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

Multi-Tenant C-RAN With Spectrum Pooling: Downlink Optimization Under Privacy Constraints