Single or Multiple Frames Content Delivery for Next-Generation Networks?

TL;DR

This paper proposes a unified framework for energy-efficient resource allocation in heterogeneous networks, considering multiple advanced technologies and two content delivery scenarios, with solutions for complex optimization problems.

Contribution

It introduces two novel content delivery scenarios and formulates joint resource allocation problems considering multiple technologies in a unified framework.

Findings

The proposed algorithms improve energy efficiency in heterogeneous networks.

The joint consideration of multiple technologies enhances resource utilization.

The iterative algorithms effectively solve complex optimization problems.

Abstract

This paper addresses the four enabling technologies, namely multi-user sparse code multiple access (SCMA), content caching, energy harvesting, and physical layer security for proposing an energy and spectral efficient resource allocation algorithm for the access and backhaul links in heterogeneous cellular networks. Although each of the above mentioned issues could be a topic of research, in a real situation, we would face a complicated scenario where they should be considered jointly, and hence, our target is to consider these technologies jointly in a unified framework. Moreover, we propose two novel content delivery scenarios: 1) single frame content delivery (SFCD), and 2) multiple frames content delivery (MFCD), where the time duration of serving user requests is divided into several frames. In the first scenario, the requested content by each user is served over one frame. However, in the second scenario, the requested content by each user can be delivered over several frames. We formulate the resource allocation for the proposed scenarios as optimization problems where our main aim is to maximize the energy efficiency of access links subject to the transmit power and rate constraints of access and backhaul links, caching and energy harvesting constraints, and SCMA codebook allocation limitations. Due to the practical limitations, we assume that the channel state information values between eavesdroppers and base stations are uncertain and design the network for the worst case scenario. Since the corresponding optimization problems are mixed integer non-linear and nonconvex programming, NP-hard, and intractable, we propose an iterative algorithm based on the well-known alternate and successive convex approximation methods.