arXiv subjects

Özlem Tuğfe Demir

Publications and source records attributed to Özlem Tuğfe Demir.

At least 37 records · Page 2Linked to original sources

arXiv2026

Unlocking the Energy-Saving Potential in O-RAN Cell-Free Massive MIMO by Joint Orchestration of Radio, Wireless Fronthaul, and Cloud Resources

Network virtualization and cloudification in Open Radio Access Networks (O-RAN) enable joint orchestration of the processing and fronthaul resources, which are essential for realizing the energy-saving potential of cell-free massive MIMO networks. To harness this potential, we investigate cell-free massive MIMO deployed over an O-RAN architecture with a wireless fronthaul that removes the need for fiber deployment. We first model the end-to-end power consumption under wireless fronthaul. Then, we propose a joint orchestration framework for radio, fronthaul, and processing resources that minimizes end-to-end power consumption while satisfying user-equipment (UE) rate requirements and wireless-fronthaul constraints. Two algorithms are developed: a scenario-sampling/group-Lasso method for centralized precoding and a block-coordinate descent method for distributed precoding. Numerical results show that centralized precoding significantly outperforms distributed precoding. End-to-end resource orchestration provides up to 70% energy-savings compared to cloud-only orchestration and up to 15% compared to radio-only orchestration. Moreover, distributing the same total number of antennas across the coverage area, rather than concentrating them at a few radio units (RUs), substantially reduces network power consumption, demonstrating that cell-free massive MIMO can deliver both high performance and high energy efficiency in future mobile networks.

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arXiv2026

NCR vs. Passive/Active RIS: How Much NCR Amplification is Required to Beat RIS?

This paper investigates the fundamental tradeoff between reconfigurable intelligent surfaces (RISs) and network-controlled repeaters (NCRs) in terms of achievable signal-to-noise ratio (SNR). Considering an uplink system with a multi-antenna base station (BS) and a single-antenna user equipment (UE), we derive closed-form SNR expressions for passive RIS-, active RIS-, and NCR-assisted communication under line-of-sight propagation between the BS-RIS/NCR and RIS/NCR-UE. Both narrowband and wideband transmissions are analyzed, with and without the presence of a direct BS--UE link. Our analysis reveals a key structural difference: while the SNR achieved with RISs grows unboundedly with the number of RIS elements, the SNR provided by an NCR is fundamentally limited by the UE--repeater channel due to noise amplification. Nevertheless, we show that NCRs can outperform both passive and active RISs when deployed close to the UE, provided that sufficient amplification is available. Numerical results based on realistic path loss models quantify the amplification levels required for NCRs to outperform RISs across different deployment geometries and system dimensions. These findings provide clear design guidelines for the practical integration of RISs and NCRs in future wireless networks.

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arXiv2026

Cell-Free Massive MIMO with Hardware-Impaired Wireless Fronthaul

Cell-free massive MIMO (multiple-input multiple-output) enhances spectral and energy efficiency compared to conventional cellular networks by enabling joint transmission and reception across a large number of distributed access points (APs). Since these APs are envisioned to be low-cost and densely deployed, hardware impairments, stemming from non-ideal radio-frequency (RF) chains, are unavoidable. While existing studies primarily address hardware impairments on the access side, the impact of hardware impairments on the wireless fronthaul link has remained largely unexplored. In this work, we fill this important gap by introducing a novel amplify-and-forward (AF) based wireless fronthauling scheme tailored for cell-free massive MIMO. Focusing on the uplink, we develop an analytical framework that jointly models the hardware impairments at both the APs and the fronthaul transceivers, derives the resulting end-to-end distorted signal expression, and quantifies the individual contribution of each impairment to the spectral efficiency. Furthermore, we design distortion-aware linear combiners that optimally mitigate these effects. Numerical results demonstrate significant performance gains from distortion-aware processing and illustrate the potential of the proposed AF fronthauling scheme as a cost-effective enabler for future cell-free architectures.

