Handoff Failure Analysis of Adaptive Keep-Alive Interval (AKI) in 3GPP Generic Access Network (GAN)

Chen, Kai‐Hsiu; Chen, Jyh-Cheng

doi:10.1109/twc.2011.100611.102191

Cited by 4 publications

(6 citation statements)

References 17 publications

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“…In this section, we develop a framework to analyze the performance of traffic offloading algorithms for IFOM. Following a common practice used in communication network modeling [20]- [22], the arrivals of IP flows to both E-UTRAN and WLAN are assumed to be Poisson processes. We denote λ m , λ e , and λ w as the arrival rate for RR IP flow, NRR IP flows to the E-UTRAN, and NRR IP flows to the WLAN, respectively.…”

Section: Performance Analysismentioning

confidence: 99%

“…Finally, based on (19), (20), (18), (25), µ w = µ + η w , and µ e = µ + η e , (2) can be rewritten as: Consider the M/M/C/C system with arrival rate λ, service rate µ and resource capacity C resource units, respectively. From [25], the resource utilization can be derived as:…”

Section: A Arrival Rates and Service Ratesmentioning

confidence: 99%

“…Applying (20) and (18) into (31), we obtain: For the calculation of offloading overhead shown in 7and (8), all the necessary parameters have been derived above. Thus, by keeping µ w = µ + η w and µ e = µ + η e in mind and inserting (18) into 7, the offloading overhead for PO is shown as following:…”

Section: A Arrival Rates and Service Ratesmentioning

confidence: 99%

“…When an IP flow is re-directed to the E-UTRAN under PPO, it also causes additional signaling overhead. Applying µ w = µ + η w , µ e = µ + η e and inserting (19), (20), and (18) into (8), the offloading overhead for PPO is obtained as:…”

Section: A Arrival Rates and Service Ratesmentioning

confidence: 99%

“…tr = p P P O bw λ w − p P P O bh λ w = (p P P O bw − p P P O bh )λ w . (21)From(19) and(20), (21) is rewritten as:λ tr = (p…”

mentioning

confidence: 99%

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Proportional and Preemption-Enabled Traffic Offloading for IP Flow Mobility: Algorithms and Performance Evaluation

Ren

Tung²,

Chen

et al. 2018

IEEE Trans. Veh. Technol.

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IP Flow Mobility (IFOM) enables a user equipment to offload data traffic at the IP flow level. Although the procedure of IFOM-based flow offloading has been specified by 3GPP, how many IP flows should be offloaded and when offloading should be performed are not defined. Consequently, IP flows may be routed to a target access network which has a strong signal strength but with backhaul congestion or insufficient access capability. In this paper, we propose two algorithms, referred to as proportional offloading (PO), and proportional and preemption-enabled offloading (PPO), respectively, for IP flow offloading in hybrid cellular and wireless local area networks. The PO algorithm decides an optimal proportion of IP flows which could be offloaded by considering available resources at the target access network. In the PPO algorithm, both service continuity and network utilization are taken into consideration. Furthermore, a detailed analytical model is developed in order to evaluate the behavior of the proposed algorithms. The analytical model is validated through extensive simulations. The results show that by dynamically adjusting the percentage of traffic flows to be offloaded, PO can reduce blocking probability and increase resource utilization. PPO further improves the performance at the cost of slightly higher offloading overhead.

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Section: Performance Analysismentioning

confidence: 99%

Section: A Arrival Rates and Service Ratesmentioning

confidence: 99%

Section: A Arrival Rates and Service Ratesmentioning

confidence: 99%

Section: A Arrival Rates and Service Ratesmentioning

confidence: 99%

“…tr = p P P O bw λ w − p P P O bh λ w = (p P P O bw − p P P O bh )λ w . (21)From(19) and(20), (21) is rewritten as:λ tr = (p…”

mentioning

confidence: 99%

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Proportional and Preemption-Enabled Traffic Offloading for IP Flow Mobility: Algorithms and Performance Evaluation

Ren

Tung²,

Chen

et al. 2018

IEEE Trans. Veh. Technol.

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Challenges of the always-best-connected enablers for user equipment in Evolved Packet System

Kellokoski

2012

2012 IV International Congress on Ultra Modern Telecommunications and Control Systems

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Impacts of S1 and X2 Interfaces on eMBMS Handover Failure: Solution and Performance Analysis

Ren

Chen

Chin

2018

IEEE Trans. Veh. Technol.

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In evolved Multimedia Broadcast/Multicast Service (eMBMS), service continuity enables users move from one cell to another without interrupting eMBMS service. Unlike traditional handover in unicast transmission, a UE can receive eMBMS service in either unicast or multicast mode. In this paper, we point out a new handover failure problem in eMBMS due to the miss of rekeying information. We first take a close look at the new handover scenarios. We then investigate the problem by using comprehensive mathematical models. Our models provide insights on the new handover problem and introduce theoretical guidelines for mobile operators to design and optimize their networks without wide deployment to save cost and time. Moreover, we propose a solution to combat against the handover failure. Both the simulation and analytical results demonstrate that the impacts of the eMBMS handover failure are reduced significantly. In this paper, we present a systematic way to investigate the handover failure problem in eMBMS.

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Handoff Failure Analysis of Adaptive Keep-Alive Interval (AKI) in 3GPP Generic Access Network (GAN)

Cited by 4 publications

References 17 publications

Proportional and Preemption-Enabled Traffic Offloading for IP Flow Mobility: Algorithms and Performance Evaluation

Proportional and Preemption-Enabled Traffic Offloading for IP Flow Mobility: Algorithms and Performance Evaluation

Challenges of the always-best-connected enablers for user equipment in Evolved Packet System

Impacts of S1 and X2 Interfaces on eMBMS Handover Failure: Solution and Performance Analysis

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