arXiv subjects

David Reiss

Publications and source records attributed to David Reiss.

5 recordsLinked to original sources

arXiv2026

Toward Fully Autonomous 6G Networks: AI-driven Operational Efficiency and Optimization

Mobile networks evolution is characterized by a substantial increase in system complexity, driven by the need to accommodate a growing number of heterogeneous services on top of the digital infrastructure. This growth in service accommodation is expected to accelerate with the adoption of the Network as a Service (NaaS) paradigm, which has emerged as a promising approach to accelerate network innovation while enabling new revenue streams for operators. Although it is fundamental to abstract network capabilities for third-party developers, it poses significant challenges in terms of efficient network operation. To address this increased complexity, future mobile networks are envisioned to be inherently Artificial Intelligence (AI)-native. In particular, the integration of AI within the Radio Access Network (RAN) becomes a key enabler for optimizing operation, energy consumption, and autonomous network control. In this context, this research explores the convergence of AI-native RAN and NaaS ecosystems to enable autonomous 6G RAN management. We propose an Agentic-based orchestration framework capable of interpreting intent-based policies. The proposed framework becomes key to integrate external NaaS requests with internal network management policies.

cs.NI↗

arXiv2026

A Practical AI-Driven Strategy for Cell On/Off Switching under Adaptable QoS Constraints

The rapid expansion of 5G networks has intensified concerns over their sustainability, as denser Radio Access Network (RAN) deployments have increased overall power consumption. Although numerous studies have examined energy-efficient cell on/off switching, few have focused on approaches capable of dynamically adapting to operator-defined Quality of Service (QoS) requirements. In this paper, we propose a Long Short Term Memory (LSTM)based strategy, trained using a dataset from a European Mobile Network Operator (MNO), that enforces both target throughput levels and outage-tolerance constraints. Unlike previous approaches, our model adapts to different QoS requirements by tuning a decision threshold at inference time, enabling operators to balance energy savings and service guarantees without retraining. Across an unseen week, the method attains 63 to 96 % of an oracle's energy savings while largely meeting operator-specified constraints. We also provide CO2 and OPEX estimates under representative scenarios to quantify potential operator benefits.

cs.NI↗

arXiv2000

Tests of the Accelerating Universe with Near-Infrared Observations of a High-Redshift Type Ia Supernova

We have measured the rest-frame B,V, and I-band light curves of a high-redshift type Ia supernova (SN Ia), SN 1999Q (z=0.46), using HST and ground-based near-infrared detectors. A goal of this study is the measurement of the color excess, E_{B-I}, which is a sensitive indicator of interstellar or intergalactic dust which could affect recent cosmological measurements from high-redshift SNe Ia. Our observations disfavor a 30% opacity of SN Ia visual light by dust as an alternative to an accelerating Universe. This statement applies to both Galactic-type dust (rejected at the 3.4 sigma confidence level) and greyer dust (grain size > 0.1 microns; rejected at the 2.3 to 2.6 sigma confidence level) as proposed by Aguirre (1999). The rest-frame $I$-band light cur ve shows the secondary maximum a month after B maximum typical of nearby SNe Ia of normal luminosi ty, providing no indication of evolution as a function of redshift out to z~0.5. A n expanded set of similar observations could improve the constraints on any contribution of extragalactic dust to the dimming of high-redshift SNe Ia.

astro-ph↗

arXiv1998

Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant

We present observations of 10 type Ia supernovae (SNe Ia) between 0.16 < z < 0.62. With previous data from our High-Z Supernova Search Team, this expanded set of 16 high-redshift supernovae and 34 nearby supernovae are used to place constraints on the Hubble constant (H_0), the mass density (Omega_M), the cosmological constant (Omega_Lambda), the deceleration parameter (q_0), and the dynamical age of the Universe (t_0). The distances of the high-redshift SNe Ia are, on average, 10% to 15% farther than expected in a low mass density (Omega_M=0.2) Universe without a cosmological constant. Different light curve fitting methods, SN Ia subsamples, and prior constraints unanimously favor eternally expanding models with positive cosmological constant (i.e., Omega_Lambda > 0) and a current acceleration of the expansion (i.e., q_0 < 0). With no prior constraint on mass density other than Omega_M > 0, the spectroscopically confirmed SNe Ia are consistent with q_0 <0 at the 2.8 sigma and 3.9 sigma confidence levels, and with Omega_Lambda >0 at the 3.0 sigma and 4.0 sigma confidence levels, for two fitting methods respectively. Fixing a ``minimal'' mass density, Omega_M=0.2, results in the weakest detection, Omega_Lambda>0 at the 3.0 sigma confidence level. For a flat-Universe prior (Omega_M+Omega_Lambda=1), the spectroscopically confirmed SNe Ia require Omega_Lambda >0 at 7 sigma and 9 sigma level for the two fitting methods. A Universe closed by ordinary matter (i.e., Omega_M=1) is ruled out at the 7 sigma to 8 sigma level. We estimate the size of systematic errors, including evolution, extinction, sample selection bias, local flows, gravitational lensing, and sample contamination. Presently, none of these effects reconciles the data with Omega_Lambda=0 and q_0 > 0.

astro-ph↗

arXiv1998

The High-Z Supernova Search: Measuring Cosmic Deceleration and Global Cur vature of the Universe Using Type Ia Supernovae

The High-Z Supernova Search is an international collaboration to discover and monitor type Ia supernovae (SN Ia) at $z > 0.2$ with the aim of measuring cosmic deceleration and global curvature. Our collaboration has pursued a basic understanding of supernovae in the nearby Universe, discovering and observing a large sample of objects, and developing methods to measure accurate distances with SN Ia. This paper describes the extension of this program to $z \geq 0.2$, outlining our search techniques and follow-up program. We have devised high-throughput filters which provide accurate two-color restframe $B$ and $V$ light curves of SN Ia, enabling us to produce precise, extinction-corrected luminosity distances in the range $0.25 < z < 0.55$. Sources of systematic error from K-corrections, extinction, selection effects, and evolution are investigated, and their effects estimated. We present photometric and spectral observations of SN 1995K, our program's first supernova, and use the data to obtain a precise measurement of the luminosity distance to the $z=0.479$ host galaxy. This object, when combined with a nearby sample of SN, yields an estimate for the matter density of the Universe of $Ω_M = -0.2^{+1.0}_{-0.8}$ if $Ω_Λ= 0$. For a spatially flat universe composed of normal matter and a cosmological constant, we find $Ω_M = 0.4^{+0.5}_{-0.4}$, $Ω_Λ= 0.6^{+0.4}_{-0.5}$. We demonstrate that with a sample of $\sim 30$ objects, we should be able to determine relative luminosity distances over the range $0 < z< 0.5$ with sufficient precision to measure $Ω_M$ with an uncertainty of $\pm 0.2$.

astro-ph↗