Title
A Closed-Form Power Allocation and Signal Alignment for a Diagonalized MIMO Two-Way Relay Channel With Linear Receivers
Abstract
novel channel diagonalization scheme for an amplify-and-forward, multiple-input multiple-output (MIMO), two-way relay channel (TWRC) is proposed using generalized singular value decomposition (GSVD). Diagonalization of the MIMO TWRC is a sub-optimal approach that achieves two main purposes: reducing the computational complexity for optimizing the linear precoders at each node; and reducing the detection complexity at the source nodes by separating the multiple data streams. For the given diagonalized structure, we first align the entries of the diagonalized channels using a permutation to maximize a lower bound of average achievable sum rate (ASR), and a joint source-relay power allocation is then performed to maximize the ASR of the aligned TWRC; the overall problem is divided into two convex subproblems, the solutions to which are provided in closed-form. Our analysis for the proposed scheme underlines the benefits of acquiring channel state information. Simulation results demonstrate that the proposed GSVD-based relaying scheme, with the signal alignment and closed-form power allocation, significantly improves the ASR while retaining the diagonalized channel structure. In addition, the proposed scheme achieves the same level of ASR with much less computational complexity as compared to the iterative schemes.
Year
DOI
Venue
2012
10.1109/TSP.2012.2208960
IEEE Transactions on Signal Processing
Keywords
Field
DocType
antennas,singular value decomposition,computational complexity,permutation,precoding,mimo,resource management,convex programming,radio receivers
Generalized singular value decomposition,Relay channel,Mathematical optimization,Control theory,Communication channel,MIMO,Convex optimization,Precoding,Mathematics,Channel state information,Computational complexity theory
Journal
Volume
Issue
ISSN
60
11
1053-587X
Citations 
PageRank 
References 
12
0.59
33
Authors
4
Name
Order
Citations
PageRank
Heesun Park1293.12
Hyun Jong Yang226224.94
Joohwan Chun339635.12
Raviraj Adve41683105.03