# Performance Analysis and Optimization of Uplink Cellular Networks with Flexible Frame Structure

arXiv: https://arxiv.org/abs/2103.03342 · HTML: https://mlsanity.com/paper/2103.03342/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Mar 2021.

## Built on by (most cited first, 2 of 2)

- [Evolutionary Deep Reinforcement Learning for Dynamic Slice Management in O-RAN](https://mlsanity.com/paper/2208.14394/) (2022)
- [Joint Path planning and Power Allocation of a Cellular-Connected UAV using Apprenticeship Learning via Deep Inverse Reinforcement Learning](https://mlsanity.com/paper/2306.10071/) (2023)

## Abstract (arXiv)

Future wireless cellular networks must support both enhanced mobile broadband (eMBB) and ultra reliable low latency communication (URLLC) to manage heterogeneous data traffic for emerging wireless services. To achieve this goal, a promising technique is to enable flexible frame structure by dynamically changing the data frame's numerology according to the channel information as well as traffic quality of service requirements. However, due to nonorthogonal subcarriers, this technique can result in an interference, known as inter numerology interference (INI), thus, degrading the network performance. In this work, a novel framework is proposed to analyze the INI in the uplink cellular communications. In particular, a closed form expression is derived for the INI power in the uplink with a flexible frame structure, and a new resource allocation problem is formulated to maximize the network spectral efficiency (SE) by jointly optimizing the power allocation and numerology selection in a multi user uplink scenario. The simulation results validate the derived theoretical INI analyses and provide guidelines for power allocation and numerology selection.