Adaptive Target-Condition Neural Network: DNN-Aided Load Balancing for Hybrid LiFi and WiFi Networks

08/09/2022
by   Han Ji, et al.
7

Load balancing (LB) is a challenging issue in the hybrid light fidelity (LiFi) and wireless fidelity (WiFi) networks (HLWNets), due to the nature of heterogeneous access points (APs). Machine learning has the potential to provide a complexity-friendly LB solution with near-optimal network performance, at the cost of a training process. The state-of-the-art (SOTA) learning-aided LB methods, however, need retraining when the network environment (especially the number of users) changes, significantly limiting its practicability. In this paper, a novel deep neural network (DNN) structure named adaptive target-condition neural network (A-TCNN) is proposed, which conducts AP selection for one target user upon the condition of other users. Also, an adaptive mechanism is developed to map a smaller number of users to a larger number through splitting their data rate requirements, without affecting the AP selection result for the target user. This enables the proposed method to handle different numbers of users without the need for retraining. Results show that A-TCNN achieves a network throughput very close to that of the testing dataset, with a gap less than 3 obtain a network throughput comparable to two SOTA benchmarks, while reducing the runtime by up to three orders of magnitude.

READ FULL TEXT

page 2

page 5

page 6

page 7

page 8

page 9

page 11

page 12

research
06/30/2021

Limited-Fronthaul Cell-Free Hybrid Beamforming with Distributed Deep Neural Network

Cell-free massive MIMO (CF-mMIMO) systems represent a promising approach...
research
11/05/2020

Inter-Cell Interference and Load Balancing Aware Access Point Placement in Small-Cell Networks

In this paper, we provide solutions to the access point (AP) placement p...
research
06/06/2021

A novel Deep Neural Network architecture for non-linear system identification

We present a novel Deep Neural Network (DNN) architecture for non-linear...
research
02/28/2018

C-3PO: Click-sequence-aware DeeP Neural Network (DNN)-based Pop-uPs RecOmmendation

With the emergence of mobile and wearable devices, push notification bec...
research
07/06/2021

Deep Learning Methods for Joint Optimization of Beamforming and Fronthaul Quantization in Cloud Radio Access Networks

Cooperative beamforming across access points (APs) and fronthaul quantiz...
research
04/17/2020

Channel load aware AP / Extender selection in Home WiFi networks using IEEE 802.11k/v

Next-generation Home WiFi networks have to step forward in terms of perf...
research
09/28/2020

The model reduction of the Vlasov-Poisson-Fokker-Planck system to the Poisson-Nernst-Planck system via the Deep Neural Network Approach

The model reduction of a mesoscopic kinetic dynamics to a macroscopic co...

Please sign up or login with your details

Forgot password? Click here to reset