Zone based GLRT for detecting physical random access channel signals in 5G
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In LTE/5G systems, the random access channel (RACH) process occurs during the boot-up phase. As channel state information is not available at this stage, detecting several devices with high performance presents a challenging problem. In particular, servicing many devices simultaneously can get difficult when a large number of user equipment and machines exist in the network. The problem can become more dramatic as the number of user equipment increases around the world. In the literature, power delay profile (PDP) is proposed as a decision metric for this problem. The use of this metric handles many cases with satisfactory performance and low complexity; however, it does not lead to optimal detection performance. In this thesis, we address this issue with a generalized likelihood ratio test (GLRT) based approach and propose detectors with high detection performance. We also derive an ideal detector that provides an upper bound on the detection probability. Via extensive RACH simulations, it is shown that improvements in detection performance can be achieved by the proposed approach in various scenarios.