Abstract

Random access is a commonly used multiple access scheme that allows multiple users to share the same resource in a distributed fashion. In a Universal Mobile Telecommunication System (UMTS), the preamble of a random access channel (RACH) message is used by a mobile user to signal the base station for requesting network access or short data packets transportation. The base station is responsible in a timely fashion for detecting the preambles and informing the user whether the request has been granted or denied through the acquisition indication channel (AICH). Preamble detection is one of the most computationally intensive functional units of a base station. It has attracted many research attentions and investments in the past a few decades. The drawback of the existing preamble detection (PD) algorithms for UMTS base-station is that either their computational complexity is high or the detection accuracy is low. The conventional full search PD algorithm gives the best result in terms of the detection probability, but its complexity is high. On the hand, the parallel-serial code phase detector PD algorithm provides a reduced computational complexity, but the detection accuracy becomes low. In this thesis, a sample-decimation based preamble detection technique is proposed in order to substantially reduce the computational complexity and at the same time retain a high detection accuracy. The proposed algorithm comprises two stages. Delay hypotheses or delay offsets which are unlikely to have a strong correlation power between the antenna samples and the locally generated preamble replica are identified and discarded in the first stage. The second stage operates on the remaining offsets and employs all the antenna samples within the preamble signal. Extensive computer simulations are conducted under different levels of additive white Gaussian noise interferences. The results show that the proposed algorithm has a detection performance very close to that of the conventional full search PD algorithm, while at the same time it reduces the computational complexity by more than sixty percent