V. Nagendra Babu ¹, V. Adinarayana ¹, K. Muralikrishna ², P. Rajesh Kumar ³

Affiliations
1 Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530049, Andhra Pradesh, IN
2 Department of ECE, ANITS Engineering College, Visakhapatnam - 531162, Andhra Pradesh, IN
3 Department of ECE, A.U College of Engineering, Andhra University, Visakhapatnam - 530003, Andhra Pradesh, IN

Abstract

In this paper, we proposed an improved recovery algorithm, with efficient pilot placement, for Compressed Sensing (CS)-based sparse channel estimation based on Sparsity Adaptive Matching Pursuit (SAMP) in Orthogonal Frequency Division Multiplexing (OFDM) communication systems. The proposed algorithm does not require a priori knowledge of the sparsity, and to approach the true sparsity, adjusts the step size adaptively. Furthermore, estimation accuracy can be affected by different measurement matrices in CS, due to different pilot arrangements. It is known that, the Cyclic Difference Set (CDS) is the optimal setoff pilot locations when the signal is sparse on the unitary Discrete Fourier Transform (DFT) matrix by minimizing the mutual coherence of the measurement matrix. Based on this, an efficient pilot insertion scheme is introduced in cases where Cyclic Different Set does not exist. Simulation results in the paper show that the channel estimation algorithm, with the new pilot placement scheme, which offers a better trade-off between the performances in terms of Bit Error Rate (BER), Mean Squared Error (MSE) and the complexity, when compared to previous estimation algorithms.

Keywords

Compressed Sensing, Cyclic Difference Set, Sparse Channel Estimation, Sparsity Adaptive Matching Pursuit.

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D. Sanjay ¹, P. Rajesh Kumar ², T. Satya Savithri ³

Affiliations
1 Department of ECE, B.V. Raju Institute of Technology, Narsapur, Medak – 502313, IN
2 Department of ECE, JNTU College of Engineering, Hyderabad – 500085, IN
3 Department of ECE, P.V.P. Siddhartha Institute of Technology, Vijayawada – 520007, IN

Abstract

Robotic systems perform various tasks using image processing techniques. This paper proposes a fuzzy logic controlled robotic system for person follower behavior in an indoor environment. The robot platform used here is from National Instruments which has 120 degree rotating ultrasonic sensor and a Single-Board Reconfigurable Input-Output (SBRIO). The board has a Field Programmable Gate Array (FPGA) device and real time controller which is interfaced to an Internet Protocol (IP) camera. The robot motion is controlled using a fuzzy logic based algorithm. Higher momentum and soft control are some benefits of using fuzzy logic controller when compared to binary logic, as it assigns variable speeds to wheels. The image captured from the camera is processed using Optical Character Recognition (OCR) method and the ultrasonic sensor is used to measure the distance, avoid the obstacles. The design is done using NI-LabVIEW and the experimental results of this approach shows fast response of the robot to follow a person in a smooth manner.

Keywords

FPGA, Fuzzy control, Robot, Ultrasonic sensor

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