Interference Avoidance and Mitigation in 5G and Beyond Networks

Interference remains a critical challenge in modern wireless networks, especially as nextgeneration systems are expected to operate under increasingly dense deployments, heterogeneous spectrum usage, and adversarial conditions. This thesis investigates two complementary approaches for mitigating interference in the fifth-generation (5G) cellular networks and beyond. One which avoids interference altogether through frequency agility and the other suppresses interference through better degree of spatial separation in cell-free massive MIMO (mMIMO) topology compared to conventional cellular mMIMO architecture. Frequency agility for cellular networks is a vital technology to meet the increasing demands that will be placed on future-generation wireless systems. Motivating scenarios include spectrum sharing and protection of incumbent users, dynamic interference handling, energy-efficient network management, and resiliency to malicious users or jamming. This thesis outlines methods to achieve frequency agility within the open radio access network (O-RAN) framework to establish robust service capabilities against intentional and unintentional interference sources in 5G New Radio (NR) base stations. We describe the 5G protocols (e.g., RRC signaling) and O-RAN service models (e.g., E2SM-RC) that support our proposed methods, while identifying a number of enhancements required to achieve the desired capability. O-RAN xApps add intelligence to the RAN with seamless integration. Hence, we present a frequency agility xApp that provides E2SM control actions to the E2 node initiating swift user offloading between cells operating at different center frequencies or physical locations. Furthermore, we demonstrate a prototype implementation using an open-source software-defined O-RAN 5G testbed to characterize the capabilities and limitations of current open source software in supporting the proposed methods. The later part of the thesis focuses on interference suppression capabilities in massive MIMO setup comparing cellular and cell-free topologies. We specifically explore if the cell-free mMIMO architecture could provide a better degree of interference suppression through improved spatial separation of the received signals in the uplink (UL) owing to the antennas being distributed across the geographic area. We develop a comprehensive system-level simulation to evaluate spectral efficiency under various channel conditions, including line-of-sight (LoS) and non-line-of-sight (NLoS) propagation. We model the channel with spatial correlation on both receive-side and transmit-side to capture realistic effects of mMIMO setup. We briefly describe the combining technique employed in our setup for the UL receive signal processing to suppress interference. We model spatial correlation to highlight the performance advantages of cell-free mMIMO. Monte Carlo simulations reveal that cell-free mMIMO consistently outperforms cellular mMIMO due to improved spatial separation, reduced correlation, and favorable path loss characteristics. The analysis further examines the impact of increasing the number of users and interferers beyond the number of receive antennas, revealing key scalability trade-offs. Collectively, this thesis presents two vital contributions that could make future wireless networks coordinated, share spectrum, dense and scalable all while resilient to interference.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Engineering

Department dc:contributor.department

Electrical and Computer Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2025

Author dc:creator

• Nagampally, Rakesh Reddy

Chairs dc:contributor.committeechair

• Reed, Jeffrey H.
• Jakubisin, Daniel

Committee member dc:contributor.committeemember

• Tripathi, Nishithkumar Dhananjay

• 5G
• O-RAN
• Cellular Networks
• Cell-Free MIMO
• Spatial Correlation

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:44574

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/137783