Integrating Large AI Models (LAMs) into 6G mobile networks is a key enabler of the AI-Native Air Interface (AI-AI), where protocol intelligence must scale beyond handcrafted logic. This paper presents, to our knowledge, the first standards-compliant emulation of the Radio Resource Control (RRC) layer using a decoder-only LAM (LLAMA-class) fine-tuned with Low-Rank Adaptation (LoRA) on a multi-vendor corpus of real-world traces spanning both 5G and 4G systems. We treat RRC as a domain-specific language and construct a segmentation-safe, question-answer (Question-and-Answer (QA)) dataset that preserves Abstract Syntax Notation (ASN.1) structure through linearization prior to Byte Pair Encoding (BPE) tokenization. The proposed approach combines parameter-efficient adaptation with schema-bounded prompting to ensure syntactic and procedural fidelity. Evaluation introduces a standards-aware triad -- ASN.1 conformance, field-level coverage analysis, and uplink-to-downlink state-machine checks -- alongside semantic similarity and latency profiling across 120 configurations. On 30k 5G request-response pairs plus an additional 4.8k QA turns from 4G sessions, our 8B model achieves a median cosine similarity of 0.97, a 61% relative gain over a zero-shot baseline, while sustaining high conformance rates. These results demonstrate that LAMs, when augmented with protocol-aware reasoning, can directly orchestrate control-plane procedures, laying the foundation for the future Artificial Intelligence (AI)-native Radio Access Network (RAN).
Deploying fifth-generation (5G) networks in emerging markets demands a balance between performance targets and constraints in budget, spectrum, and infrastructure. We use MATLAB simulations to quantify how radio and architectural levers - MIMO (beamforming, diversity, spatial multiplexing), carrier aggregation (CA), targeted spectrum refarming to New Radio (NR), mmWave propagation with blockage/rain, and Non-Standalone (NSA) versus Standalone (SA) cores - affect capacity, coverage, latency, and interference robustness, with D2D and M2M as complements to wide-area access. Beamforming improves cell-edge SNR by about 3-6 dB, while spatial multiplexing dominates at moderate/high SNR via multi-stream gains. Throughput scales strongly with CA: increasing from 1 to 5x20-MHz carriers raises peak rate from about 200 Mb/s to about 1 Gb/s at 30 dB SNR; water-filling adds 5-12% over equal power at mid-SNR. Targeted mid-band refarming to NR increases median throughput by 60-90% in urban and 40-70% in rural scenarios when sub-1-GHz layers preserve coverage. At 28 GHz, rain and human blockage add about 8-30 dB excess loss, so viable mmWave deployment concentrates in LOS hot zones with narrow-beam arrays and short inter-site distances. NSA delivers broader initial coverage than SA by reusing LTE/EPC, while SA becomes attractive as transport improves (e.g., >= 10 Gb/s and < 5 ms RTT) and site density grows. We synthesize these results into a practical roadmap: start NR on NSA, prioritize CA-centric spectrum strategies with focused refarming, densify selectively in demand hotspots, and migrate to SA as backhaul and device ecosystems mature.
This study investigated the dynamic connectivity patterns between EEG and fMRI modalities, contributing to our understanding of brain network interactions. By employing a comprehensive approach that integrated static and dynamic analyses of EEG-fMRI data, we were able to uncover distinct connectivity states and characterize their temporal fluctuations. The results revealed modular organization within the intrinsic connectivity networks (ICNs) of the brain, highlighting the significant roles of sensory systems and the default mode network. The use of a sliding window technique allowed us to assess how functional connectivity varies over time, further elucidating the transient nature of brain connectivity. Additionally, our findings align with previous literature, reinforcing the notion that cognitive states can be effectively identified through short-duration data, specifically within the 30-60 second timeframe. The established relationships between connectivity strength and cognitive processes, particularly during different visual states, underscore the relevance of our approach for future research into brain dynamics. Overall, this study not only enhances our understanding of the interplay between EEG and fMRI signals but also paves the way for further exploration into the neural correlates of cognitive functions and their implications in clinical settings. Future research should focus on refining these methodologies and exploring their applications in various cognitive and clinical contexts.
