arXiv subjects

Ebrahim Bedeer

Publications and source records attributed to Ebrahim Bedeer.

At least 19 recordsLinked to original sources

arXiv2026

Measured-Pattern-Aware Pinching-Antenna Systems With Coupling-Efficiency Optimization

Pinching-antenna (PA) systems have been widely investigated as a flexible architecture for waveguide-enabled wireless transmission. Existing analytical models, however, often rely on isotropic radiation assumptions and simplified couplingefficiency settings, which may overlook two practical design factors: the geometry-dependent radiation pattern of each PA and the sequential extraction of guided power along the waveguide. In this paper, we propose a measured-radiation-pattern-aware PA framework that incorporates an externally obtained radiation pattern, waveguide attenuation, and coupling-dependent power extraction. For a single PA, the resulting placement rule balances directional gain, waveguide loss, and free-space path loss, leading to a coupling-efficiency threshold for outperforming a fixed isotropic antenna. For multiple PAs, we study phase-matched placement and coupling-efficiency design under both uniform and independently controllable coupling. The uniform-coupling case yields a one-dimensional optimality condition and reveals that the preferred coupling efficiency decreases as more phasematched PAs participate in coherent combining. The independently controllable case admits a closed-form power-allocation structure, where stronger effective directional channels receive larger radiated power fractions. Numerical results based on a representative measured PA radiation pattern demonstrate the importance of jointly accounting for measured-radiation-patternaware placement and coupling-efficiency optimization.

cs.IT↗

arXiv2026

PAPR Reduction for AFDM by Affine-Domain Circular Shift without Side Information

This paper proposes a novel method to reduce the peak-to-average-power-ratio (PAPR) of affine frequency division multiplexing (AFDM) signals without side information (SI). The method is based on circularly shifting the original transmit signal in the affine domain, and selecting the shifted candidate with the lowest PAPR. Next, a maximum-likelihood-based (MLB) receiver is derived, which exploits the position of the AFDM pilot and guard band to detect the shift applied at the transmitter without SI. Simulation results show that the proposed method can achieve 2.5 to 4 dB in PAPR reduction as compared to original AFDM and existing schemes, which can be translated into significantly lower error rate, depending on the quality of power amplifiers.

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arXiv2026

Noncoherent Maximum Likelihood Detection for LoRa Signals in Multipath Fading

This letter derives the noncoherent (NC) maximum likelihood (ML) detection rule for LoRa signals under Rician multipath fading channels. The proposed NC-ML detection only requires the channel statistics, not the actual instantaneous channel state information (CSI), which eliminates the overhead associated with channel estimation. Simulation results show that despite the low-complexity, the proposed detection scheme significantly improves the performance of LoRa detection over multipath channels. Notably, in time-invariant channels, the NC-ML receiver can achieve equivalent performance as compared to existing coherent schemes, and even surpasses them when Doppler shift is present, while not relying on the channel estimation nor reference signals extracted from the preamble.

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arXiv2026

Robust Single- and Multi-Pinching Antenna Systems Under User Location Uncertainty

Pinching antenna (PA) systems have recently emerged as a promising architecture for reconfigurable wireless communications by enabling flexible antenna placement along a dielectric waveguide. However, existing works typically assume perfect knowledge of user locations, which is impractical in real systems where location estimation errors are inevitable. In this paper, we investigate robust power allocation and antenna placement for PA systems under user location uncertainty. We consider both single-antenna and multi-antenna configurations, where the true user locations are unknown but lie within bounded uncertainty regions. For the single-antenna case, we adopt a worst-case robust design and leverage the S-procedure to transform the joint power allocation and antenna placement problem into a convex semidefinite program (SDP), ensuring that quality-of-service (QoS) constraints are satisfied for all possible user locations. For the multi-antenna case, we address the additional challenges arising from the superposition of channel components from multiple antennas by developing an efficient numerical procedure to evaluate the worst-case channel gain. Then, we derive a closed-form solution for optimal power allocation and develop a block coordinate descent algorithm to optimize antenna placement. Simulation results show that the proposed framework provides robustness to location uncertainty while achieving power consumption close to that of outage-based benchmark schemes.

