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Generative AI for Immersive Communication: The Next Frontier in Internet-of-Senses Through 6G
Over the past two decades, the Internet-of-Things (IoT) has been a transformative concept, and as we approach 2030, a new paradigm known as the Internet of Senses (IoS) is emerging.
GenAINet: Enabling Wireless Collective Intelligence via Knowledge Transfer and Reasoning
Connecting GenAI agents over a wireless network can potentially unleash the power of collective intelligence and pave the way for artificial general intelligence (AGI).
Large Generative AI Models for Telecom: The Next Big Thing?
To be specific, large GenAI models are envisioned to open up a new era of autonomous wireless networks, in which multi-modal GenAI models trained over various Telecom data, can be fine-tuned to perform several downstream tasks, eliminating the need for building and training dedicated AI models for each specific task and paving the way for the realization of artificial general intelligence (AGI)-empowered wireless networks.
Understanding Telecom Language Through Large Language Models
In particular, we fine-tune several LLMs including BERT, distilled BERT, RoBERTa and GPT-2, to the Telecom domain languages, and demonstrate a use case for identifying the 3rd Generation Partnership Project (3GPP) standard working groups.
The Interplay of AI and Digital Twin: Bridging the Gap between Data-Driven and Model-Driven Approaches
The evolution of network virtualization and native artificial intelligence (AI) paradigms have conceptualized the vision of future wireless networks as a comprehensive entity operating in whole over a digital platform, with smart interaction with the physical domain, paving the way for the blooming of the Digital Twin (DT) concept.
An Effective Spatial Modulation Based Scheme for Indoor VLC Systems
This scheme enhances the achievable throughput of conventional SM schemes by transmitting higher order complex modulation symbol, which is decomposed into three different parts.
Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges
New technological advancements in wireless networks have enlarged the number of connected devices.
Towards Federated Learning-Enabled Visible Light Communication in 6G Systems
Nevertheless, concerns pertaining to privacy and communication overhead when sharing raw data of the involved clients with a server constitute major bottlenecks in the implementation of centralized ML techniques.
Rate-Splitting Multiple Access: Unifying NOMA and SDMA in MISO VLC Channels
Then, we introduce rate-splitting multiple access (RSMA), which was initially proposed for RF systems and discuss its potentials in VLC systems.
Large Intelligent Surface Assisted Non-Orthogonal Multiple Access: Performance Analysis
Specifically, we consider a downlink NOMA system, in which data transmission between a base station (BS) and $L$ NOMA users is assisted by an LIS comprising $M$ reflective elements.
Non-Orthogonal Multiple Access in the Presence of Additive Generalized Gaussian Noise
The derived PEP expression is subsequently utilized to derive a union bound on the bit error rate (BER) and to quantify the diversity orders realized by NOMA users in the presence of additive white (AW) GGN.
A Prospective Look: Key Enabling Technologies, Applications and Open Research Topics in 6G Networks
To accommodate the stringent requirements of their prospective applications, which are data-driven and defined by extremely low-latency, ultra-reliable, fast and seamless wireless connectivity, research initiatives are currently focusing on a progressive roadmap towards the sixth generation (6G) networks.