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arXiv2026

Joint Impact of ADC and Fronthaul Quantization in Cell-Free Massive MIMO-OFDM Uplink

In the uplink of a cell-free massive MIMO system, quantization affects performance in two key domains: the time-domain distortion introduced by finite-resolution analog-to-digital converters (ADCs) at the access points (APs), and the fronthaul quantization of signals sent to the central processing unit (CPU). Although quantizing twice may seem redundant, the ADC quantization in orthogonal frequency-division duplex (OFDM) systems appears in the time domain, and one must then convert to the frequency domain, where quantization can be applied only to the signals at active subcarriers. This reduces fronthaul load and avoids unnecessary distortion, since the ADC output spans all OFDM samples while only a subset of subcarriers carries useful information. While both quantization effects have been extensively studied in narrowband systems, their joint impact in practical wideband OFDM-based cell-free massive MIMO remains largely unexplored. This paper addresses the gap by modeling the joint distortion and proposing a fronthaul strategy in which each AP processes the received signal to reduce quantization artifacts before transmission. We develop an efficient estimation algorithm that reconstructs the unquantized time-domain signal prior to fronthaul transmission and evaluate its effectiveness. The proposed design offers new insights for implementing efficient, quantization-aware uplink transmission in wideband cell-free architectures.

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arXiv2026

Feasibility Study Regarding Self-sustainable Reconfigurable Intelligent Surfaces

Without requiring operational costs such as cabling and powering while maintaining reconfigurable phase-shift capability, self-sustainable reconfigurable intelligent surfaces (ssRISs) can be deployed in locations inaccessible to conventional relays or base stations, offering a novel approach to enhance wireless coverage. This study assesses the feasibility of ssRIS deployment by analyzing two harvest-and-reflect (HaR) schemes: element-splitting (ES) and time-splitting (TS). We examine how element requirements scale with key system parameters, transmit power, data rate demands, and outage constraints under both line-of-sight (LOS) and non-line-of-sight (NLOS) ssRIS-to-user equipment (UE) channels. Analytical and numerical results reveal distinct feasibility characteristics. The TS scheme demonstrates better channel hardening gain, maintaining stable element requirements across varying outage margins, making it advantageous for indoor deployments with favorable harvesting conditions and moderate data rates. However, TS exhibits an element requirement that exponentially scales to harvesting difficulty and data rate. Conversely, the ES scheme shows only linear growth with harvesting difficulty, providing better feasibility under challenging outdoor scenarios. These findings establish that TS excels in benign environments, prioritizing reliability, while ES is preferable for demanding conditions requiring operational robustness.

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arXiv2025

Near-Field Beamfocusing, Localization, and Channel Estimation with Modular Linear Arrays

This paper investigates how near-field beamfocusing can be achieved using a modular linear array (MLA), composed of multiple widely spaced uniform linear arrays (ULAs). The MLA architecture extends the aperture length of a standard ULA without adding additional antennas, thereby enabling near-field beamfocusing without increasing processing complexity. Unlike conventional far-field beamforming, near-field beamfocusing enables simultaneous data transmission to multiple users at different distances in the same angular interval, offering significant multiplexing gains. We present a detailed mathematical analysis of the beamwidth and beamdepth achievable with the MLA and show that by appropriately selecting the number of antennas in each constituent ULA, ideal near-field beamfocusing can be realized. In addition, we propose a computationally efficient localization method that fuses estimates from each ULA, enabling efficient parametric channel estimation. Simulation results confirm the accuracy of the analytical expressions and that MLAs achieve near-field beamfocusing with a limited number of antennas, making them a promising solution for next-generation wireless systems.

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arXiv2025

Energy-Aware Resource Allocation for Multi-Operator Cell-Free Massive MIMO in V-CRAN Architectures

Cell-free massive multiple-input multiple-output (MIMO) implemented in virtualized cloud radio access networks (V-CRAN) has emerged as a promising architecture to enhance spectral efficiency (SE), network flexibility, and energy efficiency (EE) in next-generation wireless systems. In this work, we develop a holistic optimization framework for the efficient deployment of cell-free massive MIMO in V-CRAN with multiple mobile network operators (MNOs). Specifically, we formulate a set of integer programming models to jointly optimize access point (AP) selection, user equipment (UE) association, cloud resource allocation, and MNO assignment while minimizing the maximum total power consumption (TPC) across MNOs. We consider two different scenarios based on whether UEs can be assigned to arbitrary MNOs or not. The numerical results demonstrate the impact of different deployment assumptions on power consumption, highlighting that flexible UE-MNO assignment significantly reduces TPC. The findings provide key insights into optimizing resource management in cell-free massive MIMO V-CRAN, paving the way for energy-efficient wireless network implementations.

