Name
Abstract | ||
|---|---|---|
This paper considers transmit optimization in multi-input multi-output (MIMO) wiretap channels, wherein we aim at maximizing the secrecy capacity or rate of an MIMO channel overheard by one or multiple eavesdroppers. Such optimization problems are nonconvex, and appear to be difficult especially in the multi-eavesdropper scenario. In this paper, we propose an alternating optimization (AO) approach to tackle these secrecy optimization problems. We first consider the secrecy capacity maximization (SCM) problem in the single eavesdropper scenario. An AO algorithm is derived through a judicious SCM reformulation. The algorithm conducts some kind of reweighting and water-filling in an alternating fashion, and thus is computationally efficient to implement. We also prove that the AO algorithm is guaranteed to converge to a Karush-Kuhn-Tucker (KKT) point of the SCM problem. Then, we turn our attention to the multiple eavesdropper scenario, where the artificial noise (AN)-aided secrecy rate maximization (SRM) problem is considered. Although the AN-aided SRM problem has a more complex problem structure than the previous SCM, we show that AO can be extended to deal with the former, wherein the problem is handled by solving convex problems in an alternating fashion. Again, the resulting AO method is proven to have KKT point convergence guarantee. For fast implementation, a custom-designed AO algorithm based on smoothing and projected gradient is also derived. The secrecy rate performance and computational efficiency of the proposed algorithms are demonstrated by simulations. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/JSAC.2013.130906 | IEEE Journal on Selected Areas in Communications |
Keywords | Field | DocType |
secrecy capacity,physical-layer secrecy,transmit optimization,alternating optimization,convex problems,multiple eavesdroppers,data privacy,karush-kuhn-tucker point,secrecy optimization problems,multi-input multi-output wiretap channels,artificial noise-aided secrecy rate maximization,convex programming,wireless channels,iterative water-filling,mimo communication,mimo wiretap channels,water-filling,transmit solutions,secrecy capacity maximization,telecommunication security,scm reformulation,mimo channel overheard,multi-eavesdropper scenario,artificial noise,tin,algorithm design and analysis,optimization,mimo,transmitters,convergence | Convergence (routing),Mathematical optimization,Computer science,MIMO,Smoothing,Artificial noise,Karush–Kuhn–Tucker conditions,Optimization problem,Convex optimization,Maximization | Journal |
Volume | Issue | ISSN |
31 | 9 | 0733-8716 |
Citations | PageRank | References |
63 | 1.76 | 28 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qiang Li | 1 | 525 | 30.90 |
| Mingyi Hong | 2 | 1533 | 91.29 |
| Hoi-To Wai | 3 | 169 | 24.51 |
| Y. F. Liu | 4 | 454 | 30.59 |
| Wing-Kin Ma | 5 | 3370 | 192.34 |
| Zhi-Quan Luo | 6 | 7506 | 598.19 |