Blind interference alignment (BIA) can eliminate users’ interference without channel state information and greatly improve the channel capacity, which has been regarded as a promising technique in next generation wireless systems. However, current BIA mechanisms neglect noise accumulations, resulting in final signal-to-noise ratio (fSNR) deterioration and reduced transmission rates. Motivated by ameliorating such negative impact induced by noise accumulations, this study establishes an SNR aware semi-BIA (SNR SBIA) framework in the multi-input–single-output broadcast channel, where the users form different groups performing BIA for different SNR reductions. An SNR SBIA algorithm is further proposed based on tabu search for maximising the overall performance ensuring all users’ fSNRs higher than an SNR threshold. Extensive evaluations demonstrate that SNR SBIA can adapt to the users’ diverse received SNRs and the corresponding achievable sum rate is about 1.38 times and 1.92 times that in standard BIA and grouped hierarchical BIA, respectively.
['Qing Yang', 'Ting Jiang', 'Zheng Zhou']
SNR aware SBIA in multiple-input–single-output broadcast channel