# Joint Power Allocation and Caching Optimization in Fiber-Wireless Access Networks

## TL;DR

This paper proposes a joint power allocation and caching optimization framework for Fiber-Wireless access networks to alleviate backhaul bottlenecks and maximize throughput, using novel algorithms for power and cache management.

## Contribution

It introduces a combined optimization approach for power and caching in FiWi networks, including a new water-filling method and a dynamic programming solution for knapsack problems.

## Key findings

- Proposed algorithms outperform existing methods in throughput.
- Joint optimization effectively alleviates backhaul bottleneck.
- Simulation results validate the approach's efficiency.

## Abstract

Fiber-Wireless (FiWi) access networks have been widely deployed due to the complementary advantages of high-capacity fiber backhaul and ubiquitous wireless front end. To meet the increasing demands for bandwidth-hungry applications, access points (APs) are densely deployed and new wireless network standards have been published for higher data rates. Hence, fiber backhaul in FiWi access networks is still facing the incoming bandwidth capacity crunch. In this paper, we involve caches in FiWi access networks to cope with fiber backhaul bottleneck and enhance the network throughput. On the other hand, power consumption is an important issue in wireless access networks. As both power budget in wireless access networks and bandwidth of fiber backhaul are constrained, it is challenging to properly leverage power for caching and that for wireless transmission to achieve optimal system performance. To address this challenge, we formulate the downlink wireless access throughput maximization problem by joint consideration of power allocation and caching strategy in FiWi access networks. To solve the problem, firstly, we propose a volume adjustable backhaul-constrained water-filling method (VABWF) to derive the expression of optimal wireless transmission power allocation. Then, we reformulate the problem as a multiple-choice knapsack problem (MCKP) and propose a dynamic programming algorithm to find the optimal solution of the MCKP problem. Simulation results show that the proposed algorithm significantly outperforms existing algorithms in terms of system throughput under different FiWi access network scenarios.