Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | IEEE Vehicular Technology Conference |
| DOIs | |
| Publication status | Published - 2012 Dec 1 |
| Event | 76th IEEE Vehicular Technology Conference, VTC Fall 2012 - Quebec City, QC, Canada Duration: 2012 Sep 3 → 2012 Sep 6 |
Other
| Other | 76th IEEE Vehicular Technology Conference, VTC Fall 2012 |
|---|---|
| Country | Canada |
| City | Quebec City, QC |
| Period | 12/9/3 → 12/9/6 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Computer Science Applications
- Applied Mathematics
Cite this
Distributed precoding techniques for weighted sum rate maximization in mimo interfering broadcast channels. / Choi, Hyun Joo; Park, Seok Hwan; Lee, Sang Rim; Lee, Inkyu.
IEEE Vehicular Technology Conference. 2012. 6399062.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
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 - 2012/12/1
Y1 - 2012/12/1
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
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U2 - 10.1109/VTCFall.2012.6399062
DO - 10.1109/VTCFall.2012.6399062
M3 - Conference contribution
SN - 9781467318815
BT - IEEE Vehicular Technology Conference
ER -