Resource Allocation for Cellular/WLAN Integrated Networks

The next-generation wireless communications have been envisioned to be supported by heterogeneous networks using various wireless access technologies. The popular cellular networks and wireless local area networks (WLANs) present perfectly complementary characteristics in terms of service capacity, mobility support, and quality-of-service (QoS) provisioning. The cellular/WLAN interworking is thus an effective way to promote the evolution of wireless networks. As an essential aspect of the interworking, resource allocation is vital for efficient utilization of the overall resources. Specially, multi-service provisioning can be enhanced with cellular/WLAN interworking by taking advantage of the complementary network strength and an overlay structure. Call assignment/reassignment strategies and admission control policies are effective resource allocation mechanisms for the cellular/WLAN integrated network. Initially, the incoming calls are distributed to the overlay cell or WLAN according to call assignment strategies, which are enhanced with admission control policies in the target network. Further, call reassignment can be enabled to dynamically transfer the traffic load between the overlay cell and WLAN via vertical handoff. By these means, the multi-service traffic load can be properly shared between the interworked systems. In this thesis, we investigate the load sharing problem for this heterogeneous wireless overlay network. Three load sharing schemes with different call assignment/reassignment strategies and admission control policies are proposed and analyzed. Effective analytical models are developed to evaluate the QoS performance and determine the call admission and assignment parameters. First, an admission control scheme with service-differentiated call assignment is studied to gain insights on the effects of load sharing on interworking effectiveness. Then, the admission scheme is extended by using randomized call assignment to enable distributed implementation. Also, we analyze the impact of user mobility and data traffic variability. Further, an enhanced call assignment strategy is developed to exploit the heavy-tailedness of data call size. Last, the study is extended to a multi-service scenario. The overall resource utilization and QoS satisfaction are improved substantially by taking into account the multi-service traffic characteristics, such as the delay-sensitivity of voice traffic, elasticity and heavy-tailedness of data traffic, and rate-adaptiveness of video streaming traffic

Robustness of optimal channel reservation using handover prediction in multiservice wireless networks

The aim of our study is to obtain theoretical limits for the gain that can be expected when using handover prediction and to determine the sensitivity of the system performance against different parameters. We apply an average-reward reinforcement learning approach based on afterstates to the design of optimal admission control policies in mobile multimedia cellular networks where predictive information related to the occurrence of future handovers is available. We consider a type of predictor that labels active mobile terminals in the cell neighborhood a fixed amount of time before handovers are predicted to occur, which we call the anticipation time. The admission controller exploits this information to reserve resources efficiently. We show that there exists an optimum value for the anticipation time at which the highest performance gain is obtained. Although the optimum anticipation time depends on system parameters, we find that its value changes very little when the system parameters vary within a reasonable range. We also find that, in terms of system performance, deploying prediction is always advantageous when compared to a system without prediction, even when the system parameters are estimated with poor precision. © Springer Science+Business Media, LLC 2012.The authors would like to thank the reviewers for their valuable comments that helped to improve the quality of the paper. This work has been supported by the Spanish Ministry of Education and Science and European Comission (30% PGE, 70% FEDER) under projects TIN2008-06739-C04-02 and TIN2010-21378-C02-02 and by Comunidad de Madrid through project S-2009/TIC-1468.Martínez Bauset, J.; Giménez Guzmán, JM.; Pla, V. (2012). Robustness of optimal channel reservation using handover prediction in multiservice wireless networks. 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EVEREST IST - 2002 - 00185 : D23 : final report

Deliverable públic del projecte europeu EVERESTThis deliverable constitutes the final report of the project IST-2002-001858 EVEREST. After its successful completion, the project presents this document that firstly summarizes the context, goal and the approach objective of the project. Then it presents a concise summary of the major goals and results, as well as highlights the most valuable lessons derived form the project work. A list of deliverables and publications is included in the annex.Postprint (published version

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

4. generációs mobil rendszerek kutatása = Research on 4-th Generation Mobile Systems

A 3G mobil rendszerek szabványosítása a végéhez közeledik, legalábbis a meghatározó képességek tekintetében. Ezért létfontosságú azon technikák, eljárások vizsgálata, melyek a következő, 4G rendszerekben meghatározó szerepet töltenek majd be. Több ilyen kutatási irányvonal is létezik, ezek közül projektünkben a fontosabbakra koncentráltunk. A következőben felsoroljuk a kutatott területeket, és röviden összegezzük az elért eredményeket. Szórt spektrumú rendszerek Kifejlesztettünk egy új, rádiós interfészen alkalmazható hívásengedélyezési eljárást. Szimulációs vizsgálatokkal támasztottuk alá a megoldás hatékonyságát. A projektben kutatóként résztvevő Jeney Gábor sikeresen megvédte Ph.D. disszertációját neurális hálózatokra épülő többfelhasználós detekciós technikák témában. Az elért eredmények Imre Sándor MTA doktori disszertációjába is beépültek. IP alkalmazása mobil rendszerekben Továbbfejlesztettük, teszteltük és általánosítottuk a projekt keretében megalkotott új, gyűrű alapú topológiára épülő, a jelenleginél nagyobb megbízhatóságú IP alapú hozzáférési koncepciót. A témakörben Szalay Máté Ph.D. disszertációja már a nyilvános védésig jutott. Kvantum-informatikai módszerek alkalmazása 3G/4G detekcióra Új, kvantum-informatikai elvekre épülő többfelhasználós detekciós eljárást dolgoztunk ki. Ehhez új kvantum alapú algoritmusokat is kifejlesztettünk. Az eredményeket nemzetközi folyóiratok mellett egy saját könyvben is publikáltuk. | The project consists of three main research directions. Spread spectrum systems: we developed a new call admission control method for 3G air interfaces. Project member Gabor Jeney obtained the Ph.D. degree and project leader Sandor Imre submitted his DSc theses from this area. Application of IP in mobile systems: A ring-based reliable IP mobility mobile access concept and corresponding protocols have been developed. Project member Máté Szalay submitted his Ph.D. theses from this field. Quantum computing based solutions in 3G/4G detection: Quantum computing based multiuser detection algorithm was developed. Based on the results on this field a book was published at Wiley entitled: 'Quantum Computing and Communications - an engineering approach'

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications