Energy-efficient and interference-aware handover decision for the LTE-Advanced femtocell network

Xenakis, Dionysis; Passas, Nikos; Merakos, Lazaros; Verikoukis, Christos

doi:10.1109/icc.2013.6654902

Cited by 16 publications

(14 citation statements)

References 8 publications

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“…In [8], the authors proposed a cooperation mechanism named Ha VHO scheme, which used X2 link to exchange the cooperation messages among neighbor FBSs, to expand the coverage area of femtocells and to reduce inter-femtocell interference. In [9], the authors presented a novel hand over decision policy considering received signal strength and handover hysteresis margin (HHM), by suitably adapting the HHM in accordance with standardized LTE measurements, e.g., received signal strength (RRS), reduced the power consumption of MT, and further extended in [10]. In [11], the authors formulated a predictive association game, considering the velocity of MT and hand over frequency, to determine the optimal base station and maximize the total throughput.…”

Section: Introductionmentioning

confidence: 99%

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Joint handover decision and channel allocation for LTE-A femtocell networks

Chen

Wang

Xiang

et al. 2014

The 2014 5th International Conference on Game Theory for Networks

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Cell handover has been considered as one of the most challenging issues in LTE-A macro-femtocell networks, due to the ad hoc deployment nature of Femto Base Stations (FBSs). In this paper, our goal is to achieve seamless handover of Mobile Te rminal (MT) among different cells while improving the system throughput. First, we formulate the handover decision and channel allocation problem as a Markov Decision Problem (MDP) whose objective is to maximize the total discounted expected reward per connection over an inOilite horizon. The MDP formulation takes various system parameters into account such as MT moving velocity, MT buffer size, cell switching cost and call dropping penalty. Then, we propose an algorithm based on Q-Iearning techniques to obtain the optimal cell handover and channel allocation policy. Simulation results show that our proposed algorithm is effective, and can maximize the expected total reward and reduce the average number of handovers.Index Terms Handover decision, Markov decision process, Femtocell, Q-Iearning.

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Section: Introductionmentioning

confidence: 99%

“…V7r(S) = E{L'''l Rt(st,Jr(St)) I So = s}(10) t =O where E { . } denotes the expected discounted reward over an inCIDite time.…”

mentioning

confidence: 99%

Joint handover decision and channel allocation for LTE-A femtocell networks

Chen

Wang

Xiang

et al. 2014

The 2014 5th International Conference on Game Theory for Networks

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“…Nevertheless, the power consumption and the throughput remain constant for each RAT, thus assuming unrealistic static channel characteristics where no adaptive modulation and coding (AMC) is used. In [8], an interference-aware HO decision algorithm is proposed to reduce the energy expenditure and interference at the user side, while in [9], a macro-femto cell HO algorithm for energy efficiency is presented, where the HO decision is taken based on an innovative efficient power control estimation.…”

Section: Introductionmentioning

confidence: 99%

An energy efficient vertical handover decision algorithm

Pons

Mesοdiakaki

Gruet

et al. 2014

2014 IEEE Globecom Workshops (GC Wkshps)

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As wireless communications evolve towards heterogeneous networks, mobile terminals have been enabled to handover seamlessly from one network to another. At the same time, the continuous increase in the terminal power consumption has resulted in an ever-decreasing battery lifetime. To that end, the network selection is expected to play a key role on how to minimize the energy consumption, and thus to extend the terminal lifetime. Hitherto, terminals select the network that provides the highest received power. However, it has been proved that this solution does not provide the highest energy efficiency. Thus, this paper proposes an energy efficient vertical handover algorithm that selects the most energy efficient network that minimizes the uplink power consumption. The performance of the proposed algorithm is evaluated through extensive simulations and it is shown to achieve high energy efficiency gains compared to the conventional approach.Index Terms-Energy efficiency, vertical handover, handover decision algorithm, LTE, Wi-Fi.

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“…When the threshold value is reached, a handover procedure is triggered. Many works have focused on handover decisions [11][12][13][14][15][16]. In this paper, user measures RSRP periodically with neighbor eNodeBs.…”

Section: Handover Predictionmentioning

confidence: 99%

“…In Equation (15), because , , , , , and m are pre-defined values, we only consider , and , in the following simulations. In this paper, for maintaining high QoS for video streaming, the BL data transmission must be given precedence over the EL data.…”

Section: Pre-scheduling Mechanismmentioning

confidence: 99%

A Pre-Scheduling Mechanism in LTE Handover for Streaming Video

Lai

Tai

2016

Applied Sciences

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This paper focuses on downlink packet scheduling for streaming video in Long Term Evolution (LTE). As a hard handover is adopted in LTE and has the period of breaking connection, it may cause a low user-perceived video quality. Therefore, we propose a handover prediction mechanism and a pre-scheduling mechanism to dynamically adjust the data rates of transmissions for providing a high quality of service (QoS) for streaming video before new connection establishment. Advantages of our method in comparison to the exponential/proportional fair (EXP/PF) scheme are shown through simulation experiments.

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Energy-efficient and interference-aware handover decision for the LTE-Advanced femtocell network

Cited by 16 publications

References 8 publications

Joint handover decision and channel allocation for LTE-A femtocell networks

Joint handover decision and channel allocation for LTE-A femtocell networks

An energy efficient vertical handover decision algorithm

A Pre-Scheduling Mechanism in LTE Handover for Streaming Video

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