1 research outputs found
Advances in parameter estimation, source enumeration, and signal identification for wireless communications
Parameter estimation and signal identification play an important role in modern wireless
communication systems. In this thesis, we address different parameter estimation
and signal identification problems in conjunction with the Internet of Things (IoT),
cognitive radio systems, and high speed mobile communications.
The focus of Chapter 2 of this thesis is to develop a new uplink multiple access
(MA) scheme for the IoT in order to support ubiquitous massive uplink connectivity
for devices with sporadic traffic pattern and short packet size. The proposed uplink
MA scheme removes the Media Access Control (MAC) address through the signal
identification algorithms which are employed at the gateway.
The focus of Chapter 3 of this thesis is to develop different maximum Doppler
spread (MDS) estimators in multiple-input multiple-output (MIMO) frequency-selective
fading channel. The main idea behind the proposed estimators is to reduce the computational
complexity while increasing system capacity.
The focus of Chapter 4 and Chapter 5 of this thesis is to develop different antenna
enumeration algorithms and signal-to-noise ratio (SNR) estimators in MIMO timevarying
fading channels, respectively. The main idea is to develop low-complexity
algorithms and estimators which are robust to channel impairments.
The focus of Chapter 6 of this thesis is to develop a low-complexity space-time
block codes (STBC)s identification algorithms for cognitive radio systems. The goal
is to design an algorithm that is robust to time-frequency transmission impairments