86 research outputs found
Cognitive control channels for the cooperation of opportunistic and composite wireless networks
Opportunistic networks (ONs) are considered as coordinated extensions of a radio access network infrastructure, which are dynamically and temporarily created in an infrastructure-less manner in order to increase service reachability, improve resource utilization efficiency and facilitate localised service provisioning. The realization of the ON concept relies on the existence of control channels which will provide necessary signalling for the coordination of the ON
nodes. Proposed control channels are conceived as an evolution of the already established cognitive pilot channel
concept. As a result, new interfaces are discussed in order to convey information from the infrastructure to the terminals
and vice versa or between terminals. Finally, the business benefits of the aforementioned approach are provided in
order to strengthen the notion of the proposed control channels and consider future expansions.Peer ReviewedPostprint (published version
Control channels for the cooperation of cognitive management systems in opportunistic and composite wireless networks
Opportunistic Networks (ONs) are assumed to be temporary, localized extensions of the
infrastructure network that are created under certain circumstances. According to that vision, ONs
are coordinated by the radio access network (RAN) operator which governs the overal system
behaviour (e.g. ON related policies), provides the neccessary resources (e.g. dedicated specturm
bands) and supports users in decision making (e.g. additional knowledge and context information). ONs comprise both nodes of the infrastructure and infrastructure-less devices. For the management and control of operator-governed ONs the introduction of Cognitive Management Systems (CMSs), localized on the terminal and infrastructure side, is proposed. The cooperation of
CMS entities will require existence of well-defined control channels. In order to enable the necessary signalling between the CMS entities, Control Channels for the Cooperation of the Cognitive Management Systems (C4 MS) are proposed.Peer ReviewedPostprint (published version
Cognitive pilot channel: A radio enabler for spectrum awareness and optimized radio resource management
Today’s wireless communications landscape is characterized by the coexistence of a plethora of disparate radio access technologies (RATs), which exhibit varying features in terms of capacity and coverage capabilities, mobility support etc. and also offer a great number of applications and services to different types of devices. In such a miscellaneous environment, mobile terminals are provided with a great set of options while setting up the parameters of their operation including among others the RAT, carrier frequency, and must also take into account the latest trend towards a flexible spectrum framework in heterogeneous radio access networks (RANs). As a result, in order to implement the optimal action, a mobile terminal needs to be enabled to acquire knowledge of its environment and established policies. Apart from mobilizing a rather time- and power-consuming operation such as spectrum sensing, the Cognitive Pilot Channel (CPC) concept has been proposed as a solution for providing the terminal with the necessary radio awareness at a given time and place, in a possible flexible spectrum management context. Framed within the above, this paper, developed within the E3 project, aims at describing the CPC concept by showcasing its twofold role. First, as an enabler of the switch-on process for assisting the mobile terminal to camp onto the network side and second, as an enabler of an efficient decentralized and network-assisted radio resource management during the on-going communication phase.Postprint (published version
Quality-of-Trust in 6G: combining emotional and physical trust through explainable AI
Wireless networks like many multi-user services have to balance limited resources in real-time. In 6G, increased network automation makes consumer trust crucial. Trust is reflect in both a personal emotional sentiment as well as a physical understanding of the transparency of AI decision making. Whilst there has been isolated studies of consumer sentiment to wireless services, this is not well linked to the decision making engineering. Likewise, limited recent research in explainable AI (XAI) has not established a link to consumer perception.Here, we develop a Quality-of-Trust (QoT) KPI that balances personal perception with the quality of decision explanation. That is to say, the QoT varies with both the time-varying sentiment of the consumer as well as the accuracy of XAI outcomes. We demonstrate this idea with an example in Neural Water-Filling (N-WF) power allocation, where the channel capacity is perceived by artificial consumers that communicate through Large Language Model (LLM) generated text feedback. Natural Language Processing (NLP) analysis of emotional feedback is combined with a physical understanding of N-WF decisions via meta-symbolic XAI. Combined they form the basis for QoT. Our results show that whilst the XAI interface can explain up to 98.9% of the neural network decisions, a small proportion of explanations can have large errors causing drops in QoT. These drops have immediate transient effects in the physical mistrust, but emotional perception of consumers are more persistent. As such, QoT tends to combine both instant physical mistrust and long-term emotional trends.We acknowledge funding from EC H2020 (778305), and EPSRC (EP/X040518/1
