Performance analysis of frequency allocation in cellular network

Qinchu Cai; Letao Feng; Yetong Gu

doi:10.1117/12.2632013

14 April 2022 Performance analysis of frequency allocation in cellular network

Qinchu Cai, Letao Feng, Yetong Gu

Proceedings Volume 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021); 121781L (2022) https://doi.org/10.1117/12.2632013
Event: International Conference on Signal Processing and Communication Technology (SPCT 2021), 2021, Tianjin, China

Abstract

This paper mainly studies the frequency allocation for 5G+, the magic of mobile communications. The effectiveness of these methods and practicability of the algorithm are analyzed. We first introduce the structure of the model we use, which is cellular network consists of 19 cells. The model covers the following five approaches: IFR3+FFR, SWF, tx_ITL, selfoptimizing tx_ITL and FLG. In order to elaborate the difference of the 5 models in this paper, we describe the algorithms of each model we use by giving pseudo code and flowchart in the method part. The FFR algorithm uses IFR1 and IFR3 at the same time. In the cell center, we use IFR1 algorithm, while in cell edge we use IFR3. Partitioning a cell into a cell center and a cell edge. The core of the other four methods is the simultaneous water-filling algorithm, which is a smarter frequency allocation with a self-optimizing algorithm and distributed intelligence for every user to decide on which frequency should be selected. The basic principle of water-filling algorithm is based on the Shannon formula and boundary conditions. The other three methods are developed from the water-filling algorithm. By comparing the average capacity of each network, we reach the conclusion under different conditions.

Citation Download Citation

Qinchu Cai, Letao Feng, and Yetong Gu "Performance analysis of frequency allocation in cellular network", Proc. SPIE 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021), 121781L (14 April 2022); https://doi.org/10.1117/12.2632013

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KEYWORDS

Computer simulations

Algorithm development

Signal to noise ratio

Networks

Multiplexing

Systems modeling

Telecommunications

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