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arXiv2025

Green One-Bit Quantized Precoding in Cell-Free Massive MIMO

Cell-free massive MIMO (multiple-input multiple-output) is expected to be one of the key technologies in sixth-generation (6G) and beyond wireless communications, offering enhanced spectral efficiency for cell-edge user equipments by employing joint transmission and reception with a large number of antennas distributed throughout the region. However, high-resolution RF chains associated with these antennas significantly increase power consumption. To address this issue, the use of low-resolution analog-to-digital and digital-to-analog converters (ADCs/DACs) has emerged as a promising approach to balance power efficiency and performance in massive MIMO networks. In this work, we propose a novel quantized precoding algorithm tailored for cell-free massive MIMO systems, where the proposed method dynamically deactivates unnecessary antennas based on the structure of each symbol vector, thereby enhancing energy efficiency. Simulation results demonstrate that our algorithm outperforms existing methods such as squared-infinity norm Douglas-Rachford splitting (SQUID) and regularized zero forcing (RZF), achieving superior performance while effectively reducing power consumption.

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arXiv2025

Near-Field Channel Estimation with ELAA Modular Arrays Under Hardware Impairments

Extremely large-scale antenna arrays (ELAAs) enable high spatial resolution and multiplexing, especially for user equipments (UEs) in the radiative near-field. To reduce hardware cost, modular ELAA architectures with distributed baseband units (BBUs) are gaining traction. This paper addresses near-field line-of-sight (LOS) channel estimation under low noise amplifier (LNA)-induced hardware impairments in such modular systems. We propose computationally efficient estimators that exploit the array geometry and constant-modulus structure of near-field LOS channels, including a novel two-dimensional (2D) discrete Fourier transform (DFT) masking technique that improves estimation accuracy and significantly reduces fronthaul signaling. Numerical results show that the proposed methods significantly outperform the conventional least squares (LS) method.

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arXiv2025

Comprehensive Analysis of Behavioral Hardware Impairments in Cell-Free Massive MIMO-OFDM Uplink: Centralized Operation

Cell-free massive MIMO is a key 6G technology, offering superior spectral and energy efficiency. However, its dense deployment of low-cost access points (APs) makes hardware impairments unavoidable. While narrowband impairments are well-studied, their impact in wideband systems remains unexplored. This paper provides the first comprehensive analysis of hardware impairments, such as nonlinear distortion in low-noise amplifiers, phase noise, in-phase-quadrature imbalance, and low-resolution analog-to-digital converters, on uplink spectral efficiency in cell-free massive MIMO. Using an OFDM waveform and centralized processing, APs share channel state information for joint uplink combining. Leveraging Bussgang decomposition, we derive a distortion-aware combining vector that optimizes spectral efficiency by modeling distortion as independent colored noise.

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arXiv2025

Impact of Phase Noise and Power Amplifier Non-Linearities on Downlink Cell-Free Massive MIMO-OFDM Systems

Cell-free massive MIMO (multiple-input multiple-output) is a key enabler for the sixth generation (6G) of mobile networks, offering significant spectral and energy efficiency gains through user-centric operation of distributed access points (APs). However, its reliance on low-cost APs introduces inevitable hardware impairments, whose combined impact on wideband downlink systems remains unexplored when analyzed using behavioral models. This paper presents a comprehensive analysis of the downlink spectral efficiency (SE) in cell-free massive MIMO-OFDM systems under practical hardware impairments, including phase noise and third-order power amplifier nonlinearities. Both centralized and distributed precoding strategies are examined. By leveraging the Bussgang decomposition, we derive an SE expression and quantify the relative impact of impairments through simulations. Our results reveal that phase noise causes more severe degradation than power amplifier distortions, especially in distributed operation, highlighting the need for future distortion-aware precoding designs.

