Browsing by Author "Ko, Ta"

Now showing 1 - 2 of 2

A Blind Statistical Approach for Optimal Receive Beam Steering in Multipath Environments
(2012)
Tsai, Tsung-Yu
;
Ko, Ta
;
Lin, You-Hsien
;
Tsai, Zsehong
;
Hsu, Terng-Yin
A novel blind statistical algorithm for obtaining the optimal receive beam vector with maximum time-domain effective SNR in OFDMA systems under multipath environment is proposed. The basic procedure of the proposed approach is obtained via the coarse cyclic prefix (CP) detection first and the sample average of the correlation matrices is calculated from selected signal samples for later singular value decomposition (SVD) on the averaged correlation matrix. The proposed approach has the following advantages: First, it is accurate even in the presence of high noise power and when the process of the OFDMA sampled signals are not white (i.e. not all subcarriers are allocated for data transmission). Secondly, it can be operated in time-domain with no training signals and no pre-assumption of the antenna array structure. Hence, it could be applied directly to a variety of existing OFDMA systems and its design can be made relatively simple for implementation. Theoretical proofs of its optimality and the guarantee of convergence are also provided in this paper. Finally, simulation results verifies the theoretical analysis and shows that the proposed approach can accurately achieve a near optimal SNR gain even in low SNR environment and has a convergence speed within two OFDM symbols.
Low-Complexity Beam Steering Algorithm Based on Binary Search Strategy for Receive Beamform
(2012)
Lin, You-Hsien
;
Tsai, Tsung-Yu
;
Chen, Ying-Liang
;
Ko, Ta
;
Chien, Chun-Che
The complexity of beamforming, such as complexity complex weighting and combining process, are extremely important for implementation. This work presents a low complexity time-domain statistic noise suppression and beam steering algorithm based on binary search strategy to estimate the optimal beam vector at the receivers. The beam steering algorithm based on binary search strategy could achieve closely (about 99%) optimal SNR gain within only two binary search. It is desirable choice to archive the suitable trade-off between the performance and the processing overhead. Hence, it could obtain a near-optimal performance with considerably low complexity and high convergence speed. In addition, this algorithm is well-matched to different specifications.