Name
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/icc.2011.5962914 | ICC |
Keywords | Field | DocType |
radio links,discrete data rates,mimo links,power constraint,capacity optimization problem,svd,quasinewton method,gradient projection algorithm,integer programming,newton method,mimo communication,gradient methods,discrete powers,interference,interference (signal),optimization,scheduling,mimo,algorithms,numerical integration,signal to noise ratio,covariance matrix,transmitters | Mathematical optimization,Convexity,Scheduling (computing),Computer science,Signal-to-noise ratio,MIMO,Integer programming,Interference (wave propagation),Optimization problem,Capacity optimization | Conference |
ISSN | ISBN | Citations |
1550-3607 E-ISBN : 978-1-61284-231-8 | 978-1-61284-231-8 | 2 |
PageRank | References | Authors |
0.37 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peng Wang | 1 | 2 | 0.37 |
| John D. Matyjas | 2 | 554 | 43.69 |
| Michael J. Medley | 3 | 337 | 26.06 |