Blind channel estimation in LTE uplink system using variable step size based LMS algorithm

Rana, Md. Masud; Kim, Dong Ha; Cho, Won‐Kyung

doi:10.1109/coin.2010.5546407

Cited by 2 publications

(1 citation statement)

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“…Finally, theses algorithms have been employed across a variety of applications in the wireless communication systems, including parameter estimation as well as data detection and equalization for linear and nonlinear channels. Up to date, these algorithms are still considered open topics to researchers, since they provide acceptable performance and complexity while error and latency mainly depend on optimization techniques used [16].…”

Section: -mentioning

confidence: 99%

A Comprehensive Review on Various Estimation Techniques for Multi Input Multi Output Channel

Althahab¹,

Alrufaiaat

2019

JUBES

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The problem of wireless channel estimation has been evolving due to some undesirable effects of channel physical properties on transmitted signals. At the receiver end, distortions, delays, attenuations, interferences, and phase shifts are the most issues encounter together with the received signals. In order to overcome channel effects and provide almost a perfect quality of data transmission, channel parameter estimation is needed. In Multiple Input-Multiple Output systems (MIMO), channel estimation is a more complicated step as compared with the Single Input-Single Output systems, SISO, because of the fact that the number of sub-channels that needs estimate is much greater than SISO systems. The fundamental objective of this research paper is to go over the famous and efficient algorithms that have been innovated to solve the problem of MIMO channel estimation in wireless communication systems. In this paper, these techniques have been classified into three groups: non-blind, semi-blind and blind estimation. For each group, a brief illustration is presented for familiar estimation algorithms. Finally, we compare between these techniques based on computational complexity, latency and estimation accuracy.

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Section: -mentioning

confidence: 99%