User Pairing and Power Allocation in Untrusted Multiuser NOMA for Internet-of-Things

TL;DR

This paper proposes a secure resource allocation framework for multiuser NOMA in IoT, optimizing sum secrecy rate while managing power and user pairing, with proven convergence and superior performance.

Contribution

It introduces a novel iterative solution for joint user pairing and power allocation in untrusted multiuser NOMA systems, enhancing security and efficiency.

Findings

Outperforms existing methods in sum secrecy rate

Reduces computational complexity significantly

Ensures convergence of the proposed algorithm

Abstract

In the Internet-of-Things (IoT), massive sensitive and confidential information is transmitted wirelessly, making security a serious concern. This is particularly true when technologies, such as non-orthogonal multiple access (NOMA), are used, making it possible for users to access each other's data. This paper studies secure communications in multiuser NOMA downlink systems, where each user is potentially an eavesdropper. Resource allocation is formulated to achieve the maximum sum secrecy rate, meanwhile satisfying the users' data requirements and power constraint. We solve this non-trivial, mixed-integer non-linear programming problem by decomposing it into power allocation with a closed-form solution, and user pairing obtained effectively using linear programming relaxation and barrier algorithm. These subproblems are solved iteratively until convergence, with the convergence rate rigorously analyzed. Simulations demonstrate that our approach outperforms its existing alternatives significantly in the sum secrecy rate and computational complexity.