Analysis of Channel Uncertainty in Trusted Wireless Services via Repeated Interactions

TL;DR

This paper examines how wireless channel unreliability affects trust-building in 6G heterogeneous networks using blockchain and repeated interactions, proposing models and optimizations to sustain secure services.

Contribution

It introduces a repeated game framework to analyze and optimize trust and cooperation under channel uncertainty in blockchain-based wireless networks.

Findings

Channel unreliability impacts trust cooperation

Optimized strategies improve service resilience

Trade-offs between efficiency, security, and cooperation

Abstract

The coexistence of heterogeneous sub-networks in 6G poses new security and trust concerns and thus calls for a perimeterless-security model. Blockchain radio access network (B-RAN) provides a trust-building approach via repeated interactions rather than relying on pre-established trust or central authentication. Such a trust-building process naturally supports dynamic trusted services across various service providers (SP) without the need for perimeter-based authentications; however, it remains vulnerable to environmental and system unreliability such as wireless channel uncertainty. In this study, we investigate channel unreliability in the trust-building framework based on repeated interactions for secure wireless services. We derive specific requirements for achieving cooperation between SPs and clients via a repeated game model and illustrate the implications of channel unreliability on sustaining trusted wireless services. We consider the framework design and optimization to guarantee SP-client cooperation, given the worst channel condition and/or the least cooperation willingness. Furthermore, we explore the maximum cooperation area to enhance service resilience and reveal the trade-off relationship between transmission efficiency, security integrity, and cooperative margin. Finally, we present simulations to demonstrate the system performance over fading channels and verify our results.