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This paper is interested in maximizing the total throughput of cloud radioaccess networks (CRANs) in which multiple radio remote heads (RRHs) areconnected to a central computing unit known as the cloud. The transmit frame ofeach RRH consists of multiple radio resources blocks (RRBs), and the cloud isresponsible for synchronizing these RRBS and scheduling them to users. Unlikeprevious works that consider allocating each RRB to only a single user at eachtime instance, this paper proposes to mix the flows of multiple users in eachRRB using instantly decodable network coding (IDNC). The proposed scheme isthus designed to jointly schedule the users to different RRBs, choose theencoded file sent in each of them, and the rate at which each of them istransmitted. Hence, the paper maximizes the throughput which is defined as thenumber of correctly received bits. To jointly fulfill this objective, we designa graph in which each vertex represents a possible user-RRB association,encoded file, and transmission rate. By appropriately choosing the weights ofvertices, the scheduling problem is shown to be equivalent to a maximum weightclique problem over the newly introduced graph. Simulation results illustratethe significant gains of the proposed scheme compared to classical coding anduncoded solutions.

Throughput Maximization in Cloud Radio Access Networks using Network Coding