Linear Precoding with Resource Allocation for MIMO Relay Channels

• Published in: IEEE transactions on wireless communications Vol. 12; no. 11; pp. 5704 - 5716
• Main Authors: Monroy, Edwin, Choi, Sunghyun, Jabbari, Bijan
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.2013; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Access methods and protocols, osi model; Algorithms; Antennas; Applied sciences; Coding, codes; convex optimization; Encoding; Exact sciences and technology; Information, signal and communications theory; Interference; linear precoding; MIMO; MIMO Relay; Radiocommunications; Relays; resource allocation; Resource management; Signal and communications theory; Telecommunications; Telecommunications and information theory; Teleprocessing networks. Isdn; Vectors; Wireless communication; MIMO system; MIMO Relay; Freedom degree; Relay; Approximate method; Resource allocation; Transmission protocol; Algorithm; Computational complexity; Convex programming; Duplex process; linear precoding; Relay channel; Coding; Numerical simulation; convex optimization; Routing protocols; Pretreatment; Resource management; Antenna array; Antenna
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2013.093013.122002

This paper considers a half-duplex relay channel with a single source, relay, and destination, where each node has multiple antennas and the relay operates in decode-and-forward (DF) mode. The additional degrees of freedoms introduced by the MIMO channels entail increased complexity in comparison with the single antenna case. We propose a new transmission strategy for the relay channel that is able to take advantage of the MIMO gains while employing practical techniques that help reduce complexity. In the proposed scheme, the source splits its message in two parts and sends them to the destination, one part directly and the other with help from the relay. For such a transmission strategy, we formulate the problem of obtaining the rate-maximizing linear precoding matrices with time, power, and spatial stream allocation and transform the problem into a convex form. We also propose a suboptimal algorithm that provides simplifying expressions to solve the resulting problem with far less computational complexity. The numerical results show that the achievable rate of our scheme is greater than the DF rate in certain scenarios, as well as that of other practical existing strategies. In addition, the rate obtained by the suboptimal method approximates the optimal rate extremely well in all considered scenarios.