Secure Transmission in NOMA-enabled Industrial IoT with Resource-Constrained Untrusted Devices

TL;DR

This paper develops a joint optimization framework for secure NOMA-enabled IIoT networks with resource-constrained untrusted devices, deriving a global-optimal solution that enhances secrecy fairness and outperforms benchmark schemes.

Contribution

It introduces a novel joint optimization approach for secure NOMA in IIoT with resource constraints, including optimal decoding order and power allocation, with a closed-form global-optimal solution.

Findings

Joint optimization improves secrecy fairness significantly.

Optimal decoding order differs from conventional strategies.

Achieves up to 98.16% gain over benchmark schemes.

Abstract

The security of confidential information associated with devices in the industrial Internet of Things (IIoT) network is a serious concern. This article focuses on achieving a nonorthogonal multiple access (NOMA)-enabled secure IIoT network in the presence of untrusted devices by jointly optimizing the resources, such as decoding order and power allocated to devices. Assuming that the devices are resource-constrained for performing perfect successive interference cancellation (SIC), we characterize the residual interference at receivers with the linear model. Firstly, considering all possible decoding orders in an untrusted scenario, we obtain secure decoding orders that are feasible to obtain a positive secrecy rate for each device. Then, under the secrecy fairness criterion, we formulate a joint optimization problem of maximizing the minimum secrecy rate among devices. Since the formulated problem is non-convex and combinatorial, we first obtain the optimal secure decoding order and then solve it for power allocation by analyzing Karush-Kuhn-Tucker points. Thus, we provide the closed-form global-optimal solution of the formulated optimization problem. Numerical results validate the analytical claims and demonstrate an interesting observation that the conventional decoding order and assigning more power allocation to the weak device, as presumed in many works on NOMA, is not an optimal strategy from the secrecy fairness viewpoint. Also, the average percentage gain of about 22.75%, 50.58%, 94.59%, and 98.16%, respectively, is achieved by jointly optimized solution over benchmarks ODEP (optimal decoding order, equal power allocation), ODFP (optimal decoding order, fixed power allocation), FDEP (fixed decoding order, equal power allocation), and FDFP (fixed decoding order, fixed power allocation).