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A constrained MDP-based vertical handoff decision algorithm for 4G heterogeneous wireless networks
abstract: The 4th generation wireless communication systems aim to provide users with the convenience of seamless roaming among heterogeneous wireless access networks. To achieve this goal, the support of vertical handoff is important in mobility management. This paper focuses on the vertical handoff decision algorithm, which determines the criteria under which vertical handoff should be performed. The problem is formulated as a constrained Markov decision process. The objective is to maximize the expected total reward of a connection subject to the expected total access cost constraint. In our model, a benefit function is used to assess the quality of the connection, and a penalty function is used to model the signaling incurred and call dropping. The user%27s velocity and location information are also considered when making handoff decisions. The policy iteration and Q-learning algorithms are employed to determine the optimal policy. Structural results on the optimal vertical handoff policy are derived by using the concept of supermodularity. We show that the optimal policy is a threshold policy in bandwidth, delay, and velocity. Numerical results show that our proposed vertical handoff decision algorithm outperforms other decision schemes in a wide range of conditions such as variations on connection duration, user%27s velocity, user%27s budget, traffic type, signaling cost, and monetary access cost. © Springer Science%2bBusiness Media, LLC 2011.
e iscopus: 2-s2.0-79956066392
related by: authorship_16064
has funding vehicle: Natural Sciences and Engineering Research Council of Canada, NSERC
origen: scopus
estado: published
type: Generically Dependent Continuant
doi: 10.1007/s11276-011-0335-x
abstract: The 4th generation wireless communication systems aim to provide users with the convenience of seamless roaming among heterogeneous wireless access networks. To achieve this goal, the support of vertical handoff is important in mobility management. This paper focuses on the vertical handoff decision algorithm, which determines the criteria under which vertical handoff should be performed. The problem is formulated as a constrained Markov decision process. The objective is to maximize the expected total reward of a connection subject to the expected total access cost constraint. In our model, a benefit function is used to assess the quality of the connection, and a penalty function is used to model the signaling incurred and call dropping. The user%27s velocity and location information are also considered when making handoff decisions. The policy iteration and Q-learning algorithms are employed to determine the optimal policy. Structural results on the optimal vertical handoff policy are derived by using the concept of supermodularity. We show that the optimal policy is a threshold policy in bandwidth, delay, and velocity. Numerical results show that our proposed vertical handoff decision algorithm outperforms other decision schemes in a wide range of conditions such as variations on connection duration, user%27s velocity, user%27s budget, traffic type, signaling cost, and monetary access cost. © Springer Science Business Media, LLC 2011.
volume: 17
abstract: The 4th generation wireless communication systems aim to provide users with the convenience of seamless roaming among heterogeneous wireless access networks. To achieve this goal, the support of vertical handoff is important in mobility management. This paper focuses on the vertical handoff decision algorithm, which determines the criteria under which vertical handoff should be performed. The problem is formulated as a constrained Markov decision process. The objective is to maximize the expected total reward of a connection subject to the expected total access cost constraint. In our model, a benefit function is used to assess the quality of the connection, and a penalty function is used to model the signaling incurred and call dropping. The user's velocity and location information are also considered when making handoff decisions. The policy iteration and Q-learning algorithms are employed to determine the optimal policy. Structural results on the optimal vertical handoff policy are derived by using the concept of supermodularity. We show that the optimal policy is a threshold policy in bandwidth, delay, and velocity. Numerical results show that our proposed vertical handoff decision algorithm outperforms other decision schemes in a wide range of conditions such as variations on connection duration, user's velocity, user's budget, traffic type, signaling cost, and monetary access cost. © Springer Science%2bBusiness Media, LLC 2011.
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has publication venue: Wireless Networks
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issue: 4
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crisid: 2732
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page end: 1081
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page start: 1063
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freetext keyword: Constrained Markov decision processes; Heterogeneous wireless networks; Vertical handoff Access cost; Benefit functions; Call dropping; Constrained Markov decision process; Handoff decision; Heterogeneous wireless access networks; Heterogeneous wireless network; Location information; Mobility management; Numerical results; Optimal policies; Penalty function; Policy iteration; Q-learning algorithms; Seamless Roaming; Signaling costs; Supermodularity; Threshold policies; Vertical handoff; Vertical handoff decision algorithm; Wireless communication system; Communication systems; Global system for mobile communications; Learning algorithms; Markov processes; Signaling; Structural optimization; Wireless telecommunication systems; Wireless networks
has funding vehicle: Bell Canada Enterprises, BCE
related by: authorship_16063

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RDF description of A constrained MDP-based vertical handoff decision algorithm for 4G heterogeneous wireless networks - http://orbis.uaslp.mx/vivo/individual/scopus2731
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date: 2026-08-26T15:58:12
publisher: vivo
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Wireless Networks
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publication venue for: A constrained MDP-based vertical handoff decision algorithm for 4G heterogeneous wireless networks
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Bell Canada Enterprises, BCE
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funding vehicle for: A constrained MDP-based vertical handoff decision algorithm for 4G heterogeneous wireless networks

Natural Sciences and Engineering Research Council of Canada, NSERC
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funding vehicle for: A constrained MDP-based vertical handoff decision algorithm for 4G heterogeneous wireless networks