Dynamic D2D Communication in 5G/6G Using a Distributed AI Framework

Abstract

This paper focuses on D2D communication for 5G/6G in dynamic environments where the D2D network topology changes through time due to D2D Devices' mobility. Specifically, we consider a scenario within the coverage area of a Base Station (BS) serving a number of User Devices (UEs), with variations in speed and direction causing changes in the D2D network topology, either via direct connections or via D2D single-hop or D2D Multi-hop paths.Based on this scenario, we formulate a problem aiming to maximise the total Spectral Efficiency (SE) whilst minimising the total Power Consumption (PC), by selecting the best transmission mode that the D2D devices will operate. In order to address the aforementioned problem, the Distributed Artificial Intelligence Solution (DAIS) plan proposed in our earlier work and designed for static environments is extended to consider the mobility (i.e., speed, direction and indirectly link distance change) of the D2D Device, targeting the dynamic creation of stable and efficient clusters and good backhauling links towards the gateway. The enhanced DAIS performance is comparatively evaluated in terms of SE and PC against selected variations in UE speed and direction, changes in the link Transmission Power (TP), and an increase in the number of Devices in the D2D network. Overall, the results obtained demonstrated superior performance of enhanced DAIS over all the other related investigated approaches (i.e., Distributed Sum Rate (DSR), Single Hop Relay Approach (SHRA), Distributed Random (DR)), in terms of Spectral Efficiency (SE) and Power Consumption (PC). Also, the ability of enhanced DAIS to react and adapt quickly and efficiently to D2D network topology changes, with reduced signalling overhead and control delay in responding to changes, shows that it is a well-poised approach to be used in a Dynamic D2D Environment.

A Distributed AI Framework for Nano-Grid Power Management and Control

“…In addition, DAI regulates a type of distributed control strategy that addresses complex learning, planning, and decision-making issues [8]- [10]. This DAI approach enables a perfectly parallel workload 3 .…”

“…Their additional functionality is comprised of their Beliefs, Desires, Goals, Intentions, and Behaviour (see e.g. [1]- [3], [15], [16]):…”

“…• The BDI Behaviour is defined by its Perception and the Plans in its Planning Library that correspond to its Desires. To be more specific: 3 A fully parallel workload in parallel computing requires little or no manipulation to divide the issue into a number of parallel tasks [11] with distributed control thanks to its application. This is frequently the case when there is little to no dependence or communication requirement between the parallel activities.…”

“…This research advocates and develops a Distributed AI (DAI) framework, initially developed and evaluated within a mobile communication environment [1]- [3]. At the heart of this framework are Belief-Desire-Intention Extended (BDIx) agents.…”

Random Directional Access with and without Feedback for 5G/6G Peer-to-Peer Networks

“…Just the availability of ICenabled receivers has stimulated the design of many evolved SA-based schemes, relying on packet repetition [3], [4], code diversity [5], non-orthogonal multiple access [6], as well as on combinations of these techniques [7], [8]. On the other hand, the compactness characteristics of the millimeter-wave (mmWave) radiating equipments [9]- [11], have invited to rediscover the application of analog beamforming to provide spatial multiplexing [12]- [14], to address the 5G initial access problem [15], [16], and to provide joint terrestrial/nonterrestrial link support to 5G/6G gateways [17], [18]. Besides, within the next-generation standards, peer-to-peer connections, in the form of device-to-device or machine-to-machine communications, are expected to play a key role for offloading the core network and reducing the end-to-end delay, even more in the presence of massive inhomogeneous traffics.…”