Cloud radio access network (C-RAN) architecture offers two key advantages as compared with traditional radio access networks (RANs) from the physical-layer transmission point of view. First, the centralization and virtualization of RANs allow the coordination of base stations (BSs) across a large geographic area, thereby enabling coordinated physical-layer resource allocation across the BSs. The physical-layer resources here refer to the frequency, time, and spatial dimensions that can be utilized by radio transmission. Second, and more importantly, the C-RAN architecture also opens up the possibility of the joint transmission and joint reception of user signals across multiple BSs, thereby fundamentally addressing the issue of inter-cell interference. As interference is the main bottleneck in modern densely deployed wireless networks, the C-RAN architecture offers significant advantages in that it provides the possibility of interference mitigation leading to performance enhancement without the need for additional site and bandwidth acquisition.

This chapter provides an optimization framework for cooperative beamforming and resource allocation in C-RANs. We begin by identifying frequency, time, and spatial resources in wireless cellular networks and defining the overall spectrum allocation, scheduling, and beamforming problem in a cooperative network. The chapter then provides a network model for the C-RAN architecture and illustrates typical network objective functions and constraints for network utility maximization. A key characteristic of the C-RAN architecture is that the fronthaul connections between the cloud and the BSs may have limited capacities. One of the main goals of this chapter is to illustrate the impact of limited fronthaul capacity on the cooperative beamforming and resource allocation in C-RANs.

The chapter explores the optimization of the design variables associated with CRANs, depending on the transmission strategies at the cooperative BSs. For the uplink C-RAN, we illustrate compress-forward as the main strategy at the BSs and focus on the impact of the choice of quantization noise levels at the BSs and possible joint transmit optimization strategies. For the downlink C-RAN, we compare a compression-based strategy and a data-sharing strategy and illustrate the problem formulation and solution strategy in both cases. Throughout the chapter, key optimization techniques for solving resource-allocation problems in C-RANs are presented.