A Novel Approach for Joint Radio Resource Management Based on Fuzzy Neural Methodology

Giupponi, Lorenza; Agustí, R.; Perez-Romero, J.; Roig, O.

doi:10.1109/tvt.2007.907012

Cited by 102 publications

(63 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1 The selling/buying period should not be too long (e.g., months or years) to make dynamic spectrum access infeasible, and it should not be too short (e.g., seconds or minutes) to incur overwhelming overhead in spectrum trading. The typical duration is hours or days as shown in [12]. In the rest of paper, we assume that all the spectrum transactions are of fixed duration, so that the time parameter is not included in our formulation.…”

Section: B Reward and Risk For Osamentioning

confidence: 99%

Reward and Risk for Opportunistic Spectrum Accessing in Cognitive Radio Networks

Pan

Song

et al. 2010

2010 IEEE Global Telecommunications Conference GLOBECOM 2010

View full text Add to dashboard Cite

Abstract-Cognitive Radio technology releases the spectrum from shackles of authorized licenses and facilitates the trading of spectrum bands. In the spectrum market, primary service providers (PSPs) set price for the vacant licensed bands of primary users (PUs) and sell them for monetary gains, and the secondary service provider (SSP) can buy the bands and opportunistically use them to satisfy the service demands of secondary users (SUs) when the primary services are not active. However, when there are multiple bands available, the SSP confronts the challenges of how to choose bands and how to split the overall traffic on them considering both his monetary reward and the potential risk, from the unpredictable activities of the primary services, for opportunistic spectrum accessing (OSA). In this paper, we propose a reward and risk based band-mix selection algorithm to address these concerns of the SSP, and help the SSP to make appropriate decisions of traffic splitting over available spectrum band-mix, consisting of both the band belonging to SSP itself and the bands from PSPs. By numerical simulations, we verify our theoretical analysis and show that the proposed spectrum band-mix selection effectively improves the spectrum utilization as well as the satisfactory degree of SUs.

show abstract

Section: B Reward and Risk For Osamentioning

confidence: 99%

Reward and Risk for Opportunistic Spectrum Accessing in Cognitive Radio Networks

Pan

Song

et al. 2010

2010 IEEE Global Telecommunications Conference GLOBECOM 2010

View full text Add to dashboard Cite

show abstract

“…This function has to be crosslayer defined, since it depends on functionalities defined at different layers of the communication stack: the frequency channel decision making procedure should be carried out by considering multiple criteria such as interference at the primary user receivers, pathloss in the available frequency channels, wireless link errors, primary user activity, spectrum availability, routing and transport requirements, application requirements, etc. [27]. The spectrum handoff functionality is in charge of vacating a primary channel due to, e.g., the sudden activation of a primary user in that channel, or degradation of secondary user QoS.…”

Section: Cognitive Networkmentioning

confidence: 99%

Cross-layer radio resource allocation: The journey so far and the road ahead

Corvino

Giupponi

Neira

et al. 2009

2009 Second International Workshop on Cross Layer Design

View full text Add to dashboard Cite

Abstract-The cross-layer concept originated almost ten years ago with the aim of taking the most advantage from the difficult wireless media to break the barriers imposed by the layered transmission. One of the domains where cross-layer design has been more investigated is Radio Resource Allocation, since current and future networks need to provide wireless connectivity to heterogeneous users, offering many different data traffic types. Nonetheless, new paradigms are emerging in the field of wireless communications, like cognitive radios, wireless systems with relays and Multiple Input Multiple Output (MIMO) systems, where the potential advantages of cross-layer scheduling are still largely unknown. Moreover, in spite of a large literature on cross-layer, in the most cases different focuses and perspectives, biased by the application(s), are addressed, thus, there is lack of a general framework. The main goal of this paper is not to provide a state of the art on cross-layer scheduling and resource allocation, since this would result maybe in a heterogeneous list of scientific contributions. Rather, we are interested in performing a cataloguing of the work so far, trying to identify common tools and general frameworks used for cross-layer resource allocation, justify them by means of specific network examples and highlight open issues and challenges to be faced. Nevertheless, a preliminary objective of this work is to introduce a set of definitions which can be hopefully agreed by the scientific community.

show abstract

“…This algorithm uses Particle Swarm Optimization, Fuzzy logic controller, Genetic Algorithm and decision making algorithm for the selection of RAT. The fuzzy neural mechanism is used in [12] and [13] for the selection of best RAT among UMTS, GERAN and WLAN. Thus many RAT selection algorithms are available for the selection of RAT.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Modified Particle Swarm Optimization for Heterogeneous Radio Access Technology (RAT) Selection

Preethi¹,

Palaniswami²

2012

IJCA

View full text Add to dashboard Cite

A Novel Approach for Joint Radio Resource Management Based on Fuzzy Neural Methodology

Cited by 102 publications

References 18 publications

Reward and Risk for Opportunistic Spectrum Accessing in Cognitive Radio Networks

Reward and Risk for Opportunistic Spectrum Accessing in Cognitive Radio Networks

Cross-layer radio resource allocation: The journey so far and the road ahead

A Hybrid Modified Particle Swarm Optimization for Heterogeneous Radio Access Technology (RAT) Selection

Contact Info

Product

Resources

About