Title :
Capacity Optimization of MIMO Links with Interference
Author :
Wang, Peng ; Matyjas, John ; Medley, Michael
Abstract :
The capacity optimization problem of MIMO links with interference has attracted an increasing interest. Due to the nonconvexity of the capacity problem, only suboptimal solutions can be found. In the previous works, a Gradient Projection (GP) algorithm and a Quasi-Newton (QN) method were proposed to provide suboptimal solutions subject to the constant power constraint. In this paper, we derive the capacity for MIMO links decomposed via SVD and interfered from other links. Then, each eigenchannel of MIMO link is represented by a set of logical links with a set of discrete data rates and discrete powers. An Integer Programming based algorithm (named as IP) is presented to solve the capacity optimization problem. The solution specifies the set of logical links that can transmit simultaneously. Numerical results show that GP and QN methods achieve better performance than IP method for the case of weak interference because of the convexity of the optimization problem when INR is sufficiently small. In the case of strong interference, IP method achieves better performance than GP and QN methods, which means that transmitting one link at a time is better than transmitting all links simultaneously with full power. In other words, scheduling links to transmit is more important for the case of strong interference.
Keywords :
MIMO communication; Newton method; gradient methods; integer programming; interference (signal); radio links; MIMO links; SVD; capacity optimization problem; discrete data rates; discrete powers; gradient projection algorithm; integer programming; interference; power constraint; quasiNewton method; Covariance matrix; IP networks; Interference; MIMO; Receivers; Signal to noise ratio; Transmitters;
Conference_Titel :
Communications (ICC), 2011 IEEE International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-61284-232-5
Electronic_ISBN :
1550-3607
DOI :
10.1109/icc.2011.5962914