Optimal Beamforming and Power Allocation for Cognitive Femto Base Stations Based on Soft Decision

In this paper, an optimal beamforming and power allocation for the sensing-based spectrum sharing (SBSS) that employs a soft decision on the state of the primary user is proposed. Different from the existing soft-decision-based SBSS that employs a single antenna and adjusts only transmit power, in the proposed scheme, the secondary transmitter employs multiple transmit antennas and controls the beamforming direction and the transmit power. We design the optimal beamforming and power allocation under the constraints of total transmit power and interference power, where both average and instantaneous power constraints are considered. Simulation results demonstrate that the proposed technique can significantly improve the average throughput of the secondary user compared with the existing methods. The proposed beamforming for the soft-decision-based SBSS is a promising scheme, particularly for cognitive femto base stations (BSs) to boost up the spectral efficiency while managing the interference to the macro BSs.