Jordi Pérez-Romero

A novel on-demand cognitive pilot channel enabling dynamic spectrum allocation

This paper addresses the implementation of the cognitive pilot channel (CPC), which has been recently proposed as a solution to assist the mobile reconfigurable and cognitive terminals in heterogeneous wireless scenarios with different access networks available and varying spectrum allocations. The paper describes the operation of the CPC and the different approaches existing in the literature depending on how it is mapped onto specific radio resources. Then, it focuses on the implementation of the CPC information delivery and proposes the use of an on-demand CPC, which requires a significantly lower bit rate than the broadcast approach to achieve similar performance.

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.

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

In this paper, an innovative mechanism to perform joint radio resource management (JRRM) in the context of heterogeneous radio access networks is introduced. In particular, a fuzzy neural algorithm that is able to ensure certain quality-of-service (QoS) constraints in a multicell scenario deployment with three different radio access technologies (RATs), namely, the wireless local area network (WLAN), the universal mobile telecommunication system (UMTS), and the global system for mobile communications (GSM)/Enhanced Data rates for GSM Evolution (EDGE) radio access network (GERAN), is discussed. The proposed fuzzy neural JRRM algorithm is able to jointly manage the common available radio resources operating in two steps. The first step selects a suitable combination of cells built around the three available RATs, while the second step chooses the most appropriate RAT to which a user should be attached. A proper granted bit rate is also selected for each user in the second step. Different implementations are presented and compared, showing that the envisaged fuzzy neural methodology framework, which is able to cope with the complexities and uncertainties of heterogeneous scenarios, could be a promising choice. Furthermore, simulation results show that the reinforcement learning mechanisms introduced in the proposed JRRM methodology allow guaranteeing the QoS requirement in terms of the so-called user dissatisfaction probability in the presence of different traffic loads and under different dynamic situations. Also, the proposed framework is able to take into consideration different operator policies as well as different subjective criteria by means of a multiple decision-making mechanism, such as balancing the traffic among the RATs or giving more priority to the selection of one RAT in front of another one.

A Markovian Approach to Radio Access Technology Selection in Heterogeneous Multiaccess/Multiservice Wireless Networks

This paper addresses the problem of radio access technology (RAT) selection in heterogeneous multi-access/multi-service scenarios. For such purpose, a Markov model is proposed to compare the performance of various RAT selection policies within these scenarios. The novelty of the approach resides in the embedded definition of the aforementioned RAT selection policies within the Markov chain. In addition, the model also considers the constraints imposed by those users with terminals that only support a subset of all the available RATs (i.e. multi-mode terminal capabilities). Furthermore, several performance metrics may be measured to evaluate the behaviour of the proposed RAT selection policies under varying offered traffic conditions. In order to illustrate the validation and suitability of the proposed model, some examples of operative radio access networks are provided, including the GSM/EDGE Radio Access Network (GERAN) and the UMTS Radio Access Network (UTRAN), as well as several service-based, load-balancing and terminal-driven RAT selection strategies. The flexibility exhibited by the presented model enables to extend these RAT selection policies to others responding to diverse criteria. The model is successfully validated by means of comparing the Markov model results with those of system-level simulations.

A fuzzy-neural based approach for joint radio resource management in a beyond 3G framework

This paper presents a comprehensive framework to develop joint RRM (radio resource management) strategies taking full advantage of the reconfigurable equipment capabilities and the diversity offered by available RATs (radio access technologies) in a multi-radio environment. The envisaged JRRM treatment calls for establishing links with all the entities involved, first at functional level, identifying realistic scenarios in terms of deployment, technologies and services, and managing the emerging complexity with proper algorithms. Then, a fuzzy-neural methodology framework able to cope with the complexities and uncertainties these new scenarios rise is presented. In particular both technical and economical aspects are considered when selecting a particular RAT. Finally some significant examples of the algorithm behaviour are shown.

Common radio resource management: functional models and implementation requirements

Common radio resource management strategies are devoted to achieve an efficient usage of the pool of radio resources available in a heterogeneous radio access network context. This paper describes the functionalities associated with the common vision of radio access technologies, the different possibilities in the functional model split and the corresponding implementation considerations

Spectral occupation measurements and blind standard recognition sensor for cognitive radio networks

Cognitive radio has been claimed to be a hopeful solution to the existing conflicts between spectrum demand growth and spectrum underutilization. The basic underlying idea of cognitive radio is to allow unlicensed users to access in an opportunistic and non-interfering manner some licensed bands temporarily unoccupied by licensed users. The cognitive radio concept relies on two basic premises: the current spectrum underutilization, which has been demonstrated in some spectrum measurements campaigns, and the ability of unlicensed users to effectively detect and identify the presence of different licensed technologies in order not to cause harmful interference. In this context, this paper reports the joint work on these two areas that is currently being carried out in the framework of the FP7 Network of Excellence in Wireless COMmunications (NEWCOM++). Concretely, this paper presents spectrum occupancy measurements conducted in the frequency range from 75 MHz to 7075 MHz that demonstrate the low degree to which spectrum is currently used in an urban outdoor environment and also describes the blind standard recognition sensor concept, a sensor embedded in a cognitive radio equipment to enable the identification of many commercial wireless standards without the need to connect to any network. The joint research in both areas is a key step in promoting and validating the idea of dynamic spectrum usage.

Joint radio resource management algorithm for multi-RAT networks

This paper presents a joint radio resource management algorithm to operate in a heterogeneous network scenario including cellular and wireless local area network radio access technologies. It makes use of a methodology based on fuzzy-neural systems in order to carry out a coordinated management of the radio resources among the different access networks. In order to reveal the potentials of the proposed algorithm, it is compared with other strategies in a multicellular and multi-RAT scenario

Provisioning multimedia wireless networks for better QoS: RRM strategies for 3G W-CDMA

Third-generation mobile communication systems will bring a wide range of new services with different quality of service requirements and will open the ability to exploit radio resource management functions to guarantee a certain target QoS, to maintain the planned coverage area and to offer a high-capacity while using the radio resources in an efficient way. RRM functions impact the overall system efficiency and the operator infrastructure cost, so they will definitively play an important role in a mature 3G scenario. In order to provide some insight into radio resource management (RRM) strategies implementation, a range of representative case-studies with several innovative algorithms are presented and supported by simulation results in a realistic UMTS Terrestrial Radio Access Network scenario as devised in the 3GGP standardization forum. In particular, a decentralized uplink transmission rate selection algorithm in the short term, a congestion control mechanism to cope with overload situations, and downlink scheduling for layered streaming video packets are proposed.

A novel joint radio resource management approach with reinforcement learning mechanisms

This paper presents a novel JRRM strategy based on reinforcement learning mechanisms that control a fuzzy-neural algorithm to ensure certain QoS constraints. Three RATs (radio access technologies), namely UMTS, GERAN and WLAN are considered as common available technologies to select. The fuzzy logic allows for a very simple handling of the joint radio resource manager simply by activating a set of rules. The membership functions considered by these rules are adaptive so that a desired performance in terms of the probability of user satisfaction can be guaranteed by means of the reinforcement learning algorithm. Some illustrative simulation results to evaluate the behaviour of the proposed JRRM technique are presented.