Fronthaul Compression and Precoding Design for C-RANs over Ergodic Fading Channel

This work investigates the joint design of fronthaul compression and precoding for the downlink of Cloud Radio Access Networks (C-RANs). In a C-RAN, a central unit (CU) performs the baseband processing for a cluster of radio units (RUs) that receive compressed baseband samples from the CU through low-latency fronthaul links. Most previous works on the design of fronthaul compression and precoding assume constant channels and instantaneous channel state information (CSI) at the CU. This work, in contrast, concentrates on a more practical scenario with block-ergodic channels and considers either instantaneous or stochastic CSI at the CU. Moreover, the analysis encompasses both the Compression-After-Precoding (CAP) and the Compression-Before-Precoding (CBP) schemes. With the CAP approach, which is the standard C-RAN solution, the CU performs channel coding and precoding and then the CU compresses and forwards the resulting baseband signals on the fronthaul links to the RUs. With the CBP scheme, instead, the CU does not perform precoding but rather forwards separately the information messages of a subset of mobile stations (MSs) along with the compressed precoding matrices to the each RU, which then performs precoding. Optimization algorithms over fronthaul compression and precoding for both CAP and CBP are proposed that are based on a stochastic successive upper-bound minimization approach. Via numerical results, the relative merits of the two strategies under either instantaneous or stochastic CSI are evaluated as a function of system parameters such as fronthaul capacity and channel coherence time.Comment: 25 pages, 9 figures, Submitted to IEEE Transactions on Vehicular Technolog

Layered Downlink Precoding for C-RAN Systems with Full Dimensional MIMO

The implementation of a Cloud Radio Access Network (C-RAN) with Full Dimensional (FD)-MIMO is faced with the challenge of controlling the fronthaul overhead for the transmission of baseband signals as the number of horizontal and vertical antennas grows larger. This work proposes to leverage the special low-rank structure of FD-MIMO channel, which is characterized by a time-invariant elevation component and a time-varying azimuth component, by means of a layered precoding approach, so as to reduce the fronthaul overhead. According to this scheme, separate precoding matrices are applied for the azimuth and elevation channel components, with different rates of adaptation to the channel variations and correspondingly different impacts on the fronthaul capacity. Moreover, we consider two different Central Unit (CU) - Radio Unit (RU) functional splits at the physical layer, namely the conventional C-RAN implementation and an alternative one in which coding and precoding are performed at the RUs. Via numerical results, it is shown that the layered schemes significantly outperform conventional non-layered schemes, especially in the regime of low fronthaul capacity and large number of vertical antennas.Comment: 29 pages, 12 figures, Submitted to IEEE Transactions on Vehicular Technolog

Radio resource management for high-speed wireless cellular networks

The fifth-generation (5G) wireless cellular system, which would be deployed by 2020, is expected to deliver significantly higher capacity and better network performance compared to those of the current fourth-generation (4G) system. Specifically, it is predicted that tens of billions of wireless devices will be connected to the wireless network over the next few years, which results in an exponential explosion of mobile data traffic. Therefore, more advanced wireless architecture, as well as radical and innovative access technologies, must be proposed to meet this urgent increasing growth of mobile data and connectivity requirements in the coming years. Toward this end, two important wireless cellular architectures, namely wireless heterogeneous networks (HetNets) based on the dense deployment of small cells and the cloud radio access networks (C-RANs) have been proposed and actively studied by both academic and industry communities. Besides enabling a lot of advantages in increasing network coverage as well as end-to-end system throughput, these two novel network architectures have also raised some novel technical challenges and opened exciting research areas for further research. Motivated by the aforementioned technical challenges, the general objective of this Ph.D. research is to develop efficient radio resource allocation and interference management algorithms for the future high-speed wireless cellular networks. In particular, we have developed various efficient resource allocation algorithms for reducing the transmission power and increasing the end-to-end network throughput for both HetNets and C-RANs. Furthermore, extensive numerical results are presented to gain further insights and to evaluate the performance of our resource allocation designs.Comment: PhD Thesi