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arXiv2025

Control Signaling for Reconfigurable Intelligent Surfaces: How Many Bits are Needed?

Reconfigurable intelligent surfaces (RISs) can greatly improve the signal quality of future communication systems by reflecting transmitted signals toward the receiver. However, even when the base station (BS) has perfect channel knowledge and can compute the optimal RIS phase-shift configuration, implementing this configuration requires feedback signaling over a control channel from the BS to the RIS. This feedback must be kept minimal, as it is transmitted wirelessly every time the channel changes. In this paper, we examine how the feedback load, measured in bits, affects the performance of an RIS-aided system. Specifically, we investigate the trade-offs between codebook-based and element-wise feedback schemes, and how these influence the signal-to-noise ratio (SNR). We propose a novel quantization codebook tailored for line-of-sight (LoS) that guarantees a minimal SNR loss using a number of feedback bits that scale logarithmically with the number of RIS elements. We demonstrate the codebook's usefulness over Rician fading channels and how to extend it to handle a non-zero static path. Numerical simulations and analytical analysis are performed to quantify the performance degradation that results from a reduced feedback load, shedding light on how efficiently RIS configurations can be fed back in practical systems.

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arXiv2025

RIS-Assisted Survivable Fronthaul Design in Cell-Free Massive MIMO System

This paper investigates the application of reconfigurable intelligent surfaces (RISs) to improve fronthaul link survivability in cell-free massive MIMO (CF mMIMO) systems. To enhance the fronthaul survivability, two complementary mechanisms are considered. Firstly, RIS is set to provide reliable line-of-sight (LOS) connectivity and enhance the mmWave backup link. Secondly, a resource-sharing scheme that leverages redundant cable capacity through neighboring master access points (APs) to guarantee availability is considered. We formulate the redundant capacity minimization problem as a RIS-assisted multi-user MIMO rate control optimization problem, developing a novel solution that combines a modified weighted minimum mean square error (WMMSE) algorithm for precoding design with Riemannian gradient descent for RIS phase shift optimization. Our numerical evaluations show that RIS reduces the required redundant capacity by 65.6% compared to the no RIS case to reach a 99% survivability. The results show that the most substantial gains of RIS occur during complete outages of the direct disconnected master AP-CPU channel. These results demonstrate RIS's potential to significantly enhance fronthaul reliability while minimizing infrastructure costs in next-generation wireless networks.

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arXiv2025

Beyond Diagonal RIS Design for Parameter Estimation With and Without Eavesdropping

In this letter, we investigate the transmission of a complex-valued parameter vector from a transmitter to an intended receiver, considering both the presence and absence of an eavesdropper. The direct links from the transmitter to both the intended receiver and the eavesdropper are assumed to be blocked, and communications occur solely through cascaded channels facilitated by a beyond-diagonal reconfigurable intelligent surface (BD-RIS). While previous research has considered this system under conventional (diagonal) RIS assistance, we extend the setup to incorporate BD-RIS and quantify the resulting improvement in estimation performance at the intended receiver. This performance is measured by the trace of the Fisher information matrix (FIM), or equivalently, the average Fisher information, while simultaneously limiting the estimation capability of the eavesdropper. We propose solutions and algorithms for optimizing the BD-RIS response matrix and demonstrate their effectiveness. Numerical results reveal that the BD-RIS provides a significant enhancement in estimation quality compared to conventional diagonal RIS architectures.

