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Ezmin Abdullah

Researcher at Universiti Teknologi MARA

Publications -  20
Citations -  84

Ezmin Abdullah is an academic researcher from Universiti Teknologi MARA. The author has contributed to research in topics: Orthogonal frequency-division multiplexing & Computer science. The author has an hindex of 3, co-authored 16 publications receiving 60 citations.

Papers
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Journal Article

Papr reduction using scs-slm technique in stfbc mimo-ofdm

TL;DR: The utilization of circulant shift codeword from SCS technique with multiplication of phase factor of SLM technique in preparing several candidates for interleaving technique is proposed in MIMO-OFDM system for PAPR and BER performance improvement.
Proceedings ArticleDOI

Comparison between LDPC codes and QC-LDPC codes in term of PAPR in OFDM system with different encoding techniques

TL;DR: A comparison between two coding; Low Density Parity Check Codes (LDPC) codes and Quasi Cyclic LDPC (QC-LDPC] codes has been discussed and additionally two types of encoding technique; G-Matrix and Approximate Triangular that is used in LDPC/QC -LDPC has been compared.
Proceedings ArticleDOI

Boost Converter of Maximum Power Point Tracking (MPPT) Using Particle Swarm Optimization (PSO) Method

TL;DR: In this paper, the simulation of the PV energy conversion method based on MPPT algorithm based on particle swarm optimization (PSO) is presented, which is fast, adjustable, accurate, and efficient for full tracking of PV power.
Proceedings ArticleDOI

Performance Analysis of Radio Propagation Models in VANET Application

TL;DR: In this paper, the performance analysis of radio propagation model (RPM) in VANET has been studied and the best performance of RPM has been identified by observing packet loss, throughput and average end-to-end delay between vehicles by implementing different type of RPMs.
Proceedings ArticleDOI

Performance Analysis of Cross-Entropy Stopping Criterion for Quadrature Amplitude Modulation

TL;DR: The cross-entropy stopping criterion with binary phase-shift keying can perform well at high sound-to-noise ratio regions in additive white Gaussian noise (AWGN) but is poor in average iteration number (AIN) at a high noisy channel while it can terminate early at a low noisy channel.