A computing offloading algorithm for F-RAN with limited capacity fronthaul

Abstract

In order to alleviate heavy burden on the capacity-limited fronthaul of C-RAN, a fog computing based C-RAN(F-RAN) architecture has been proposed in recent years. In F-RAN, RRH receives the signal from mobile devices and decides part of tasks to be processed in fog part for computing offloading. With the purpose of offloading sampling signal in fronthaul and separating tasks from cloud part to be processed in fog part, we formulate the problem as a congestion game. And we propose a discrete distribution computing offloading algorithm (DDCO) for F-RAN to solve this game. The DDCO algorithm decides the latency-sensitive mobile to be computed in the fog part such that the fronthaul can be offloaded and Quality of Service (QoS) can be improved. The DDCO algorithm can also balance load in fronthaul in order to improve performance. With the DDCO algorithm, the network get larger throughput and reduce the burden in fronthaul when it achieve a Nash Equilibrium. Finally, we analyze the feasibility of the algorithm. Numerical result corroborate that the DDCO algorithm can well improve throughput compared with the traditional C-RAN network.