Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : LMS

A Proposed Channel Estimation Based on Enhanced Sub-carrier Index Modulation and Packet-Discrete Wavelet Transform to Minimize Bit Error Rate

Ansam S. Jabbar

Engineering and Technology Journal, 2021, Volume 39, Issue 10, Pages 1506-1513
DOI: 10.30684/etj.v39i10.2206

For Orthogonal Frequency Division Multiplexing (OFDM) and other communication systems, many estimating approaches have been developed to estimate the channel state information and lower the Bit Error Rate (BER). These estimating methods, however, are still subject to the influence of large peak powers compared to average powers. Reduced computational complexity is one of the most significant factors to consider while developing a new estimate algorithm. This study aims to provide a novel design of the Packet-Discrete Wavelet Transform (P-DWT) algorithm for channel estimation in wireless OFDM instead of the fast Fourier transform (FFT). It is presented to retrieve the code of a spread spectrum signal and transmitted data bits, and it is compared to particle swarm optimization PSO and least mean square (LMS) optimization. The suggested approach reduces the computing cost of DWT by recognizing the Packet Wavelet Transform (PWT) coefficients and local points, findings utilizing P-DWT channels generated from both models and measurements show that the proposed technique outperforms pilot-based channel estimation in terms of bit error rate under sparseness conditions BER. Moreover, as compared to typical semi-blind approaches, the estimation accuracy is enhanced while computing cost is reduced.

Channel Equalization Using Wavelet Denoising

M. H. Miry

Engineering and Technology Journal, 2007, Volume 25, Issue 9, Pages 1081-1091

A problem in digital signal transmission occurs when a signal in one
signal interval overlaps the signal in an adjacent interval. This problem is called
intersymbol interference and limits the speed of digital transmission. Interference
and noise are common in communication channels, and the recovery of
transmitted signals may be a difficult task. The adaptive equalizer which is used
to recover the transmitted signals and LMS algorithm which is one of the most
efficient criteria for determining the values of the adaptive equalizer coefficients
are very important in communication systems, but the LMS adaptive equalizer
suffers response degrades and slow convergence rate under low Signal-to- Noise
ratio (SNR) condition. The present work is concerned with the development and
application of wavelet transform based denoising technique for improving the
response and convergence rate of LMS adaptive equalizer in digital
communication systems under low SNR.