Generic Adaptive Handoff Algorithms Using Fuzzy Logic and Neural Networks

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Virginia Tech

Efficient handoff algorithms cost-effectively enhance the capacity and Quality of Service (QoS) of cellular systems. This research presents novel approaches for the design of high performance handoff algorithms that exploit attractive features of several existing algorithms, provide adaptation to dynamic cellular environment, and allow systematic tradeoffs among different system characteristics. A comprehensive foundation of handoff and related issues of cellular communications is given. The tools of artificial intelligence utilized in this research, neural networks and fuzzy logic, are introduced. The scope of existing simulation models for macrocellular and microcellular handoff algorithms is enhanced by incorporating several important features. New simulation models suitable for performance evaluation of soft handoff algorithms and overlay handoff algorithms are developed. Four basic approaches for the development of high performance algorithms are proposed and are based on fuzzy logic, neural networks, unified handoff candidate selection, and pattern classification. The fuzzy logic based approach allows an organized tuning of the handoff parameters to provide a balanced tradeoff among different system characteristics. The neural network based approach suggests neural encoding of the fuzzy logic systems to simultaneously achieve the goals of high performance and reduced complexity. The unified candidacy based approach recommends the use of a unified handoff candidate selection criterion to select the best handoff candidate under given constraints. The pattern classification based approach exploits the capability of fuzzy logic and neural networks to obtain an efficient architecture of an adaptive handoff algorithm. New algorithms suitable for microcellular systems, overlay systems, and systems employing soft handoff are described. A basic adaptive algorithm suitable for a microcellular environment is proposed. Adaptation to traffic, interference, and mobility has been superimposed on the basic generic algorithm to develop another microcellular algorithm. An adaptive overlay handoff algorithm that allows a systematic balance among the design parameters of an overlay system is proposed. Important considerations for soft handoff are discussed, and adaptation mechanisms for new soft handoff algorithms are developed.

Microcells, Macrocells, Neural Networks, Fuzzy Logic, Handoff Algorithms, Overlays, Soft Handoff