TY - GEN
T1 - Distributed precoding techniques for weighted sum rate maximization in mimo interfering broadcast channels
AU - Choi, Hyun Joo
AU - Park, Seok Hwan
AU - Lee, Sang Rim
AU - Lee, Inkyu
PY - 2012
Y1 - 2012
N2 - In this paper, we propose a linear precoding technique for weighted sum rate (WSR) maximization in multiple-input multiple-output interfering broadcast channels. In multicell environments, the WSR can be jointly maximized through centralized processing which causes a large amount of channel state information (CSI) exchange. In order to reduce the overhead associated with CSI, we focus on a distributed precoding scheme utilizing local CSI at each base station (BS). First, applying a high signal-to-interference-plus-noise ratio assumption, we decouple the WSR maximization problem into distributed problems. Then we solve this distributed WSR maximization problem for each BS by using a zero-gradient based algorithm which converges to a local maximum point. Unlike conventional distributed schemes which require additional information, our proposed scheme at each base station utilizes only the local CSI to compute its precoding matrices. Through the Monte-Carlo simulation, we show that our proposed algorithm exhibits the performance almost identical to the centralized scheme requiring the global CSI.
AB - In this paper, we propose a linear precoding technique for weighted sum rate (WSR) maximization in multiple-input multiple-output interfering broadcast channels. In multicell environments, the WSR can be jointly maximized through centralized processing which causes a large amount of channel state information (CSI) exchange. In order to reduce the overhead associated with CSI, we focus on a distributed precoding scheme utilizing local CSI at each base station (BS). First, applying a high signal-to-interference-plus-noise ratio assumption, we decouple the WSR maximization problem into distributed problems. Then we solve this distributed WSR maximization problem for each BS by using a zero-gradient based algorithm which converges to a local maximum point. Unlike conventional distributed schemes which require additional information, our proposed scheme at each base station utilizes only the local CSI to compute its precoding matrices. Through the Monte-Carlo simulation, we show that our proposed algorithm exhibits the performance almost identical to the centralized scheme requiring the global CSI.
UR - http://www.scopus.com/inward/record.url?scp=84878908772&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84878908772&partnerID=8YFLogxK
U2 - 10.1109/VTCFall.2012.6399062
DO - 10.1109/VTCFall.2012.6399062
M3 - Conference contribution
AN - SCOPUS:84878908772
SN - 9781467318815
T3 - IEEE Vehicular Technology Conference
BT - 2012 IEEE Vehicular Technology Conference, VTC Fall 2012 - Proceedings
T2 - 76th IEEE Vehicular Technology Conference, VTC Fall 2012
Y2 - 3 September 2012 through 6 September 2012
ER -