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Maximizing achievable rate of cognitive radio networks through efficient spectrum sensing and multi-level power allocation

In this paper, we study a multi-level power allocation scheme for SUs in cognitive radio systems that uses a new frame structure to improve overall throughput of the system. The scheme is different from the conventional strategies in that the PU can now transmit with multiple levels of power rather than a constant level of power, which seems to be more realistic and practical. Our proposed strategy also allows SUs to choose different power levels according to their receiving energy. In this work, we are interested in finding a solution that power level selection by SUs is optimized to maximize the achievable rate under the constraints of average transmit power at cognitive users and average interference temperature to the PU. This allows the throughput of SUs to be improved while minimizing harmful interference to the PU and maintaining the QoS in the PU side at the reduced complexity of computation.