ETSI RRS - The Standardization Path to Next Generation Cognitive Radio Systems
This paper details the current work status of the ETSI Reconfigurable Radio Systems (RRS) Technical Committee (TC) and gives an outlook on the future evolution. While previous publications have presented an overview of ETSI RRS' main working axes related to i) Cognitive Radio System Aspects, ii) Radio Equipment Architecture (including a Cognitive Pilot Channel (CPC) proposal and a Functional Architecture (FA) for Management and Control of Reconfigurable Radio Systems), iii) Cognitive Management and Control and iv) Public Safety, this document focuses on latest progress related to UHF White Spaces work and the definition of an SDR Handset Architecture. In particular, it is outlined how Cognitive Radio principles can help to adapt existing and/or evolving Radio Standards, such as 3GPP Long Term Evolution, to a possible operation in UHF White Space bands
ETSI reconfigurable radio systems: status and future directions on software defined radio and cognitive radio standards
This article details the current work status of the ETSI Reconfigurable Radio Systems Technical Committee, positions the ETSI work with respect to other standards efforts (IEEE 802, IEEE SCC41) as well as the European Regulatory Framework, and gives an outlook on the future evolution. In particular, software defined radio related study results are presented with a focus on SDR architectures for mobile devices such as mobile phones. For MDs, a novel architecture
and inherent interfaces are presented enabling the usage of SDR principles in a mass market context. Cognitive radio principles within ETSI RRS are concentrated on two topics, a cognitive pilot channel proposal and a Functional Architecture for Management and control of reconfigurable radio systems, including dynamic self-organizing planning and management, dynamic spectrum management, joint radio resource management. Finally, study results are
indicated that are targeting a SDR/CR security framework.Postprint (published version
Protocols, performance assessment and consolidation on interfaces for standardization – D3.3
The following document presents a detailed description of the protocol for the “
Control Channels for the Cooperation of the Cognitive Management System
” (C4MS) which provides the necessary means
to enable proper management of Opportunistic Networks.
Additionally, the document defines the
methodology that was applied for the purpose of signalling evaluation.
The protocol overview presented in section
2 of the main document, provides the
C4MS principles.
The section includes, among others, the description of the protocol identifiers,
procedures, protocol state machines and message format as well as the security asp
ects.
Section 3 provides a high-level description of the data structures defined within the scope of OneFIT project. The data structures are classified into five categories, i.e.: Profiles, Context, Decisions,Knowledge and Policies. The high level description is complemented by some detailed data
structures in the Appendix to D3.3 Section
3[10].
Section 4 provides details on the evaluation methodology applied for the purpose of C4MS
performance assessment. The section presents
the evaluation plan along with a description of metrics that are to be exploited in the scope of WP3.
Section 5 and Section 6 are composed of the signalling evaluation results. Section 5
focuses on the estimation of the signalling load imposed by ON management in different ON phases. Additionally some results for the initialization phase (not explicitly mentioned in the previous phases of the
project)and security related aspects are also depicted. Section 6 on the other hand is
focused on the evaluation of the
signalling traffic generated by
different ON related algorithms.
Conclusions to the document are drawn in section 7. Detailed description of the C4MS procedures, implementation options based on IEEE 802.21, DIAMTER and 3GPP are depicted in the appendix to the D3.3[10]
. Additionally, the appendix incorporates the detailed definition of the information data structures and final set of Message Sequence Charts (MSCs) provided for
the OneFIT project.Peer ReviewedPreprin
Formulations and identification of algorithmic solutions for enabling opportunistic networks - M4.1
Milestone M4.1 del projecte Europeu OneFIT (ICT-2009-257385).This document contains a detailed description of the algorithms to be implemented to manage the opportunistic networks. There are defined according to the functional and system architecture (WP2) to fulfil the technical challenges.
These algorithms will implemented during the WP4.2 and validated during the WP4.3Postprint (published version
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