Beta
23534

Performance of Adaptive MMSE Receivers Using Aided Tentative Coefficients in Flat Fading Channels

Article

Last updated: 04 Jan 2025

Subjects

-

Tags

-

Abstract

The conventional matched filter (MF) receiver is considered the optimum filter to recover the CDMA signals. One of the problems of the MF is that its performance is significantly degraded due to the channel impairments and the increase of the multiple access interference (MAI). In this paper, an adaptive minimum mean square error-maximum likelihood (MMSE-ML) receiver is introduced to overcome this problem. This receiver uses two sets of adaptive coefficients to increase the ability of tracking the time variations of the channel. The performance of the receiver is measured in terms of bit error rate (BER) and compared with other receivers over flat fading channel. It is found that the performance of the
adaptive MMSE-ML receiver is much better than the performance of the other receivers in the flat fading channel.

DOI

10.21608/asat.2009.23534

Keywords

Code division multiple access (CDMA), minimum mean square error-maximum likelihood (MMSE-ML), matched filter (MF)

Authors

First Name

Khairy

Last Name

Elbarbary

MiddleName

A.

Affiliation

Egyptian Armed Forces.

Email

-

City

-

Orcid

-

Volume

13

Article Issue

AEROSPACE SCIENCES & AVIATION TECHNOLOGY, ASAT- 13, May 26 – 28, 2009

Related Issue

4377

Issue Date

2009-05-01

Receive Date

2019-01-03

Publish Date

2009-05-01

Page Start

1

Page End

12

Print ISSN

2090-0678

Online ISSN

2636-364X

Link

https://asat.journals.ekb.eg/article_23534.html

Detail API

https://asat.journals.ekb.eg/service?article_code=23534

Order

37

Type

Original Article

Type Code

737

Publication Type

Journal

Publication Title

International Conference on Aerospace Sciences and Aviation Technology

Publication Link

https://asat.journals.ekb.eg/

MainTitle

Performance of Adaptive MMSE Receivers Using Aided Tentative Coefficients in Flat Fading Channels

Details

Type

Article

Created At

22 Jan 2023