Designing a dynamic spectrum sharing algorithm between DCS and LTE in the 1800 MHz band: a case study of a mobile telecommunication operator in Zimbabwe

Magwa, Luckmore

Designing a dynamic spectrum sharing algorithm between DCS and LTE in the 1800 MHz band: a case study of a mobile telecommunication operator in Zimbabwe

Thesis / Dissertation

2025

Publisher

University of Cape Town

Department

Department of Electrical Engineering

Faculty

Faculty of Engineering and the Built Environment

Abstract

In recent years, there has been remarkable growth in the wireless devices and networks market, leading to the proliferation of numerous wireless services and applications. Consequently, regulatory agencies around the world have allocated licensed spectrum chunks to different wireless services to meet the increasing demand. Despite technological advancements such as Multiple Input Multiple Output (MIMO) communications, heterogeneous networks, and cooperative communications, spectrum scarcity continues to pose a challenge for regulatory agencies worldwide. Facing this challenge, Dynamic Spectrum Sharing (DSS) has emerged as a promising remedy. As a facet of frequency spectrum management, DSS aims to bolster spectrum utilization efficiency and elevate the end-user experience by introducing greater flexibility in the usage of spectrum resources. This Dissertation has substantiated DSS as a viable solution to the challenge of spectrum scarcity. It assessed the effectiveness and suitability of dynamic spectrum sharing within a conventional mobile network setting, concentrating on intra-operator scenarios encompassing Digital Cellular System (DCS), also recognized as GSM1800, and LTE radio technologies. Monte Carlo-style system-level simulations were conducted using Atoll, utilizing raster traffic maps provided by the Mobile Network Operator (MNO). These simulations served two main purposes: firstly, to benchmark the simulator's performance with actual network performance data collected from the MNO, and secondly, to validate the impact of DSS on the network by contrasting it with the current fixed spectrum sharing method employed by the MNO in urban and suburban settings, thus offering a realistic analysis. Key Performance Indicators (KPIs) on LTE, such as Downlink Throughput, Physical Resource Block (PRB) Utilization, and Evolved Radio Access Bearer (ERAB) Establishment, were evaluated, along with consideration of the impact on 2G metrics like voice call drops, total carried traffic, and receiver (Rx) signal quality. The simulations revealed a substantial surge in LTE throughput, averaging 62% across both clusters, resulting in an overall increase in LTE traffic by 34%, thanks to DSS implementation. Remarkably, this enhancement in LTE performance was achieved while ensuring minimal adverse effects on DCS performance. Notably, DSS's impact on the DCS network was more pronounced in urban areas, leading to a 7% reduction in voice traffic attributed to heightened interference in shared spectrum zones, leading to increased SINR. As a result, there was a 6% drop in DL quality samples (DL Rq), resulting in a 0.16% increase in voice call drops post-DSS activation. In suburban regions, both DSS and Fixed Spectrum Allocation (FSA) exhibited nearly identical DCS performance, with negligible impact, as indicated by a slight 1.7% decline in received signal quality compared to the urban cluster. To further optimize DCS performance within the DSS framework, future strategies suggest reducing the transmit power of resource elements in shared spectrum zones to mitigate interference with DCS channels.