Economy-efficient resource allocation in cloud radio access networks with fronthaul capacity constraints

As an advanced paradigm, the cloud radio access network (C-RAN) promises high spectral efficiency (SE) and energy efficiency (EE). However, the capacity-constrained fronthaul has become a key performance bottleneck for C-RANs. Generally, the traditional SE and EE are utilized to evaluate radio transmit performances without considering fronthaul cost, which is always the major concern for operators. In this paper, an economical spectral efficiency (ESE) is proposed to jointly take traditional SE/EE and the impact of wired/wireless fronthaul into account. Aiming at maximizing ESE, a non-convex beamformer design problem with fronthaul capacity and transmit power constraints is formulated. To deal with this non-convexity, the primal problem is transformed to an equivalent problem, which is solved by the weighted minimum mean square error approach. Simulation results demonstrate that the proposed algorithm can significantly improve ESE, in which the impact of fronthaul on ESE is evaluated and analyzed as well.