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Full-Duplex MIMO Precoding for Sum-Rate Maximization With Sequential Convex Programming.
- Source :
-
IEEE Transactions on Vehicular Technology . Nov2015, Vol. 64 Issue 11, p5103-5112. 10p. - Publication Year :
- 2015
-
Abstract
- This paper focuses on precoding design for sum-rate maximization while considering the effects of residual self-interference for multiuser multiple-input–multiple-output (MU-MIMO) full-duplex (FD) systems. The problem formulation leads to a nonconvex matrix-variable optimization problem, where we develop two efficient sum-rate maximization algorithms using sequential convex programming (SCP), namely, the difference of convex functions (DC)-based and the sequential convex approximations for matrix-variable programming (SCAMP) algorithms. In addition, we derive the achievable sum rate under the effect of residual self-interference. Simulation results show that, even in cases of high self-interference and high estimation error, the SCAMP algorithm provides approximately 20%–30% sum-rate improvements over both conventional optimized half-duplex (HD) transmission and the existing state-of-the-art FD algorithm in a wide range of scenarios. Finally, the convergence results indicate that the DC-based algorithm tends to initially give the best performance; however, at convergence, the SCAMP algorithm tends to significantly outperform the other algorithms. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MIMO systems
*CONVEX programming
*CONVEX functions
*ALGORITHMS
*CHANNEL estimation
Subjects
Details
- Language :
- English
- ISSN :
- 00189545
- Volume :
- 64
- Issue :
- 11
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Vehicular Technology
- Publication Type :
- Academic Journal
- Accession number :
- 110950552
- Full Text :
- https://doi.org/10.1109/TVT.2014.2380775