Opportunistic Beamforming with Link Anaptation Robust to Imperfect Channel Estimation 


Vol. 33,  No. 8, pp. 617-626, Aug.  2008


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  Abstract

Opportunistic Beamforming (OBF) offers a way to provide the multiuser diversity even in slow fading channel by using randomly generated beam weights, leading to the substantially reduced feedback in the form of the instantaneous SNR from users. In spite of the advantage of the reduced feedback, the imperfect channel estimation might influence the quality of the estimated SNR and channel scheduler so bad that the selected AMC level would be higher than the achievable rate of the actual channel, resulting the corruption of transmitted packet. In this paper, we propose a conservative link adaptation, where the estimated SNR is scaled down by a conservative factor which minimizes the variance of the maximum difference between the actual channel SNR and the resultant SNR. To support the proposed scheme, we analyze the statistics of the difference of the channel SNR and the estimated SNR. Simulation results show that the introduction of conservative factor achieves more than two-fold performance improvement in the presence of channel estimation error and the fairness of PF scheduler is maintained when the least squared channel estimator is applied.

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  Cite this article

[IEEE Style]

Y. Kim and D. K. Kim, "Opportunistic Beamforming with Link Anaptation Robust to Imperfect Channel Estimation," The Journal of Korean Institute of Communications and Information Sciences, vol. 33, no. 8, pp. 617-626, 2008. DOI: .

[ACM Style]

Yohan Kim and Dong Ku Kim. 2008. Opportunistic Beamforming with Link Anaptation Robust to Imperfect Channel Estimation. The Journal of Korean Institute of Communications and Information Sciences, 33, 8, (2008), 617-626. DOI: .

[KICS Style]

Yohan Kim and Dong Ku Kim, "Opportunistic Beamforming with Link Anaptation Robust to Imperfect Channel Estimation," The Journal of Korean Institute of Communications and Information Sciences, vol. 33, no. 8, pp. 617-626, 8. 2008.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880