TY - GEN
T1 - Carrier-cooperative zero-forcing for power minimization in parallel MIMO broadcast channels
AU - Herrmann, Stephan
AU - Hellings, Christoph
AU - Utschick, Wolfgang
PY - 2012
Y1 - 2012
N2 - We consider the power minimization problem with per-user minimum rate constraints for parallel multiple-input multiple-output (MIMO) broadcast channels employing zero-forcing beamforming. Recent results have shown that spreading data streams across several carriers - so called carrier-cooperative (CC) transmission - can lead to a reduction of the sum transmit power in such a scenario. However, using state-of-the-art power minimization algorithms based on zero-forcing, only carrier-noncooperative (CN) solutions can be obtained. In this paper, we derive a novel algorithm that is capable of finding CC transmit strategies and can achieve a significant decrease in sum transmit power compared to a conventional zero-forcing power minimization method. The key point of the algorithm is that it combines greedy allocation of data streams, which is a popular technique to optimize zero-forcing strategies, with a gradient-based update of the filter vectors, which is a way to ensure that CC solutions can be obtained. Numerical simulations show that the advantage of the new algorithm is most pronounced in an environment where users have spectrally similar channels.
AB - We consider the power minimization problem with per-user minimum rate constraints for parallel multiple-input multiple-output (MIMO) broadcast channels employing zero-forcing beamforming. Recent results have shown that spreading data streams across several carriers - so called carrier-cooperative (CC) transmission - can lead to a reduction of the sum transmit power in such a scenario. However, using state-of-the-art power minimization algorithms based on zero-forcing, only carrier-noncooperative (CN) solutions can be obtained. In this paper, we derive a novel algorithm that is capable of finding CC transmit strategies and can achieve a significant decrease in sum transmit power compared to a conventional zero-forcing power minimization method. The key point of the algorithm is that it combines greedy allocation of data streams, which is a popular technique to optimize zero-forcing strategies, with a gradient-based update of the filter vectors, which is a way to ensure that CC solutions can be obtained. Numerical simulations show that the advantage of the new algorithm is most pronounced in an environment where users have spectrally similar channels.
UR - https://www.scopus.com/pages/publications/84876210278
U2 - 10.1109/ACSSC.2012.6489203
DO - 10.1109/ACSSC.2012.6489203
M3 - Conference contribution
AN - SCOPUS:84876210278
SN - 9781467350518
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1162
EP - 1166
BT - Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
PB - IEEE Computer Society
T2 - 46th Asilomar Conference on Signals, Systems and Computers, ACSSC 2012
Y2 - 4 November 2012 through 7 November 2012
ER -