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Lingxiang Li

Publications and source records attributed to Lingxiang Li.

20 records · Page 2Linked to original sources

On the Secrecy Capacity of a MIMO Gaussian Wiretap Channel with a Cooperative Jammer

We study the secrecy capacity of a helper-assisted Gaussian wiretap channel with a source, a legitimate receiver, an eavesdropper and an external helper, where each terminal is equipped with multiple antennas. Determining the secrecy capacity in this scenario generally requires solving a nonconvex secrecy rate maximization (SRM) problem. To deal with this issue, we first reformulate the original SRM problem into a sequence of convex subproblems. For the special case of single-antenna legitimate receiver, we obtain the secrecy capacity via a combination of convex optimization and one-dimensional search, while for the general case of multi-antenna legitimate receiver, we propose an iterative solution. To gain more insight into how the secrecy capacity of a helper-assisted Gaussian wiretap channel behaves, we examine the achievable secure degrees of freedom (s.d.o.f.) and obtain the maximal achievable s.d.o.f. in closed-form. We also derive a closed-form solution to the original SRM problem which achieves the maximal s.d.o.f.. Numerical results are presented to illustrate the efficacy of the proposed schemes.

cs.IT↗

On Feasibility of Generalized Interference Alignment with Partial Interference Cancelation

We study a new IA strategy which is referred to as "Partial Interference Cancelation-based Interference Alignment" (PIC-IA). Unlike the conventional IA strategy, PIC-IA does not strive to eliminate interference from all users. Instead, it aims to remove the most significant interference signals. This PIC-IA strategy generalizes the conventional IA concept by addressing partial, instead of complete, interference cancelation. The feasibility of this new strategy is studied in this paper. Our results show that for a symmetric, single-stream system with $N_t$ transmit antennas and $N_r$ receive antennas, the PIC-IA is feasible when the number of significant interference signals to be removed at each receiver is no more than $N_t+N_r-2$, no matter how many users are in the network. This is in sharp contrast to the conventional IA whose feasibility is severely limited by the number of users $K$.

cs.IT↗