra Wide Band Communications and Radar Technology”, National Symposium on Instrumentation (NSI 33). Instrument Society of India, Vishakhapatnam, 2008.

2008

Dr. Jayakumar M., Dr. Ramanathan R., and Sabarish Narayanan B., “Air Substrate Based Shorted Rectangular Patch for Air Borne Vehicles”, International Conference on Aerospace Science and Technology (INCAST -2008). National Aerospace Laboratories, Bangalore, p. 139, 2008.

Publication Type: Book

Year of Publication Title

2012

Dr. Soman K. P. and Dr. Ramanathan R., Digital Signal and Image Processing-The Sparse Way, 1stEditionst ed. Elsevier India, 2012, p. 480.[Abstract]


Digital Signal Processing Is Everywhere, It Is Pervasive And Ubiquitous. Its Methodologies Are Evolving And Spreading Its Wings Into Many Exciting New Directions Such As Networking, Bioinformatics, Digital Security And Forensics, And Spoken Language. As A Technology, It is a Phantom Technology Which Is Working From Behind The Scenes To Make Most Of Modern Day Devices Work. Designed For Both Undergraduate And Post Graduate Courses, This Book Provides A Comprehensive Insight Into The Linear Algebra And Optimization View Of Signal Processing That Can Be Readily Extended To Advanced Image Processing, Wavelet Theory And Compressive Sensing. This Book Shows How The Entire Class Of Problems In Signal And Image Processing Can Be Put In A Linear Algebra And Optimization Framework.

More »»

Citations