A First Look at Commercial 5G Performance on Smartphones

We conduct to our knowledge a first measurement study of commercial 5G performance on smartphones by closely examining 5G networks of three carriers (two mmWave carriers, one mid-band carrier) in three U.S. cities. We conduct extensive field tests on 5G performance in diverse urban environments. We systematically analyze the handoff mechanisms in 5G and their impact on network performance. We explore the feasibility of using location and possibly other environmental information to predict the network performance. We also study the app performance (web browsing and HTTP download) over 5G. Our study consumes more than 15 TB of cellular data. Conducted when 5G just made its debut, it provides a "baseline" for studying how 5G performance evolves, and identifies key research directions on improving 5G users' experience in a cross-layer manner. We have released the data collected from our study (referred to as 5Gophers) at https://fivegophers.umn.edu/www20.Comment: Published at The Web Conference 2020 (WWW 2020). Please include WWW in any citation

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin

Urban wireless traffic evolution: the role of new devices and the effect of policy

The emergence of new wireless technologies, such as the Internet of Things, allows digitalizing new and diverse urban activities. Thus, wireless traffic grows in volume and complexity, making prediction, investment planning, and regulation increasingly difficult. This article characterizes urban wireless traffic evolution, supporting operators to drive mobile network evolution and policymakers to increase national and local competitiveness. We propose a holistic method that widens previous research scope, including new devices and the effect of policy from multiple government levels. We provide an analytical formulation that combines existing complementary methods on traffic evolution research and diverse data sources. Results for a centric area of Helsinki during 2020-2030 indicate that daily volumes increase, albeit a surprisingly large part of the traffic continues to be generated by smartphones. Machine traffic gains importance, driven by surveillance video cameras and connected cars. While camera traffic is sensitive to law enforcement policies and data regulation, car traffic is less affected by transport electrification policy. High-priority traffic remains small, even under encouraging autonomous vehicle policies. We suggest that 5G small cells might be needed around 2025, albeit the utilization of novel radio technology and additional mid-band spectrum could delay this need until 2029. We argue that mobile network operators inevitably need to cooperate in constructing a single, shared small cell network to mitigate the high deployment costs of massively deploying small cells. We also provide guidance to local and national policymakers for IoT-enabled competitive gains via the mitigation of five bottlenecks. For example, local monopolies for mmWave connectivity should be facilitated on space-limited urban furniture or risk an eventual capacity crunch, slowing down digitalization

5G and beyond networks

This chapter investigates the Network Layer aspects that will characterize the merger of the cellular paradigm and the IoT architectures, in the context of the evolution towards 5G-and-beyond, including some promising emerging services as Unmanned Aerial Vehicles or Base Stations, and V2X communications

A case study on latency, bandwidth and energy efficiency of mobile 5G and YouTube Edge service in London. Why the 5G ecosystem and energy efficiency matter?

The advancements in 5G mobile networks and Edge computing offer great potential for services like augmented reality and Cloud gaming, thanks to their low latency and high bandwidth capabilities. However, the practical limitations of achieving optimal latency on real applications remain uncertain. This paper aims to investigate the actual latency and bandwidth provided by 5G Networks and YouTube Edge service in London, UK. We analyze how latency and bandwidth differ between 4G LTE and 5G networks and how the location of YouTube Edge servers impacts these metrics. Our research reveals over 10 significant observations and implications, indicating that the primary constraints on 4G LTE and 5G capabilities are the ecosystem and energy efficiency of mobile devices down-streaming data. Our study demonstrates that to fully unlock the potential of 5G and it's applications, it is crucial to prioritize efforts aimed at improving the ecosystem and enhancing the energy efficiency

Practical Commercial 5G Standalone (SA) Uplink Throughput Prediction

While the 5G New Radio (NR) network promises a huge uplift of the uplink throughput, the improvement can only be seen when the User Equipment (UE) is connected to the high-frequency millimeter wave (mmWave) band. With the rise of uplink-intensive smartphone applications such as the real-time transmission of UHD 4K/8K videos, and Virtual Reality (VR)/Augmented Reality (AR) contents, uplink throughput prediction plays a huge role in maximizing the users' quality of experience (QoE). In this paper, we propose using a ConvLSTM-based neural network to predict the future uplink throughput based on past uplink throughput and RF parameters. The network is trained using the data from real-world drive tests on commercial 5G SA networks while riding commuter trains, which accounted for various frequency bands, handover, and blind spots. To make sure our model can be practically implemented, we then limited our model to only use the information available via Android API, then evaluate our model using the data from both commuter trains and other methods of transportation. The results show that our model reaches an average prediction accuracy of 98.9\% with an average RMSE of 1.80 Mbps across all unseen evaluation scenarios