Joint spectrum selection and radio resource management based on multi-objective portfolio optimization for cognitive radio networks

The advent of cognitive radio technology will enable user terminals with adaptive access to licensed and unlicensed portions of the spectrum. This will improve end-user satisfaction and will partially alleviate the bandwidth scarcity problem. However, different parts of the spectrum not only have different network (e.g. radio and load) conditions, but also different licensing and/or billing agreements. Therefore, in order for the operators to obtain the major profit and the most efficient use of radio resources, their allocation must now target both technical and economic performance metrics. This problem can be conveniently formulated as a multi-objective portfolio optimization problem, which has been studied in detail in the fields of economics and finance theory. This paper presents a joint spectrum selection and radio resource management algorithm for cognitive radio networks based on the optimization of a multi-objective portfolio function based on return and risk values per bit/second/Hz of transmitted information in primary and secondary frequency bands. Our approach intends to obtain the most convenient use of radio resources that simultaneously maximizes network and economic performance indicators. System-level simulation results suggest that an optimum throughput solution can be reached inside the Pareto optimal trade-off performance region of the problem given an appropriate trade-off between risk and return objective functions.