Beam codebook based beamforming protocol for multi-Gbps millimeter-wave WPAN systems
IEEE Journal on Selected Areas in Communications - Special issue on realizing GBPS wireless personal area networks
Hybrid beam-forming and beam-switching for OFDM based wireless personal area networks
IEEE Journal on Selected Areas in Communications - Special issue on realizing GBPS wireless personal area networks
Analysis on spatial reuse and interference in 60-GHz wireless networks
IEEE Journal on Selected Areas in Communications - Special issue on realizing GBPS wireless personal area networks
MIMO-OFDM wireless systems: basics, perspectives, and challenges
IEEE Wireless Communications
Symbol-based space diversity for coded OFDM systems
IEEE Transactions on Wireless Communications
IEEE Transactions on Wireless Communications
On the potential of fixed-beam 60 GHz network interfaces in mobile devices
PAM'11 Proceedings of the 12th international conference on Passive and active measurement
Hi-index | 0.00 |
In this paper, we propose an efficient codebook-based symbol-wise beamforming for millimeter-wave WPAN systems, which is based on the multi-level training and antenna selection to reduce the protocol overhead in terms of the number of required training sequences. Using our proposed antenna selection method, one beam direction of the specific level includes two beam directions of the following level, which results that the required number of training sequences at each level is constant regardless of the number of antennas. Once antennas of the transmitter and receiver are selected properly at each level, then the training sequences are exchanged with the direction specified by the pre-defined codebook. By adopting the proposed antenna selection method and multi-level training, our proposed scheme can significantly reduce the total number of required training sequences for the beamforming setup. To verify the performance, we compare our proposed scheme with the conventional symbol-wise beamforming schemes based on the codebook. It is evident from the simulations that our proposed scheme can provide the effective signal-to-noise ratio (SNR) gain approaching to the conventional scheme with fewer training sequences.