arXiv subjects

C. Nicolas Barati

Publications and source records attributed to C. Nicolas Barati.

8 recordsLinked to original sources

arXiv2026

Noncoherent Detection and Interference Nulling for Terrestrial-Satellite Downlink Coexistence in the Upper Mid-Band

Terrestrial--satellite coexistence in the upper mid-band is challenging when a terrestrial base station has limited prior information about non-terrestrial receivers and their uplink transmissions. This paper studies noncoherent victim sensing and interference nulling, where uplink sensing snapshots are observed while the transmitted waveform is treated as unknown. For a single victim, we show that the generalized likelihood-ratio test reduces to a principal-eigenvector estimator of the sample covariance. For multiple victims, we combine MDL-based model-order selection with MUSIC to recover anonymous direction and power information that is sufficient for beam design without pilot knowledge or user identities. These estimates are then used in a nulling beamformer that preserves the intended terrestrial link while reducing leakage toward detected victims. We further analyze the single-victim estimator in the large-matrix regime and show that estimation accuracy improves with sensing SNR, which reveals the observed interplay between path loss and estimation quality. Site-specific ray-tracing results show significant reduction of NTN INR with only modest degradation of TN SINR.

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arXiv2026

Enabling Real-Time AI in O-RAN: Deploying and Measuring AI Inside a Near-RT RIC xApp

Open Radio Access Network (O-RAN) architectures introduce programmable Near-Real-Time RAN Intelligent Controllers (Near-RT RICs) that support closed-loop control through xApps at timescales from 10 ms to 1 s. Although AI has been widely studied for RAN optimization, fewer works demonstrate measured AI inference embedded directly within the Near-RT RIC software loop on a live testbed. This paper presents an AI-enabled network-state classification xApp implemented on an OpenAirInterface (OAI) and FlexRIC testbed. The xApp is trained and evaluated on a structured synthetic dataset that emulates cross-layer RAN states using MAC, RLC, PDCP, GTP, and UE-count features. The results validate embedding and execution feasibility rather than production-level generalization. Logistic regression and a shallow multilayer perceptron (MLP) are exported as deterministic C inference modules and compiled into the xApp binary, eliminating external machine-learning runtime dependencies. Measured inference latency is 1 to 5 microseconds for logistic regression and 10 to 25 microseconds for the MLP, while end-to-end service latency remains below 4 ms. A six-model comparison shows that supervised models achieve similar accuracy, ranging from 0.88 to 0.90, indicating that LR and MLP similarity reflects the proxy problem structure rather than limited model exploration. Noise ablation, confusion-matrix analysis, and CDF-based latency characterization show that both embedded models satisfy the 10 ms Near-RT budget for more than 95% of projected loop executions. These results demonstrate that lightweight AI can operate within Near-RT RIC timing constraints while preserving deterministic execution. We also release RIC Workbench, a lightweight orchestration dashboard for reproducing the testbed on commodity hardware.

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arXiv2026

A Self-Calibrating SDR for High Fidelity Beam- and Null-forming Arrays

Null forming is increasingly essential in modern wireless systems for spectrum-sharing, anti-jamming, and covert communications in contested and congested environments. Achieving deep nulls, however, is far more demanding than conventional beam steering: nulls are intrinsically narrow, and even small phase, timing, or gain mismatches across RF chains can significantly degrade suppression. This work develops and validates a self-calibrating SDR architecture tailored for high-fidelity null forming using a compact reference transmitter directionally coupled to the antenna feeds. We demonstrate the effectiveness of the approach through simulation and experimental measurements on an SDR platform operating from 3.0 to 3.5GHz, a band of growing importance for Department of Defense spectrum-sharing initiatives.

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arXiv2020

Energy and Latency of Beamforming Architectures for Initial Access in mmWave Wireless Networks

Future millimeter-wave (mmWave) systems, 5G cellular or WiFi, must rely on highly directional links to overcome severe pathloss in these frequency bands. Establishing such links requires the mutual discovery of the transmitter and the receiver %in the angular domain potentially leading to a large latency and high energy consumption. In this work, we show that both the discovery latency and energy consumption can be significantly reduced by using fully digital front-ends. In fact, we establish that by reducing the resolution of the fully-digital front-ends we can achieve lower energy consumption compared to both analog and high-resolution digital beamformers. Since beamforming through analog front-ends allows sampling in only one direction at a time, the mobile device is ''on'' for a longer time compared to a digital beamformer which can get spatial samples from all directions in one shot. We show that the energy consumed by the analog front-end can be four to six times more than that of the digital front-ends, depending on the size of the employed antenna arrays. We recognize, however, that using fully digital beamforming post beam discovery, i.e., for data transmission, is not viable from a power consumption standpoint. To address this issue, we propose the use of digital beamformers with low-resolution analog to digital converters (4 bits). This reduction in resolution brings the power consumption to the same level as analog beamforming for data transmissions while benefiting from the spatial multiplexing capabilities of fully digital beamforming, thus reducing initial discovery latency and improving energy efficiency.

