# Truth-Telling Mechanism for Secure Two-Way Relay Communications with Energy-Harvesting Revenue

## TL;DR

This paper introduces a truthful relay selection mechanism in secure two-way energy-harvesting communications, ensuring relays reveal true information and optimizing beamforming and power with reduced computational complexity.

## Contribution

It proposes a novel incentive mechanism for truthful relay selection and a low-complexity SOCP-based joint beamforming and power optimization scheme.

## Key findings

- The incentive mechanism effectively enforces truth-telling among relays.
- The SOCP approach reduces computational complexity significantly.
- Numerical results demonstrate improved secrecy sum rate and energy harvesting performance.

## Abstract

This paper brings the novel idea of paying the utility to the winning agents in terms of some physical entity in cooperative communications. Our setting is a secret two-way communication channel where two transmitters exchange information in the presence of an eavesdropper. The relays are selected from a set of interested parties such that the secrecy sum rate is maximized. In return, the selected relay nodes' energy harvesting requirements will be fulfilled up to a certain threshold through their own payoff so that they have the natural incentive to be selected and involved in the communication. However, relays may exaggerate their private information in order to improve their chance to be selected. Our objective is to develop a mechanism for relay selection that enforces them to reveal the truth since otherwise they may be penalized. We also propose a joint cooperative relay beamforming and transmit power optimization scheme based on an alternating optimization approach. Note that the problem is highly non-convex since the objective function appears as a product of three correlated Rayleigh quotients. While a common practice in the existing literature is to optimize the relay beamforming vector for given transmit power via rank relaxation, we propose a second-order cone programming (SOCP)-based approach in this paper which requires a significantly lower computational task. The performance of the incentive control mechanism and the optimization algorithm has been evaluated through numerical simulations.