TY - GEN
T1 - Matrix-field water-filling architecture for MIMO transceiver designs with mixed power constraints
AU - Xing, Chengwen
AU - Fei, Zesong
AU - Zhou, Yiqing
AU - Pan, Zhengang
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/1
Y1 - 2015/12/1
N2 - In this paper, we discuss MIMO transceiver design under a new type of power constraint named mixed power constraints. Mixed power constraint is referred to the power model in which for a given set of antennas, several subsets are constrained by sum power constraints while the other antennas are subject to individual power constraints. It includes sum power constraint and per-antenna power constraints as its special cases and it can strike a balance between complexity and performance. In our work, we try to solve the optimization problem in an analytical way instead of relying on some famous software packages e.g., CVX or SeDuMi. Firstly, the specific formula of the optimal signal covariance matrix has been derived. Based on the structure, a low complexity non-iterative solution is given in our work, which can be interpreted as a matrix version water-filling solution. This solution has a much clear engineering meaning and is suitable for practical implementations even for massive MIMO systems. Finally, simulation results demonstrate the accuracy of our theoretical results.
AB - In this paper, we discuss MIMO transceiver design under a new type of power constraint named mixed power constraints. Mixed power constraint is referred to the power model in which for a given set of antennas, several subsets are constrained by sum power constraints while the other antennas are subject to individual power constraints. It includes sum power constraint and per-antenna power constraints as its special cases and it can strike a balance between complexity and performance. In our work, we try to solve the optimization problem in an analytical way instead of relying on some famous software packages e.g., CVX or SeDuMi. Firstly, the specific formula of the optimal signal covariance matrix has been derived. Based on the structure, a low complexity non-iterative solution is given in our work, which can be interpreted as a matrix version water-filling solution. This solution has a much clear engineering meaning and is suitable for practical implementations even for massive MIMO systems. Finally, simulation results demonstrate the accuracy of our theoretical results.
KW - Convex optimization
KW - MIMO
KW - matrix-version water-filling
KW - transceiver design
UR - http://www.scopus.com/inward/record.url?scp=84958047420&partnerID=8YFLogxK
U2 - 10.1109/PIMRC.2015.7343330
DO - 10.1109/PIMRC.2015.7343330
M3 - Conference contribution
AN - SCOPUS:84958047420
T3 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
SP - 392
EP - 396
BT - 2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 26th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2015
Y2 - 30 August 2015 through 2 September 2015
ER -