Toward 6G: From New Hardware Design to Wireless Semantic and Goal-Oriented Communication Paradigms

TL;DR

This paper outlines a comprehensive vision for 6G, emphasizing new hardware design, integration of AI, and a shift towards semantic and goal-oriented communication paradigms to meet future performance targets.

Contribution

It introduces key performance indicators for 6G hardware, proposes a new hardware design methodology, and advocates for a paradigm shift to goal-oriented semantic communications.

Findings

Derived crucial 6G key performance indicators for hardware and technology.

Presented a new hardware design methodology for effective integration.

Suggested a paradigm shift towards goal-oriented and semantic communication.

Abstract

Several speculative visions are conjecturing on what 6G services will be able to offer at the horizon of 2030. Nevertheless, the 6G design process is at its preliminary stages. The reality today is that hardware, technologies and new materials required to effectively meet the unprecedented performance targets required for future 6G services and network operation, have not been designed, tested or even do not exist yet. Today, a solid vision on the cost-benefit trade-offs of machine learning and artificial intelligence support for 6G network and services operation optimization is missing. This includes the possible support from hardware efficiency, operation effectiveness and, the immeasurable cost due to data acquisition-transfer-processing. The contribution of this paper is three-fold. This is the first paper deriving crucial 6G key performance indicators on hardware and technology design. Second, we present a new hardware technologies design methodology conceived to enable the effective software-hardware components integration required to meet the challenging performance envisioned for future 6G networks. Third, we suggest a paradigm shift towards goal-oriented and semantic communications, in which a totally new opportunity of joint design of hardware, artificial intelligence and effective communication is offered. The proposed vision is consolidated by our recent results on hardware, technology and machine learning performance.