1,721,303 research outputs found
Can High Altitude Platforms Make 6G Sustainable?
Full text linkThe staggering growth of mobile traffic
fostered by the spreading of 5G technology and massive
Internet of Things applications is leading to the need for
extensive Radio Access Network (RAN) densification.
However, the entailed boost in energy consumption
poses significant challenges for a sustainable transition
towards 6G. High Altitude Platform Stations (HAPSs)
equipped with aerial Base Stations (BSs) represent a
promising and flexible solution to provide additional
capacity that can be used in a flexible way to facilitate
terrestrial BSs sleep modes and, ultimately, reduce
energy consumption and make the network more sus-
tainable.
As a case study, we consider a portion of a urban RAN
to investigate the potential benefits deriving from the
integration of HAPSs in terrestrial RANs as a means to
support joint energy and resource allocation strategies
that will be needed in 6G networks. Our results show
that offloading traffic to HAPS mounted BSs allows to
reduce the grid energy demand of terrestrial still maintaining adequate Quality of Service
ReCoCo: Reinforcement learning-based Congestion control for Real-time applications
Full text linkReal-time communication (RTC) platforms have seen a considerable surge in popularity in recent years, largely due to the COVID-19 pandemic which facilitated remote work. To ensure adequate Quality of Experience (QoE) for users, a good congestion control algorithm is needed. RTC applications use UDP, so congestion control is done on the application layer, leaving way for advanced algorithms. In this paper, we propose ReCoCo, a solution for congestion control in RTC applications based on Reinforcement learning (RL). ReCoCo gains information about the network conditions at the receiver-side, such as receiving rate, one-way delay and loss ratio and predicts the available bandwidth in the next time bin. We train ReCoCo on 9 bandwidth trace files that cover a vast array of network types. We try different algorithms, states and parameters, training both specific and general models. We find that ReCoCo outperforms the de-facto standard heuristic algorithm GCC in both specialized and general models. We also make observations on the difficulty of generalization when using RL
Microgrid for Radio Access Network Resilience
Full text linkThe consistent growth in electricity demand, cou-pled with factors such as political instability, cyberattacks, and the rising frequency of natural disasters due to the climate crisis, poses challenges to the reliability and consistency of the power grid supply. The malfunctioning of the power grid, in turn, has a cascading effect on the communication infrastructure, which heavily relies on the stability of the electricity grid. Despite this, enhancing the resilience of computing and communication facil-ities is fundamental. Their crucial role in supporting essential aspects of our daily lives requires ensuring their continuous and dependable operation. To cope with this, in this work, we view a group of Base Stations (BSs) of a Radio Access Network (RAN) as consumers within a Microgrid (MG), each equipped with a Photovoltaic (PV) Panel and interconnected through dedicated power cables to exchange their generated energy. We introduce a RAN resource and energy management, that, during a Power Grid Outage (PGO), aims at keeping active the most loaded BSs, given the available generated energy within the MG. We evaluate the impact of the number of BSs in the MG, the PV Panel capacity, the duration of the PGOs and the BS traffic shape profiles, formalizing also the required setting which guarantees the efficacy of our methodology. Results reveal that the performance achieved with PV Panels not exceeding 6 kWp is comparable to that of larger PV Panels (up to 12 kWp), if the MG and the RAN resource management are implemented, making our solution feasible in terms of installation space requirements and increasing the hourly served traffic up to 300%
Performance of wideband CDMA systems supporting multimedia traffic
No full textWe evaluate the performance of wideband CDMA cellular systems providing different classes of multimedia traffic and supporting user mobility. A Markovian teletraffic model of the user dynamics is developed. Constraints are imposed in the model which account for the multiple access interference among active users. Results are shown in terms of call blocking probabilities and average number of active connections. The methodology proposed is a useful tool for the design and planning of third generation cellular systems
Performance Improvements Through Recommendations for a PLC Network with Collaborative Caching in Remote Areas
Full text linkThe emergence of Power Line Communication (PLC) technology has facilitated the expansion of broadband access networks in remote areas, by utilizing existing wired power infrastructure. However, the growing demand for data, driven by the popularity of communication services, presents a formidable challenge to the underlying PLC technology. Collaborative caching involves the sharing of cached content among neighboring nodes, thereby improving cache hit ratio (CHR), reducing network and backhaul congestion, and ultimately enhancing network performance. Our research proposes a recommendation system integrated into the collaborative caching mechanism on a PLC network that suggests relevant content to the users based on users' preferences and historical usage patterns leading to an increase in CHR and a reduction in network congestion. The results indicate that the proposed system significantly improves network performance by reducing download delay and saving precious backhaul link resources thus making PLC networks more effective for remote areas
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