Ruben Borralho

Rúben Borralho

Postgraduate Research Student

Academic and research departments

Institute for Communication Systems.

My publications


Ruben Borralho, Abdelrahim Mohamed, Atta Quddus, Pedro Vieira, Rahim Tafazolli (2021)A Survey on Coverage Enhancement in Cellular Networks: Challenges and Solutions for Future Deployments, In: IEEE Communications Surveys and Tutorials IEEE

Seamless and ubiquitous coverage are key factors for future cellular networks. Despite capacity and data rates being the main topics under discussion when envisioning the Fifth Generation (5G) and beyond of mobile communications, network coverage remains one of the major issues since coverage quality highly impacts the system performance and end-user experience. The increasing number of base stations and user terminals is anticipated to negatively impact the network coverage due to increasing interference. Furthermore, the "ubiquitous coverage" use cases, including rural and isolated areas, present a significant challenge for mobile communication technologies. This survey presents an overview of the concept of coverage, highlighting the ways it is studied, measured, and how it impacts the network performance. Additionally, an overlook of the most important key performance indicators influenced by coverage, which may affect the envisioned use cases with respect to throughput, latency, and massive connectivity, are discussed. Moreover, the main existing developments and deployments which are expected to augment the network coverage, in order to meet the requirements of the emerging systems, are presented as well as implementation challenges.

R. Borralho, D. Duarte, A. Quddus, P. Vieira (2020)Developing a LTE Localization Framework using Real Network Data towards RAN Optimization through Context Knowledge, In: Proceedings of The 23rd International Symposium on Wireless Personal Multimedia Communications (WPMC2020) Institute of Electrical and Electronics Engineers (IEEE)

The exponential growth of the network elements and data traffic exchange in the last few years elevated the need of network providers for optimized and cost-efficient solutions regarding network management and monitorization. Solutions such as drive-tests (DTs) are becoming extremely expensive with the vast extension and complexity of nowadays mobile networks. Therefore, this paper provides a solution for optimized networkcontext knowledge acquisition, towards the self-organizing networks (SONs) concept. The presented framework incorporates an entire scheme for network Traces processing and positioning, based on network measurements and fingerprinting techniques. This framework enables a series of different use cases for network management and optimization, with real-time data processing capabilities within the network Traces collection interval (15 minutes), and achieving a median positioning error of 90 m.