Enabling RAN Slicing Through Carrier Aggregation in mmWave Cellular Networks

The ever increasing number of connected devices and of new and heterogeneous mobile use cases implies that 5G cellular systems will face demanding technical challenges. For example, Ultra-Reliable Low-Latency Communication (URLLC) and enhanced Mobile Broadband (eMBB) scenarios present orthogonal Quality of Service (QoS) requirements that 5G aims to satisfy with a unified Radio Access Network (RAN) design. Network slicing and mmWave communications have been identified as possible enablers for 5G. They provide, respectively, the necessary scalability and flexibility to adapt the network to each specific use case environment, and low latency and multi-gigabit-per-second wireless links, which tap into a vast, currently unused portion of the spectrum. The optimization and integration of these technologies is still an open research challenge, which requires innovations at different layers of the protocol stack. This paper proposes to combine them in a RAN slicing framework for mmWaves, based on carrier aggregation. Notably, we introduce MilliSlice, a cross-carrier scheduling policy that exploits the diversity of the carriers and maximizes their utilization, thus simultaneously guaranteeing high throughput for the eMBB slices and low latency and high reliability for the URLLC flows.Comment: 8 pages, 8 figures. Proc. of the 18th Mediterranean Communication and Computer Networking Conference (MedComNet 2020), Arona, Italy, 202

Proprietà di equipartizione asintotica e sue applicazioni nella teoria dell'informazione

In questo elaborato vedremo uno dei risultati fondamentali nella teoria dell'informazione: la proprietà di equipartizione asintotica. Grazie a questo risultato vedremo come realizzare un sistema di compressione dati senza perdita di informazione. Sarà inoltre possibile dimostrare il teorema sulla codifica di canale, che permette di identificare esattamente quanta informazione è possibile trasferire attraverso un particolare canale affetto da rumore senza avere perditaope

Minimizing Energy Consumption for 5G NR Beam Management for RedCap Devices

In 5G New Radio (NR), beam management entails periodic and continuous transmission and reception of control signals in the form of synchronization signal blocks (SSBs), used to perform initial access and/or channel estimation. However, this procedure demands continuous energy consumption, which is particularly challenging to handle for low-cost, low-complexity, and battery-constrained devices, such as RedCap devices to support mid-market Internet of Things (IoT) use cases. In this context, this work aims at reducing the energy consumption during beam management for RedCap devices, while ensuring that the desired Quality of Service (QoS) requirements are met. To do so, we formalize an optimization problem in an Indoor Factory (InF) scenario to select the best beam management parameters, including the beam update periodicity and the beamwidth, to minimize energy consumption based on users' distribution and their speed. The analysis yields the regions of feasibility, i.e., the upper limit(s) on the beam management parameters for RedCap devices, that we use to provide design guidelines accordingly

Post-Operative Functional Outcomes in Early Age Onset Rectal Cancer

Background: Impairment of bowel, urogenital and fertility-related function in patients treated for rectal cancer is common. While the rate of rectal cancer in the young (<50 years) is rising, there is little data on functional outcomes in this group. Methods: The REACCT international collaborative database was reviewed and data on eligible patients analysed. Inclusion criteria comprised patients with a histologically confirmed rectal cancer, <50 years of age at time of diagnosis and with documented follow-up including functional outcomes. Results: A total of 1428 (n=1428) patients met the eligibility criteria and were included in the final analysis. Metastatic disease was present at diagnosis in 13%. Of these, 40% received neoadjuvant therapy and 50% adjuvant chemotherapy. The incidence of post-operative major morbidity was 10%. A defunctioning stoma was placed for 621 patients (43%); 534 of these proceeded to elective restoration of bowel continuity. The median follow-up time was 42 months. Of this cohort, a total of 415 (29%) reported persistent impairment of functional outcomes, the most frequent of which was bowel dysfunction (16%), followed by bladder dysfunction (7%), sexual dysfunction (4.5%) and infertility (1%). Conclusion: A substantial proportion of patients with early-onset rectal cancer who undergo surgery report persistent impairment of functional status. Patients should be involved in the discussion regarding their treatment options and potential impact on quality of life. Functional outcomes should be routinely recorded as part of follow up alongside oncological parameters

Proprietà di equipartizione asintotica e sue applicazioni nella teoria dell'informazione

In questo elaborato vedremo uno dei risultati fondamentali nella teoria dell'informazione: la proprietà di equipartizione asintotica. Grazie a questo risultato vedremo come realizzare un sistema di compressione dati senza perdita di informazione. Sarà inoltre possibile dimostrare il teorema sulla codifica di canale, che permette di identificare esattamente quanta informazione è possibile trasferire attraverso un particolare canale affetto da rumore senza avere perdit

A second order continuous time Delta Sigma modulator for ultra low power applications

