Phd - ECE





The faculty of Electronics and Communication Engineering Department are doing their research in following titles

Frequency selective surfaces (FSS) for Electromagnetic Shielding

Frequency selective surfaces (FSS) are planar periodic arrays of metal patches or slots that function as filtering elements for free-space radiation. They are widely used as antenna reflectors, absorbers, high-impedance surfaces, electromagnetic band-gap materials, and electromagnetic shields in the microwave and millimeter-wave regimes. This research work focuses on Application of FSS in EM Shielding. While designing the metallic enclosure for the electromagnetic shielding of electronic circuits, apertures on the enclosure walls become unavoidable for the purpose of signal cabling and ventilation. The Conventional Enclosure design involves a repeated procedure where the whole position and locations are varied until the Shielding Effectiveness (SE) requirements met. By designing enclosure walls with FSS array, a systematic approach can be adopted which reduces the design time.

Some Investigations on Channel Estimation Techniques in Multiband OFDM Systems

The performance of the OFDM channel model using Least Square (LS) and Minimum Mean Square Error (MMSE) channel estimation methods. Since these channel estimation techniques are pilot based, the throughput of the system is low by sending pilots at regular intervals. Recursive Least Square (RLS) and Kalman algorithm are proposed for Blind channel estimation to estimate the channel efficiently at the OFDM receiver. In the proposed RLS method, the channel parameters are estimated from the correlation matrix of the received signal vector. To get a better channel estimates in the frequency domain, Kalman filter based channel estimation is proposed. The scalar Kalman filtering algorithm that can be used to get a refined estimation of channel responses in frequency domain. The Kalman gain is calculated with the knowledge of posterior and prior channel estimation. In this investigation, it is found that the Kalman algorithm provides better results than RLS algorithm in terms of Bit Error Rate (BER) and Mean Square Error (MSE) and also a different modulation techniques and pilot density patterns have been analyzed in MB OFDM systems.

Power Optimization in Memory Cells

A novel family of asymmetric dual-Vt static random access memory cell designs that reduce leakage power in caches while maintaining low access latency. These designs exploit the strong bias toward zero at the bit level exhibited by the memory value stream of ordinary programs. Compared to conventional symmetric high-performance cells, our cells offer significant leakage reduction in the zero state and, in some cases, also in the one state, albeit to a lesser extent. A novel sense amplifier, in combination with dummy bitlines, allows for read times to be on par with conventional symmetric cells. With one cell design, approximately the leakage is reduced by 7× (in the zero state) with no performance degradation.

Synchronization and On-Chip Signal Integrity of 3D IC’s

Three Dimensional integration has great potential to advance computational power and functionality of modern integrated systems. Reliable communication is an important requirement for 3D circuits. Synchronization and signal integrity issues play vital role to implement reliable communication. Clock distribution networks in 3D IC’s are going to be investigated to reduce interconnect latency and also power distribution networks are to be analyzed to reduce the computational power.

Performance Evaluation of Image Quality and Diagnostic Accuracy in Breast Tomo-synthesis with Digital Mammography

Breast cancer is an uncontrolled growth of abnormal cell in the breast. As with the other forms of the cancer, Breast cancer is considered to be the result of malfunctioning DNA due to damage or Inherited mutation. Digital mammography involves producing X-Ray Images of the breast and storing them directly to the machine in electronic form. Academic research also plays a significant role in the development of digital mammography and CAD Systems.

A SWARM Optimization Approach for Flexible Flow Shop Scheduling with Multiprocessor Task

In simple flow shop problems, each machine operation centre includes just one machine. If at least one machine centre includes more than one machine, the scheduling problem becomes a flexible flow shop problem (FFSP). Flexible flow shop scheduling problems have a special structure combining some elements of both the flow shop and the parallel machine scheduling problems. FFSP can be stated as finding a schedule for a general task graph to execute on a multiprocessor system so that the schedule length can be minimized. In my research, a particle swarm optimization (PSO) algorithm to solve FFSP. PSO is an effective algorithm which gives quality solutions in a reasonable computational time and consists of less numbers parameters. Mutation, a commonly used operator in genetic algorithm, has been introduced in PSO so that trapping of solutions at local minima or premature convergence can be avoided. Logistic mapping is used to generate chaotic numbers in this paper. Use of chaotic numbers makes the algorithm converge fast towards near-optimal solution and hence reduce computational efforts further. The performance of schedules is evaluated in terms of total completion time or makes span (Cmax).