# The 6G Ecosystem as Support for IoE and Private Networks: Vision, Requirements, and Challenges
## 3 Background and Current Development of 6G
RIS equipped with computing resources seems to be a promising solution to dynamically reconfigure physical parameters for enhancing wireless system design and optimization. Their adaptability allows for improved signal propagation, channel modeling and acquisition, and creating intelligent radio environments that are advantageous for 6G innovative applications, i.e., the electromagnetic environment can be reshaped as needed. Envisioned as a remarkable platform, 6G aims to integrate diverse network policies, devices, and algorithms, fostering cognitive-aware, user-centric mobile operations and mitigation strategies [16]. It is expected that 6G will demand an extensive spectrum allocation to support future mobile operations. Unlike the current range of existing 5G bands, which relies on mMIMO orchestration, which falls within the 1-30 GHz range, 6G is projected to rely on cell-free m-MIMO and utilize a spectrum extending from IR and visible light and 30-300 GHz, mmWave, or even beyond, THz wave, for its operations and for delivering efficient user-centric services [5; 13; 68]. The development of novel access methods is imperative to support extensive multiple access techniques in 6G. Among the noteworthy approaches from the literature review, we can underscore delta-orthogonal multiple access (D-OMA), filter bank multi-carrier (FBMC), and sparse code multiple access (SCMA). The D-OMA strategy leverages distributed large CoMP concepts, facilitating NOMA transmission through partially overlapping sub-bands within NOMA clusters [69]. SCMA prioritizes overall sum rates in cloud radio access network (C-RAN) scenarios, employing single-input single-output (SISO) systems and a low-complexity algorithm that considers individual user QoS, user association, and power constraints [70]. FBMC, compared to conventional OFDM systems, boasts diminished spectral side-lobes, granting it the capability for asynchronous transmission [71]. Novel breakthroughs in terahertz and optical communications will be crucial in unlocking unprecedented data transfer and communication speeds. Additionally, cell-less or poor coverage areas through integrated terrestrial satellite access technologies [72] will ensure seamless connectivity across vast areas, extending the reach of communication networks to remote and challenging locations [42]. The advent of 6G technology is set to profoundly reshape the landscape of communication progress, encompassing intelligent, deep, holographic, and pervasive connectivity, thus profoundly shaping the evolution of the intelligence process within communication [2]. Distributed end-user terminal-based AI [46; 73] will bring intelligence and decision-making capabilities closer to the user, enabling personalized and context-aware services. Moreover, the integration of distributed ledger technologies (DLTs) [74] will enhance security, transparency, and efficiency in data handling and transactions across the network to fulfill the needs of emerging applications [42]. On the other hand, AI holds the potential to [4] enhance handover operation performance by considering network deployments and geographic conditions; optimize network planning by determining base station (BS) locations; lower network energy consumption; forecast, identify, and facilitate self-healing of network irregularities; predict channel coding for more extensive bit sequences, establishing resilient synchronization to meet 6G prerequisites, facilitating mobile positioning in nLoS environments with multiple paths, conducting non-linear and non-stationary channel estimation, and implementing adaptive, RT mMIMO beamforming to represent pivotal ML applications within the physical layer. DLT technologies drive the urgency for an intelligent self-organizing network (SON) capable of managing network operations, resources, and optimizations. So 6G will have to guarantee the transition from traditional SON, which adapts functions automatically to environment states, to a self-sustaining network (SSN).