Caching Placement and Resource Allocation for Cache-Enabling UAV NOMA Networks

08/12/2020
by   Tiankui Zhang, et al.
0

This article investigates the cache-enabling unmanned aerial vehicle (UAV) cellular networks with massive access capability supported by non-orthogonal multiple access (NOMA). The delivery of a large volume of multimedia contents for ground users is assisted by a mobile UAV base station, which caches some popular contents for wireless backhaul link traffic offloading. In cache-enabling UAV NOMA networks, the caching placement of content caching phase and radio resource allocation of content delivery phase are crucial for network performance. To cope with the dynamic UAV locations and content requests in practical scenarios, we formulate the long-term caching placement and resource allocation optimization problem for content delivery delay minimization as a Markov decision process (MDP). The UAV acts as an agent to take actions for caching placement and resource allocation, which includes the user scheduling of content requests and the power allocation of NOMA users. In order to tackle the MDP, we propose a Q-learning based caching placement and resource allocation algorithm, where the UAV learns and selects action with soft ε-greedy strategy to search for the optimal match between actions and states. Since the action-state table size of Q-learning grows with the number of states in the dynamic networks, we propose a function approximation based algorithm with combination of stochastic gradient descent and deep neural networks, which is suitable for large-scale networks. Finally, the numerical results show that the proposed algorithms provide considerable performance compared to benchmark algorithms, and obtain a trade-off between network performance and calculation complexity.

READ FULL TEXT

page 4

page 5

page 6

page 7

page 8

page 9

page 12

page 13

research
07/22/2020

Cache-enabling UAV Communications: Network Deployment and Resource Allocation

In this article, we investigate the content distribution in the hotspot ...
research
02/15/2022

Efficient Content Delivery in Cache-Enabled VEN with Deadline-Constrained Heterogeneous Demands: A User-Centric Approach

Modern connected vehicles (CVs) frequently require diverse types of cont...
research
09/21/2023

Latency-Aware Radio Resource Optimization in Learning-Based Cloud-Aided Small Cell Wireless Networks

Low latency communication is one of the fundamental requirements for 5G ...
research
01/03/2018

Joint Content Delivery and Caching Placement via Dynamic Programming

In this paper, downlink delivery of popular content is optimized with th...
research
06/08/2021

AdaptSky: A DRL Based Resource Allocation Framework in NOMA-UAV Networks

Unmanned aerial vehicle (UAV) has recently attracted a lot of attention ...
research
06/09/2021

Satellite- and Cache-assisted UAV: A Joint Cache Placement, Resource Allocation, and Trajectory Optimization for 6G Aerial Networks

This paper considers LEO satellite- and cache-assisted UAV communication...
research
04/20/2022

Placement and Resource Allocation of Wireless-Powered Multiantenna UAV for Energy-Efficient Multiuser NOMA

This paper investigates a new downlink nonorthogonal multiple access (NO...

Please sign up or login with your details

Forgot password? Click here to reset