Secrecy Rate Region of SWIPT Wiretap Interference Channels

TL;DR

This paper characterizes the secrecy rate region of SWIPT wiretap interference channels with a multi-antenna eavesdropper, proposing an efficient algorithm to optimize power and receiver parameters for secure communication under energy harvesting constraints.

Contribution

It derives lower bounds for secure rates without eavesdropper limitations, compares worst-case scenarios, and proposes a polynomial-time algorithm for joint optimization of power and PS coefficients.

Findings

Secrecy rate region characterized under energy harvesting constraints.

Optimal power and PS coefficient tuning achieves Pareto boundary.

Algorithm provides suboptimal solutions with quantifiable rate loss.

Abstract

The secrecy rate region of wiretap interference channels with a multi-antenna passive eavesdropper is studied under receiver energy harvesting constraints. To stay operational in the network, the legitimate receivers demand energy alongside information, which is fulfilled by power transmission and exploiting a power splitting (PS) receiver. By simultaneous wireless information and power transfer (SWIPT), the amount of leakage to the eavesdropper increases, which in turn reduces the secrecy rates. For this setup, lower-bounds for secure communication rate are derived without imposing any limitation at the eavesdropper processing. These lower-bounds are then compared with the rates achieved by assuming the worst-case linear eavesdropper processing. We show that in certain special cases the worst-case eavesdropper does not enlarge the achievable secure rate region in comparison to the unconstrained eavesdropper case. It turns out that in order to achieve the Pareto boundary of the secrecy rate region, smart tuning of the transmit power and receiver PS coefficient is required. Hence, we propose an efficient algorithm to optimize these parameters jointly in polynomial-time. The secrecy rate region characterization is formulated as a weighted max-min optimization problem. This problem turns out to be a non-convex problem due to the non-convex constrained set. This set is replaced by a convex subset that in consequence leads to an achievable suboptimal solution which is improved iteratively. By solving the problem efficiently, we obtain the amount of rate loss for providing secrecy, meanwhile satisfying the energy demands.