Power Allocation in Two-Hop Amplify-and-Forward MIMO Relay Systems With QoS Requirements

被引:33
作者
Sanguinetti, Luca [1 ]
D'Amico, Antonio A. [1 ]
机构
[1] Univ Pisa, Dept Informat Engn, I-56126 Pisa, Italy
关键词
Closed-form solution; decision-feedback equalizer; majorization theory; multiple-input multiple-output (MIMO); nonconvex optimization; nonregenerative relay; power allocation; power consumption; quality-of-service (QoS) requirements; transceiver optimization; TRANSCEIVER DESIGN; UNIFIED FRAMEWORK; CHANNELS;
D O I
10.1109/TSP.2012.2187198
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The problem of minimizing the total power consumption while satisfying different quality-of-service (QoS) requirements in a two-hop multiple-input multiple-output (MIMO) network with a single nonregenerative relay is considered. As shown by Y. Rong ["Multihop nonregenerative MIMO relays: QoS considerations," IEEE Trans. Signal Process., vol. 59, no. 1, pp. 209-303, 2011] in [1], the optimal processing matrices for both linear and nonlinear transceiver architectures lead to the diagonalization of the source-relay-destination channel so that the power minimization problem reduces to properly allocating the available power over the established links. Unfortunately, finding the solution of this problem is numerically difficult as it is not in a convex form. To overcome this difficulty, existing solutions rely on the computation of upper- and lower-bounds that are hard to obtain or require the relaxation of the QoS constraints. In this work, a novel approach is devised for both linear and nonlinear transceiver architectures, which allows to closely approximate the solutions of the nonconvex power allocation problems with those of convex ones easy to compute in closed-form by means of multi-step procedures of reduced complexity. Computer simulations are used to assess the performance of the proposed approach and to make comparisons with alternatives.
引用
收藏
页码:2494 / 2507
页数:14
相关论文
共 28 条
[1]  
[Anonymous], 2003, Introduction to SpaceTime Wireless Communications
[2]  
BOYD S, 2002, CONVEX OPTIMIZATION
[4]   On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas [J].
Foschini G.J. ;
Gans M.J. .
Wireless Personal Communications, 1998, 6 (3) :311-335
[5]   Optimum Linear Design of Two-Hop MIMO Relay Networks With QoS Requirements [J].
Fu, Youhua ;
Yang, Luxi ;
Zhu, Wei-Ping ;
Liu, Chen .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2011, 59 (05) :2257-2269
[6]   Optimal Training Design for Channel Estimation in Decode-and-Forward Relay Networks With Individual and Total Power Constraints [J].
Gao, Feifei ;
Cui, Tao ;
Nallanathan, Arumugam .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2008, 56 (12) :5937-5949
[7]   Linear Relaying Scheme for MIMO Relay System With QoS Requirements [J].
Guan, Wei ;
Luo, Hanwen ;
Chen, Wen .
IEEE SIGNAL PROCESSING LETTERS, 2008, 15 :697-700
[8]  
Jiang Y, 2008, MATH COMPUT, V77, P1037, DOI 10.1090/S0025-5718-07-02014-5
[9]   Tunable channel decomposition for MIMO communications using channel state information [J].
Jiang, Yi ;
Hager, William W. ;
Li, Jian .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2006, 54 (11) :4405-4418
[10]   Distributed MMSE relay strategies for wireless sensor networks [J].
Khajehnouri, Nima ;
Sayed, Ali H. .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2007, 55 (07) :3336-3348