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arXiv2025

Fair and Energy-Efficient Activation Control Mechanisms for Repeater-Assisted Massive MIMO

Massive multiple-input multiple-output (mMIMO) has been the core of 5G due to its ability to improve spectral efficiency and spatial multiplexing significantly; however, cell-edge users still experience performance degradation due to inter-cell interference and uneven signal distribution. While cell-free mMIMO (cfmMIMO) addresses this issue by providing uniform coverage through distributed antennas, it requires significantly more deployment cost due to the fronthaul and tight synchronization requirements. Alternatively, repeater-assisted massive MIMO (RA-MIMO) has recently been proposed to extend the coverage of cellular mMIMO by densely deploying low-cost single-antenna repeaters capable of amplifying and forwarding signals. In this work, we investigate amplification control for the repeaters for two different goals: (i) providing a fair performance among users, and (ii) reducing the extra energy consumption by the deployed repeaters. We propose a max-min amplification control algorithm using the convex-concave procedure for fairness and a joint sleep mode and amplification control algorithm for energy efficiency, comparing long- and short-term strategies. Numerical results show that RA-MIMO, with maximum amplification, improves signal-to-interference-plus-noise ratio (SINR) by over 20 dB compared to mMIMO and performs within 1 dB of cfmMIMO when deploying the same number of repeaters as access points in cfmMIMO. Additionally, our majority-rule-based long-term sleep mechanism reduces repeater power consumption by 70% while maintaining less than 1% spectral efficiency outage.

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arXiv2025

Spatial Frequencies and Degrees of Freedom: Their Roles in Near-Field Communications

As wireless technology begins to utilize physically larger arrays and/or higher frequencies, the transmitter and receiver will reside in each other's radiative near field. This fact gives rise to unusual propagation phenomena such as spherical wavefronts and beamfocusing, creating the impression that new spatial dimensions -- called degrees-of-freedom (DoF) -- can be exploited in the near field. However, this is a fallacy because the theoretically maximum DoF are already achievable in the far field. This paper sheds light on these issues by providing a tutorial on spatial frequencies, which are the fundamental components of wireless channels, and by explaining their role in characterizing the DoF in the near and far fields. In particular, we demonstrate how a single propagation path utilizes one spatial frequency in the far field and an interval of spatial frequencies in the near field. We explain how the array geometry determines the number of distinguishable spatial frequency bins and, thereby, the spatial DoF. We also describe how to model near-field multipath channels and their spatial correlation matrices. Finally, we discuss the research challenges and future directions in this field.

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arXiv2025

UAV-Based Cell-Free Massive MIMO: Joint Placement and Power Optimization under Fronthaul Capacity Limitations

We consider a cell-free massive multiple-input multiple-output (mMIMO) network, where unmanned aerial vehicles (UAVs) equipped with multiple antennas serve as distributed UAV-access points (UAV-APs). These UAV-APs provide seamless coverage by jointly serving user equipments (UEs) with out predefined cell boundaries. However, high-capacity wireless networks face significant challenges due to fronthaul limitations in UAV-assisted architectures. This letter proposes a novel UAV-based cell-free mMIMO framework that leverages distributed UAV-APs to serve UEs while addressing the capacity constraints of wireless fronthaul links. We evaluate functional split Options 7.2 and 8 for the fronthaul links, aiming to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among the UEs and minimize the power consumption by optimizing the transmit powers of UAV-APs and selectively activating them. Our analysis compares sub-6 GHz and millimeter wave (mmWave) bands for the fronthaul, showing that mmWave achieves superior SINR with lower power consumption, particularly under Option 8. Additionally, we determine the minimum fronthaul bandwidth required to activate a single UAV-AP under different split options.

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arXiv2025

Predictive Beamforming with Distributed MIMO

In vehicle-to-everything (V2X) applications, roadside units (RSUs) can be tasked with both sensing and communication functions to enable sensing-assisted communications. Recent studies have demonstrated that distance, angle, and velocity information obtained through sensing can be leveraged to reduce the overhead associated with communication beam tracking. In this work, we extend this concept to scenarios involving multiple distributed RSUs and distributed MIMO (multiple-input multiple-output) systems. We derive the state evolution model, formulate the extended Kalman-filter equations, and implement predictive beamforming for distributed MIMO. Simulation results indicate that, when compared with a co-located massive MIMO antenna array, distributed antennas lead to more uniform and robust sensing performance, coverage, and data rates, while the vehicular user is in motion.

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