Estimation of uplink parameters in cloud radio access networks

Abstract

In this dissertation, we consider the estimation of uplink parameters and the optimization of fronthaul compression in the cloud-radio access networks (C-RANs)considering the non-orthogonal multiple access. In order to obtain performance gain through centralized processing of central unit (CU), the exact detection of the user activity and its precise channel information are required, as well as synchronization must be preceded. The imperfect channel information and imperfect synchronization causes degradation of performance of C-RANs significantly. In addition, we should consider key limitations of C-RANs, which are the limited capacity of the fronthaul link and the potentially significant latency need for the transfer and processing of the baseband signals on the fronthaul link. Therefore, this dissertation discusses several nobel techniques that effectively address these issues. First of all, we deal with the problem of channel estimation in the uplink of sparse code multiple access systems. To do this, we introduce a sparse pilot structure based on the factor graph matrix and provide an optimal pilot allocation for the sparse pilot structure in terms of mean square error. The least-square algorithm and interpolation are used for channel estimation. The proposed scheme has the benefit of training overhead reduction and low-complexity compared with the conventional scheme. Next, regarding the fronthaul compression of C-RANs, we present an effective compression method of training signal with the aim of enhancing the performance of time and phase synchronization at the CU. To this end, the effect of the synchronization error on the signal to noise ratio is analyzed by adopting the Cramer-Rao bound. The resulting proposed algorithm is based on the Charnes-Cooper transformation and the Difference of Convex approach. Numerical results show that optimized fronthaul compression outperforms conventional solution that do not account for the impact of synchronization errors. Regarding the activity detection problem with the fronthaul latency, we propose two baseline schemes based on retransmission. By considering the problem of fronthaul latency, we develop a local activity detection performed at each remote radio head, which results in a benefit of low-latency due to local feedback.