Joint design of coalition formation and semi-blind channel estimation in fog radio access networks

Coordinated signal processing can obtain a huge transmission gain for Fog Radio Access Networks (F-RANs). However, integrating into large scale, it will lead to high computation complexity in channel estimation and spectral efficiency loss in transmission performance. Thus, a joint cluster formation and channel estimation scheme is proposed in this paper. Considering research remote radio heads (RRHs) centred serving scheme, a coalition game is formulated in order to maximize the spectral efficiency of cooperative RRHs under the conditions of balancing the data rate and the cost of channel estimation. As the cost influences to the necessary consumption of training length and estimation error. Particularly, an iterative semi-blind channel estimation and symbol detection approach is designed by expectation maximization algorithm, where the channel estimation process is initialized by subspace method with lower pilot length. Finally, the simulation results show that a stable cluster formation is established by our proposed coalition game method and it outperforms compared with full coordinated schemes.