An improved multi-agent simulation methodology for modelling and evaluating wireless communication systems resource allocation algorithms

Multi-Agent Systems (MAS) constitute a well known approach in modelling dynamical real world systems. Recently, this technology has been applied to Wireless Communication Systems (WCS), where efficient resource allocation is a primary goal, for modelling the physical entities involved, like Base Stations (BS), service providers and network operators. This paper presents a novel approach in applying MAS methodology to WCS resource allocation by modelling more abstract entities involved in WCS operation, and especially the concurrent network procedures (services). Due to the concurrent nature of a WCS, MAS technology presents a suitable modelling solution. Services such as new call admission, handoff, user movement and call termination are independent to one another and may occur at the same time for many different users in the network. Thus, the required network procedures for supporting the above services act autonomously, interact with the network environment (gather information such as interference conditions), take decisions (e.g. call establishment), etc, and can be modelled as agents. Based on this novel simulation approach, the agent cooperation in terms of negotiation and agreement becomes a critical issue. To this end, two negotiation strategies are presented and evaluated in this research effort and among them the distributed negotiation and communication scheme between network agents is presented to be highly efficient in terms of network performance. The multi-agent concept adapted to the concurrent nature of large scale WCS is, also, discussed in this paper

A distributed channel allocation scheme for cellular network using intelligent software agents

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A survey of self organisation in future cellular networks

This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks

Distributed Artificial Intelligence Solution for D2D Communication in 5G Networks

Device to Device (D2D) Communication is one of the technology components of the evolving 5G architecture, as it promises improvements in energy efficiency, spectral efficiency, overall system capacity, and higher data rates. The above noted improvements in network performance spearheaded a vast amount of research in D2D, which have identified significant challenges that need to be addressed before realizing their full potential in emerging 5G Networks. Towards this end, this paper proposes the use of a distributed intelligent approach to control the generation of D2D networks. More precisely, the proposed approach uses Belief-Desire-Intention (BDI) intelligent agents with extended capabilities (BDIx) to manage each D2D node independently and autonomously, without the help of the Base Station. The paper includes detailed algorithmic description for the decision of transmission mode, which maximizes the data rate, minimizes the power consumptions, while taking into consideration the computational load. Simulations show the applicability of BDI agents in jointly solving D2D challenges.Comment: 10 pages,9 figure