Date of Award


Publication Type

Master Thesis

Degree Name



Electrical and Computer Engineering

First Advisor

Shahrrava, Behnam


Bayesian Estimation, Carrier Frequency Offset, Detection, Maximum Likelihood, Rayleigh Fading, Space Time Block Coding




In multi-antenna communication systems, signal detection is significantly affected by the presence of channel fading and the introduction of Carrier Frequency Offset (CFO) during signal demodulation. The conventional solution is to estimate the Channel State Information (CSI) and CFO and apply estimates in a detector metric that assumes perfect knowledge of CSI and CFO. This thesis proposes new metrics for Space-Time Block decoding with noisy CSI and CFO estimates by including the error variance of CSI and CFO estimates in the metric derivation.The BER performance of the conventional metric and proposed metrics, both using Joint Maximum A Posteriori (MAP) CSI/CFO estimates shows that the former slightly outperforms the latter and their performances converge at high SNR values. However, under worse-case scenarios, the proposed metrics outperform the conventional metric.We conclude that the joint MAP estimator/conventional metric combination is more appropriate for signal detection due to its relatively low complexity.