In the 5th generation mobile communication system (5G), super high frequency (SHF) bands such as 28GHz will be used in many scenarios. In Japan, a local 5G working group has been established to apply advanced 5G technologies to private networks and is working to encourage local companies and municipalities to introduce new services for local needs. Meanwhile, the smaller size of the 28GHz band cells creates the difficulties when establishing deployment areas for homogeneous networks. In general, heterogeneous network approach with the combination of macro-cell and micro-cell have been considered practical and applied by the giant telecommunication operators. However, private network operators have difficulty in deploying both micro- and macro-cells due to the cost issue. Without the assistance of macro-cells, local spot cells with a small service area may not be able to start services while high-speed mobile users are staying in the service area. In this paper, we propose a virtual pre-connection scheme allowing fast connection to local spot cells without the assistance of macro-cells. In addition, we confirm that the proposed scheme can reduce the cell search time required when entering a local spot cell from 100 seconds or more to less than 1 second, and can reduce the loss of connection opportunities to local spot cells for high-speed mobile users.

The spectrum sculpting precoder (SSP) is a precoding scheme for sidelobe suppression of frequency division multiplexing (OFDM) signals. It can form deep spectral notches at chosen frequencies and is suitable for cognitive radio systems. However, the SSP degrades the error rate as the number of notched frequencies increases. Orthogonal precoding that improves the SSP can achieve both spectrum notching and the ideal error rate, but its computational complexity is very high since the precoder matrix is large in size. This paper proposes an effective and equivalent decomposition of the precoder matrix by QR-decomposition in order to reduce the computational complexity of orthogonal precoding. Numerical experiments show that the proposed method can drastically reduce the computational complexity with no performance degradation.