  Spectrum pooling allows multiple operators, or tenants, to share the same
frequency bands. This work studies the optimization of spectrum pooling for the
downlink of a multi-tenant Cloud Radio Access Network (C-RAN) system in the
presence of inter-tenant privacy constraints. The spectrum available for
downlink transmission is partitioned into private and shared subbands, and the
participating operators cooperate to serve the user equipments (UEs) on the
shared subband. The network of each operator consists of a cloud processor (CP)
that is connected to proprietary radio units (RUs) by means of finite-capacity
fronthaul links. In order to enable interoperator cooperation, the CPs of the
participating operators are also connected by finite-capacity backhaul links.
Inter-operator cooperation may hence result in loss of privacy. Fronthaul and
backhaul links are used to transfer quantized baseband signals. Standard
quantization is considered first. Then, a novel approach based on the idea of
correlating quantization noise signals across RUs of different operators is
proposed to control the trade-off between distortion at UEs and inter-operator
privacy. The problem of optimizing the bandwidth allocation, precoding, and
fronthaul/backhaul compression strategies is tackled under constraints on
backhaul and fronthaul capacity, as well as on per-RU transmit power and
inter-operator privacy. For both cases, the optimization problems are tackled
using the concave convex procedure (CCCP), and extensive numerical results are
provided.