In this work the analysis and design of a continuous time 2nd order ∆Σ modulator for ultra low power applications is presented. a loop filter using only one amplifier is used, and the compensation of the amplifier is made such not to waste current in charging extra capacitance. Also a successive approximation register is used as the internal quantizer hence making the whole architecture designed for low power application

Enabling RAN Slicing Through Carrier Aggregation in mmWave Cellular Networks

The ever increasing number of connected devices and of new and heterogeneous mobile use cases implies that 5G cellular systems will face demanding technical challenges. For example, Ultra-Reliable Low-Latency Communication (URLLC) and enhanced Mobile Broadband (eMBB) scenarios present orthogonal Quality of Service (QoS) requirements that 5G aims to satisfy with a unified Radio Access Network (RAN) design. Network slicing and mmWave communications have been identified as possible enablers for 5G. They provide, respectively, the necessary scalability and flexibility to adapt the network to each specific use case environment, and low latency and multi-gigabit-per-second wireless links, which tap into a vast, currently unused portion of the spectrum. The optimization and integration of these technologies is still an open research challenge, which requires innovations at different layers of the protocol stack. This paper proposes to combine them in a RAN slicing framework for mmWaves, based on carrier aggregation. Notably, we introduce MilliSlice, a cross-carrier scheduling policy that exploits the diversity of the carriers and maximizes their utilization, thus simultaneously guaranteeing high throughput for the eMBB slices and low latency and high reliability for the URLLC flows

Safehaul: Risk-Averse Learning for Reliable mmWave Self-Backhauling in 6G Networks

Wireless backhauling at millimeter-wave frequencies (mmWave) in static scenarios is a well-established practice in cellular networks. However, highly directional and adaptive beamforming in today’s mmWave systems have opened new possibilities for self-backhauling. Tapping into this potential, 3GPP has standardized Integrated Access and Backhaul (IAB) allowing the same base station to serve both access and backhaul traffic. Although much more cost-effective and flexible, resource allocation and path selection in IAB mmWave networks is a formidable task. To date, prior works have addressed this challenge through a plethora of classic optimization and learning methods, generally optimizing a Key Performance Indicator (KPI) such as throughput, latency, and fairness, and little attention has been paid to the reliability of the KPI. We propose Safehaul, a risk-averse learning-based solution for IAB mmWave networks. In addition to optimizing average performance, Safehaul ensures reliability by minimizing the losses in the tail of the performance distribution. We develop a novel simulator and show via extensive simulations that Safehaul not only reduces the latency by up to 43.2% compared to the benchmarks, but also exhibits significantly more reliable performance, e.g., 71.4% less variance in achieved latency

Downlink TDMA Scheduling for IRS-aided Communications with Block-Static Constraints

Intelligent reflecting surfaces (IRSs) are being studied as possible low-cost energy-efficient alternatives to active relays, with the goal of improving coverage in millimeter wave (mmWave) and terahertz (THz) network deployments. In the literature, these surfaces are often studied by idealizing their characteristics: notably, it is often assumed that IRSs can tune with arbitrary frequency the phase-shifts induced by their elements, thanks to a wire-like control channel to the next generation node base (gNB). Instead, in this work we investigate an IRS-aided time division multiple access (TDMA) cellular network, where the reconfiguration of the IRS entails an energy or communication cost, and we aim at limiting the number of reconfigurations over time. We propose a clustering-based heuristic scheduling, which optimizes the cell sum-rate subject to a given number of reconfigurations within the TDMA frame. To this end, we first cluster user equipments (UEs) with a similar optimal IRS configuration, determined through a novel beamforming and IRS iterative optimization algorithm. Then, we obtain a single IRS configuration for each cluster of UEs. Numerical results show that our approach is effective in supporting IRSs-aided systems with practical constraints, achieving up to 85% of the sum-rate obtained by an ideal deployment, while reducing by 50% the number of IRS reconfigurations

End-to-End Simulation of 5G Networks Assisted by IRS and AF Relays

The high propagation and penetration loss experienced at millimeter wave (mmWave) frequencies requires ultra-dense deployments of 5th generation (5G) base stations, which may be infeasible and costly for network operators. Integrated Access and Backhaul (IAB) has been proposed to partially address this issue, though raising concerns in terms of power consumption and scalability. Recently, the research community has been investigating Intelligent Reflective Surfaces (IRSs) and Amplify-and-Forward (AF) relays as more energy-efficient alternatives to solve coverage issues in 5G scenarios. Along these lines, this paper relies on a new simulation framework, based on ns-3, to simulate IRS/AF systems with a full-stack, end-to-end perspective, with considerations on the impact of the channel model and the protocol stack of 5G NR networks. Our goal is to demonstrate whether these technologies can be used to relay 5G traffic requests and, if so, how to dimension IRS/AF nodes as a function of the number of end users