  Cloud-radio access networks (C-RAN) help overcoming the scarcity of radio
resources by enabling dense deployment of base-stations (BSs), and connecting
them to a central-processor (CP). This paper considers the downlink of a C-RAN,
where the cloud is connected to the BSs via limited-capacity backhaul links.
The paper proposes splitting the message of each user into two parts, a private
part decodable at the intended user only, and a common part which can be
decoded at a subset of users, as a means to enable large-scale interference
management in CRAN. To this end, the paper optimizes a transmission scheme that
combines rate splitting (RS), common message decoding (CMD), clustering and
coordinated beamforming. The paper focuses on maximizing the weighted sum-rate
subject to per-BS backhaul capacity and transmit power constraints, so as to
jointly determine the RS-CMD mode of transmission, the cluster of BSs serving
private and common messages of each user, and the associated beamforming
vectors of each user private and common messages. The paper proposes solving
such a complicated non-convex optimization problem using $l_0$-norm relaxation
techniques, followed by inner-convex approximations (ICA), so as to achieve
stationary solutions to the relaxed non-convex problem. Numerical results show
that the proposed method provides significant performance gain as compared to
conventional interference mitigation techniques in CRAN which treat
interference as noise (TIN).
