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On performance analysis of optimal diversity combining with imperfect channel estimation

Abstract

dc:description.abstract

The optimal diversity combining technique is investigated for multipath Rayleigh and Ricean fading channel with additive white Gaussian noise where only imperfect channel knowledge is available at the receiver. The non-observable estimation error contributes as an additive source of noise which is not white. Therefore, the optimal combining weight is derived taking into consideration the imperfect channel knowledge. The bit error rate for BPSK modulation over correlated Rayleigh and Ricean fading channel is derived for minimum mean square channel estimation using pilot symbol assisted modulation. Analytical result and Monte-Carlo simulation are presented for specific channel and estimation models to demonstrate the effect of diversity combining with imperfect channel estimation on error performance in comparison with the case when perfect channel knowledge is available at the receiver. The trade-off between the channel estimation accuracy and the effective bit SNR is also discussed. The Pilot-to-Data power ratio is studied for different Rice K factors for optimizing the bit error performance.

Degree

thesis:*
Name thesis:degree_name
Master of Science in Electrical Engineering - (M.S.)
Discipline thesis:degree_discipline
Electrical and Computer Engineering
Year
2005

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Peng, Yong
Contributors dc:contributor
  • Roy R. You
  • Hongya Ge
  • Sirin Tekinay

Subjects

dc:subject × 3

Identifiers

dc:identifier.*
Repository record dc:identifier
https://digitalcommons.njit.edu/theses/481
OAI identifier oai:identifier
oai:digitalcommons.njit.edu:theses-1480

Chain of custody

source
Harvested from
NJIT
Base URL
digitalcommons.njit.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Peng, Yong. On performance analysis of optimal diversity combining with imperfect channel estimation. 2005. https://digitalcommons.njit.edu/theses/481