Optimal placement of colocated and non-colocated LWA nodes in dense deployments

Pasca, S Thomas Valerrian; Srivats, R Adharsh; Franklin, A. Antony; Tamma, Bheemarjuna Reddy

doi:10.1109/ants.2017.8384088

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…In a separate study, [11] addressed the challenge of colocated and non-colocated node placement in Long Term Evolution (LTE)-WiFi aggregation networks. They formulated this problem as a Mixed Integer Nonlinear Programming (MINLP) problem.…”

Section: B Placement In Wifi and Heterogeneous Rf Networkmentioning

confidence: 99%

PlaciFi: Orchestrating Optimal 3D Access Point Placement for LiFi-WiFi Heterogeneous Networks

Vijayaraghavan,

Von Mankowski,

Mas-Machuca

et al. 2023

IEEE Access

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Section: B Placement In Wifi and Heterogeneous Rf Networkmentioning

confidence: 99%

PlaciFi: Orchestrating Optimal 3D Access Point Placement for LiFi-WiFi Heterogeneous Networks

Vijayaraghavan,

Von Mankowski,

Mas-Machuca

et al. 2023

IEEE Access

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“…A number of UEs are uniformly distributed in the hotspot area. Moreover, the indoor WLAN path loss model is represented as follows [32] P W Loss = 20 log 10 f w (MHz)+η w log 10 d + P f (n w )−28 (24) where f w represents the WLAN transmission frequency; d is the distance in meters between WAP and UE; η w is the distance power loss coefficient and assumed to be 30; P f (n w ) denotes the penetration loss factor and is equal to P f (n w ) = n w + 13; n w is the number of walls and assumed to be 3. While the indoor Path loss model for LTE Femto SBS is expressed as follows [33]…”

Section: Performance Evaluationmentioning

confidence: 99%

User Association With Mode Selection in LWA-Based Multi-RAT HetNet

2019

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Restrained by the long term evolution (LTE) limited network capacity, WiFi technology is considered as one of the promising solutions to leverage the traffic load and enhance the LTE capacity. Exploiting both the licensed and unlicensed spectrum was the motivated key to standardize the LTE-wireless local area network (WLAN) aggregation (LWA) technology by 3GPP in Release 13. In this paper, we consider the user association problem in LWA-based Multiple Radio Access Technologies (Multi-RAT) Heterogeneous Networks (HetNet) in which three transmission modes are available (LTE, WiFi, and aggregation mode) and the user needs to select not only the wireless node that will associate with it, but also the used transmission mode. For this, a new user association algorithm that considers the joint node and mode selection is proposed in this paper. This association process is formulated as an optimization problem with the aim to maximize total network throughput. To solve this problem, a one-to-many matching game-based association algorithm is designed, where each user is matched to the best transmission mode/node according to well-developed utility function that considers the achieved data rate of each user as well as the proportional fairness among users. Simulation results have shown that our proposed algorithm outperforms comparable association techniques such as WLAN first, LTE first, and LTE-W in terms of system throughput, outage probability and fairness between users.

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Joint Q-Learning Based Resource Allocation and Multi-Numerology B5G Network Slicing Exploiting LWA Technology

Elmosilhy,

Elmesalawy,

Ibrahim

et al. 2024

IEEE Access

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The emergence of the sixth generation (6G) era has highlighted the importance of Network Slicing (NS) technology as a promising solution for catering the diverse service requests of users . With the presence of a large number of devices with different service requests and since each service has different goal and requirements; efficiently allocating Resource Blocks (RBs) to each network slice is a challenging task in order to meet the desired Quality of Service (QoS) standards. However, it is worth noting that the majority of research efforts have primarily concentrated on cellular technologies, leaving behind the potential benefits of utilizing unlicensed bands to alleviate traffic congestion and enhance the capacity of existing LTE networks. In this paper we propose a novel idea by exploiting LTE-WLAN Aggregation technology (LWA) in Multi-Radio Access Technology (RAT) Heterogeneous Networks (HetNet), aiming to solve radio resource allocation problem based on the Radio Access Network (RAN) slicing and 5G New Radio (NR) scalable numerology technique. A joint optimization problem is proposed by jointly finding an efficient resource allocation ratio for each slice in each Base Station (BS) and by finding the optimum value of scalable numerology with the objective of maximizing users' satisfaction. In order to solve this problem, a novel three-stage framework is proposed which is based on channel state information as a pre-association stage, Reinforcement Learning (RL) algorithm as finding the optimum value of slice resource ratio and scalable numerology, and finally Regret Learning Algorithm (RLA) as users' re-association phase. Furthermore, a comprehensive performance evaluation is conducted against different base-line approaches. The simulation results show that our proposed model balance and achieve improvement in users' satisfaction by deploying the proposed Multi-RAT Het-Net architecture that leverage LWA technology.

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Optimal placement of colocated and non-colocated LWA nodes in dense deployments

Cited by 5 publications

References 8 publications

PlaciFi: Orchestrating Optimal 3D Access Point Placement for LiFi-WiFi Heterogeneous Networks

PlaciFi: Orchestrating Optimal 3D Access Point Placement for LiFi-WiFi Heterogeneous Networks

User Association With Mode Selection in LWA-Based Multi-RAT HetNet

Joint Q-Learning Based Resource Allocation and Multi-Numerology B5G Network Slicing Exploiting LWA Technology

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