On Pre-Emption and Congestion Control for LTE Systems

Kwan, R.; Arnott, Rob; Trivisonno, Riccardo; Kubota, Mitsuhiro

doi:10.1109/vetecf.2010.5594476

Cited by 35 publications

(25 citation statements)

References 3 publications

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“…Such a priority would be important in the case of mixed traffic. See [9]. FTP session, so that the number of arriving users can be increased for a given offered load.…”

Section: Numerical Resultsmentioning

confidence: 99%

On Radio Admission Control for LTE Systems

Kwan¹,

Arnott²,

Kubota

2010

2010 IEEE 72nd Vehicular Technology Conference - Fall

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Admission control (AC) is an important feature in a wireless network by which radio resource usage is optimized whilst maintaining the Quality of Service (QoS) of existing users. In this paper, a novel admission control mechanism is proposed for the Long-Term Evolution (LTE) cellular networks. Simulation results show that the proposed AC can provide a more flexible trade-off between network and user performances compared to simpler approaches based on resource utilisation. It is also shown that a predictive approach provides a significant overall network performance gain at the expense of cell-edge blocking.

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“…Such a priority would be important in the case of mixed traffic. See [9]. FTP session, so that the number of arriving users can be increased for a given offered load.…”

Section: Numerical Resultsmentioning

confidence: 99%

On Radio Admission Control for LTE Systems

Kwan¹,

Arnott²,

Kubota

2010

2010 IEEE 72nd Vehicular Technology Conference - Fall

Self Cite

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“…(1) Blocking probability of new calls in the SG Summing up the stationary probabilities of Markovian states where s D C sgb , we have the blocking probability of new calls in the SG (i.e., BP sg /, as shown in Equation (12). (2) Blocking probability of new calls in a sector Summing up the stationary probabilities of Markovian states where x 1 D C sec C1, we have the blocking probability of new calls in Sector 1 (i.e., BP sec /, as shown in Equation (13).…”

Section: Blocking and Dropping Probabilitiesmentioning

confidence: 99%

Analytical models for call blocking and dropping in sectorized cellular networks with fractional frequency reuse

Sheu

Lin

Chou

2014

Wireless Communications

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In this paper, we construct mathematical models to analyze the probabilities of new call blocking and handoff call (HC) dropping for a sectorized cellular network with fractional frequency reuse (FFR). Because a sectorized FFR network (SFN) consists of two areas, the super group (SG) and the regular group (or sectors), three different types of HCs may happen when a mobile station (MS) moves from the SG to a sector, from a sector to the SG, or from one sector to another sector. To characterize three types of HCs, we first derive the area transition probability, which is defined as the reciprocal of MS's average residence time in an area (i.e., sector or SG). Moreover, we construct the model of Markov chains and derive the state transition rates. Then on the basis of the stationary probabilities of Markovian states, we derive the three types of blocking probabilities of new calls and two types of dropping probabilities of HCs. Finally, we conduct extensive numerical simulations. From the results of numerical simulations, we reveal two important rules for choosing the optimal radius of the SG, with which the system blocking and dropping probability can be effectively minimized. Copyright © 2014 John Wiley & Sons, Ltd.

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“…Over years researchers were focused on enhancing downlink transmission as only downlink was challenging. They improved congestion control mechanisms while taking predicted throughput as an input parameter [1], [12]. For that, downlink cellular throughput prediction has been the ultimate goal of research, as it improves many use cases, such as video streaming quality.…”

Section: Introductionmentioning

confidence: 99%

Experimental Estimation of LTE-A Performance

Oussakel

Owezarski

Berthou

2019

2019 15th International Conference on Network and Service Management (CNSM)

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In cellular networks, the emergence of machine communications such as connected vehicles increases the high demand of uplink transmissions, thus, degrading the quality of service per user equipment. Enforcing quality-of-service in such cellular network is challenging, as radio phenomena, as well as user (and their devices) mobility and dynamics, are uncontrolled. To solve this issue, estimating what the quality of transmissions will be in a short future for a connected user is essential. For that purpose, we argue that lower layer metrics are a key feature whose evolution can help predict the bandwidth that the considered connections can take advantage of in the following hundreds of milliseconds. The paper then describes how a 4G testbed has been deployed in order to investigate throughput prediction in uplink transmissions at a small time granularity of 100 ms. Based on lower layer metrics (physical and mac layers), the main supervised machine learning algorithms are used, such as Linear Regressor and Random Forest to predict the uplink received bandwidth in different radio phenomena environment. Hence, a deep investigation of the impact of radio issues on bandwidth prediction is conducted. Further, our evaluation shows that the prediction is highly accurate: at the time granularity of 100 ms, the average prediction error is in the range of 6% to 12% for all the scenarios we explored.

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On Pre-Emption and Congestion Control for LTE Systems

Cited by 35 publications

References 3 publications

On Radio Admission Control for LTE Systems

On Radio Admission Control for LTE Systems

Analytical models for call blocking and dropping in sectorized cellular networks with fractional frequency reuse

Experimental Estimation of LTE-A Performance

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