In this note, a result of a previous paper on the Clark conjecture on time-warped bandlimited signals is extended to a more general class of the time warping functions, which includes most of the common functions in practice.
This short note is a supplement to [1], in which the total variation of graph distributional signals is introduced and studied. We introduce a different formulation of total variation and relate it to the notion of edge centrality. The relation provides a different perspective of total variation and may facilitate its computation.
A sharp inequality for $\ell_p$ quasi-norm with $0<p\leq 1$ and $\ell_q$-norm with $q>1$ is derived, which shows that the difference between $\|\textbf{\textit{x}}\|_p$ and $\|\textbf{\textit{x}}\|_q$ of an $n$-dimensional signal $\textbf{\textit{x}}$ is upper bounded by the difference between the maximum and minimum absolute value in $\textbf{\textit{x}}$. The inequality could be used to develop new $\ell_p$-minimization algorithms.
Lecture notes of a tutorial on topology in sound synthesis and digital signal processing held at international conference for digital audio effects (DAFx-22) in Vienna, Austria.
This paper reviews methods for autonomous tuning of optical transceivers, based on an overhead management channel between the modules on both sides of the link. Different implementation options for the tuning principle, as well as for the tunable laser are introduced.
The purpose of this article is to discuss recent advances in the growing field of phase retrieval, and to publicize open problems that we believe will be of interest to mathematicians in general, and algebraists in particular.
In this short paper, we describe an efficient numerical solver for the optimal sampling problem considered in "Designing Sampling Schemes for Multi-Dimensional Data". An implementation may be found on https://www.maths.lu.se/staff/andreas-jakobsson/publications/.
We propose a superscalar parallel two-stage carrier phase recovery architecture to improve the performance of optical coherent receivers in the presence of Tx I/Q imbalance, Tx I/Q skew, and laser frequency fluctuations.
We design and experimentally demonstrate a radio frequency interference management system with free-space optical communication and photonic signal processing. The system provides real-time interference cancellation in 6 GHz wide bandwidth.
A low complexity frequency offset estimation algorithm based on all-phase FFT for M-QAM is proposed. Compared with two-stage algorithms such as FFT+CZT and FFT+ZoomFFT, our algorithm can lower computational complexity by 73% and 30% respectively, without loss of the estimation accuracy.
Miroslav Dimitrov, Tsonka Baitcheva, Nikolay Nikolov
Simple and efficient algorithm based on heuristic search by shotgun hill climbing to construct binary sequences with small peak sidelobe levels (PSL) is suggested. The algorithm is applied for generation of binary sequences of lengths between 106 and 300. Improvements are obtained in almost half of the considered lengths while for the rest of the lengths, binary sequences with the same PSL values as reported in the state-of-the-art publications are found.
The interplay of shaped signaling and fiber nonlinearities is reviewed in the asymptotic and finite-length regime. We present explanations and discuss implications of an optimum shaping length of just a few hundred symbols.
Motivated by analyzing complicated time series, nonlinear-type time-frequency analysis became an active research topic in the past decades. Those developed tools have been applied to various problems. In this article, we review those developed tools and summarize their applications to high-frequency biomedical signals.
A proposed Line of Sight and Non Line of Sight model for Terahertz Communication with achievable data rates of upto 100GBps using Photonic Topological Insulator.
In this note, we discuss the shift retrieval problems, both classical and compressed, and provide connections between them using circulant matrices. We review the properties of circulant matrices necessary for our calculations and then show how shifts can be recovered from a single measurement.
Sie haben es wieder getan: Nachdem arXiv erst im April um Applied Physics erweitert wurde, sind jetzt mit Electrical Engineering and Systems Science EESS und Economics Econ gleich zwei weitere Fachgebiete hinzugekommen.