Ramón Agustí

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.

Interworking in heterogeneous wireless networks: Comprehensive framework and future trends

Interworking mechanisms are of prime importance to achieve ubiquitous access and seamless mobility in heterogeneous wireless networks. In this article we develop a comprehensive framework to categorize interworking solutions by defining a generic set of interworking levels and its related key interworking mechanisms. The proposed framework is used to analyze some of the most relevant interworking solutions being considered in different standardization bodies. More specifically, I-WLAN and GAN approaches for WLAN and cellular integration, solutions for WiMAX and 3GPP LTE/SAE interworking, and the forthcoming IEEE 802.21 standard are discussed from the common point of view provided by the elaborated 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.

A near-optimum MAC protocol based on the distributed queueing random access protocol (DQRAP) for a CDMA mobile communication system

This paper presents and analyses a new near– optimum random access protocol. The proposed access scheme is suitable for a CDMA environment and minimises the total number of spreading codes needed to achieve a certain throughput. It is based on distributed queues and a collision resolution algorithm. Computer simulations have been carried out to validate the analytical model and the obtained results show that the protocol has very good stability and delay performance, even compared with medium access protocols using more available spreading codesThis paper presents and analyzes a new near-optimum medium access control (MAC) protocol. The proposed access scheme is suitable for a CDMA mobile communication environment, and keeps under control and upper bounded the number of simultaneous transmissions. It has a delay performance approaching that of an ideal optimum M/M/K system, where K is the number of spreading codes being used (maximum number of simultaneous transmissions). The protocol is a free random access protocol when the traffic load is light, and switches smoothly and automatically to a reservation protocol when traffic load becomes heavier. It is based on distributed queues and a collision resolution algorithm. Moreover, a physical receiver structure is proposed and analyzed in order to preserve the robustness of the protocol in a wireless link. The results obtained show that the protocol outperforms other well known medium access protocols in terms of stability and delay, even when taking into account the loss caused by channel propagation conditions.

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.

Spectrum sharing in cognitive radio networks with imperfect sensing: A discrete-time Markov model

An efficient and utmost utilization of currently scarce and underutilized radio spectrum resources has stimulated the introduction of what has been coined Cognitive Radio (CR) access methodologies and implementations. While the long-established approach has been based on licensed (or primary) spectrum access, this new communication paradigm enables an opportunistic secondary access to shared spectrum resources provided mutual interference is kept below acceptable levels. In this paper we address the problem of primary-secondary spectrum sharing in cognitive radio access networks using a framework based on a Discrete Time Markov Chain (DTMC) model. Its applicability and advantages with respect to other approaches is explained and further justified. Spectrum awareness of primary activity by the secondary users is based on spectrum sensing techniques, which are modeled in order to capture sensing errors in the form of false-alarm and missed-detection. Model validation is successfully achieved by means of a system-level simulator which is able to capture the system behavior with high degree of accuracy. Parameter dependencies and potential tradeoffs are identified enabling an enhanced operation for both primary and secondary users. The suitability of the specified model is justified while allowing a wide range of extended implementations and enhanced capabilities to be considered.