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arXiv2019

A Case for Digital Beamforming at mmWave

Due to the heavy reliance of millimeter-wave (mmWave) wireless systems on directional links, beamforming (BF) with high-dimensional arrays is essential for cellular systems in these frequencies. How to perform the array processing in a power efficient manner is a fundamental challenge. Analog and hybrid BF require fewer analog-to-digital and digital-to-analog converters (ADCs and DACs), but can only communicate in a small number of directions at a time, limiting directional search, spatial multiplexing and control signaling. Digital BF enables flexible spatial processing, but must be operated at a low quantization resolution to stay within reasonable power levels. This decrease in quantizer resolution introduces noise in the received signal and degrades the quality of the transmitted signal. To assess the effect of low-resolution quantization on cellular system, we present a simple additive white Gaussian noise (AWGN) model for quantization noise. Simulations with this model reveal that at moderate resolutions (3-4 bits per ADC), there is negligible loss in downlink cellular capacity from quantization. In essence, the low-resolution ADCs limit the high SNR, where cellular systems typically do not operate. For the transmitter, it is shown that DACs with 4 or more bits of resolution do not violate the adjacent carrier leakage limit set by 3-rd Generation Partnership Project (3GPP) New Radio (NR) standards for cellular operations. Further, this work studies the effect of low resolution quantization on the error vector magnitude (EVM) of the transmitted signal.In fact, our findings suggests that low-resolution fully digital BF architectures can be a power efficient alternative to analog or hybrid beamforming for both transmitters and receivers at millimeter wave.

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arXiv2018

5G Millimeter Wave Cellular System Capacity with Fully Digital Beamforming

Due to heavy reliance of millimeter-wave (mmWave) wireless systems on directional links, Beamforming (BF) with high-dimensional arrays is essential for cellular systems in these frequencies. How to perform the array processing in a power efficient manner is a fundamental challenge. Analog and hybrid BF require fewer analog-to-digital converters (ADCs), but can only communicate in a small number of directions at a time,limiting directional search, spatial multiplexing and control signaling. Digital BF enables flexible spatial processing, but must be operated at a low quantization resolution to stay within reasonable power levels. This paper presents a simple additive white Gaussian noise (AWGN) model to assess the effect of low resolution quantization of cellular system capacity. Simulations with this model reveal that at moderate resolutions (3-4 bits per ADC), there is negligible loss in downlink cellular capacity from quantization. In essence, the low-resolution ADCs limit the high SNR, where cellular systems typically do not operate. The findings suggest that low-resolution fully digital BF architectures can be power efficient, offer greatly enhanced control plane functionality and comparable data plane performance to analog BF.

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arXiv2016

Directional Initial Access for Millimeter Wave Cellular Systems

The millimeter wave (mmWave) bands have recently attracted considerable interest for next-generation cellular systems due to the massive available bandwidths at these frequencies. However, a key challenge in designing mmWave cellular systems is initial access -- the procedure by which a mobile establishes an initial link-layer connection to a base station cell. MmWave communication relies on highly directional transmissions and the initial access procedure must thus provide a mechanism by which initial transmission directions can be searched in a potentially large angular space. Design options are compared considering different scanning and signaling procedures to evaluate access delay and system overhead. The channel structure and multiple access issues are also considered. The analysis demonstrates significant benefits of low-resolution fully digital architectures in comparison to single stream analog beamforming.

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arXiv2015

Directional Cell Discovery in Millimeter Wave Cellular Networks

The acute disparity between increasing bandwidth demand and available spectrum, has brought millimeter wave (mmW) bands to the forefront of candidate solutions for the next-generation cellular networks. Highly directional transmissions are essential for cellular communication in these frequencies to compensate for high isotropic path loss. This reliance on directional beamforming, however, complicates initial cell search since the mobile and base station must jointly search over a potentially large angular directional space to locate a suitable path to initiate communication. To address this problem, this paper proposes a directional cell discovery procedure where base stations periodically transmit synchronization signals, potentially in time-varying random directions, to scan the angular space. Detectors for these signals are derived based on a Generalized Likelihood Ratio Test (GLRT) under various signal and receiver assumptions. The detectors are then simulated under realistic design parameters and channels based on actual experimental measurements at 28~GHz in New York City. The study reveals two key findings: (i) digital beamforming can significantly outperform analog beamforming even when the digital beamforming uses very low quantization to compensate for the additional power requirements; and (ii) omni-directional transmissions of the synchronization signals from the base station generally outperforms random directional scanning.

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