cs.IT↗

arXiv2026

Index Modulation for Modulation on Conjugate-Reciprocal Zeros (IM-MOCZ)

This paper investigates the application of Index Modulation (IM) to Modulation on Conjugate-Reciprocal Zeros (MOCZ) to enhance spectral efficiency (SE) in short packet communications. The proposed IM-MOCZ scheme splits an $N$-bit message into two streams: $N-K$ bits select one of $2^{N-K}$ uniquely designed codebooks, while the remaining $K$ bits are transmitted with conventional binary-MOCZ (BMOCZ) using the selected codebook. At the receiver, Root Finding Minimum Distance (RFMD) or Direct Zero-Testing (DiZeT) detectors evaluate all candidate codebooks and compute penalty metrics, with a majority vote rule selecting the most confident codebook and recovering the transmitted message. The proposed IM-MOCZ can provide higher SE gains than conventional BMOCZ at the cost of increasing the computational complexity, with simulations demonstrating improved bit error rate (BER) and block error rate (BLER) performance for larger $K$ relative to $N$, when compared to conventional BMOCZ.

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arXiv2026

Phase-Aware Localization in Pinching Antenna Systems: CRLB Analysis and ML Estimation

Pinching antenna systems (PASS) have emerged as a promising architecture for high-frequency wireless communications. In this letter, we investigate user localization in PASS by jointly exploiting the received signal amplitude and phase information. A complex baseband signal model is formulated to capture free-space path loss, waveguide attenuation, and distance-dependent phase rotation between the user and each pinching antenna. Based on this model, we derive the Fisher information matrix and closed-form Cramer-Rao lower bound and position error bound. The derived analysis reveals that the phase-induced Fisher information decays with the fourth power of the user-antenna distance, whereas the amplitude-induced information decays with the sixth power, explaining the fundamental advantage of phase-aware localization in typical PASS deployments. A maximum likelihood estimator is then developed and implemented through a two-stage procedure combining coarse grid search and Levenberg-Marquardt refinement. Numerical results show that the proposed estimator achieves low positioning error and generally outperforms the considered benchmarks under different noise powers, numbers of pinching antennas, and user locations. In the considered scenario, the proposed method achieves sub-meter-level accuracy over the evaluated service area and yields substantially lower positioning error than the amplitude-only benchmark.

cs.IT↗

arXiv2026

Hybrid Wireless-Fed Pinching-Antenna Systems with Residual Self-Interference-Aware Optimization

Pinching-antenna systems (PASS) have recently emerged as a promising solution for enhancing coverage in high-frequency wireless communications by guiding signals through dielectric waveguides and radiating them via position-adjustable antennas. However, their practical deployment is limited by waveguide attenuation and the need for physical line installation, which restrict flexibility and coverage extension. To address these challenges, this paper proposes a hybrid wireless-fed PASS architecture, where a base station equipped with an antenna array provides adaptive directional transmission to a full-duplex amplify-and-forward relay employing a horn antenna to feed the waveguide. This hybrid design balances beamforming flexibility and low-complexity directional waveguide interfacing. Residual self-interference (SI) at the full-duplex relay is explicitly modeled to capture practical system impairments. Under this framework, a total power minimization problem is formulated subject to a quality-of-service constraint at the user equipment, involving the joint optimization of the pinching-antenna position, the relay amplification gain, and the base station transmit power. By exploiting the structure of the end-to-end signal-to-noise ratio, the optimal pinching-antenna position is first obtained in closed form by balancing waveguide attenuation and free-space path loss. Closed-form expressions for the optimal relay gain and transmit power are then derived. Numerical results under the adopted system-level model demonstrate that the proposed scheme reduces total power consumption compared with conventional benchmark systems, while providing a more realistic and robust design by accounting for residual SI.

cs.IT↗

arXiv2026

Spectral-Efficient LoRa with Low Complexity Detection

In this paper, we propose a spectral-efficient LoRa (SE-LoRa) modulation scheme with a low complexity successive interference cancellation (SIC)-based detector. The proposed communication scheme significantly improves the spectral efficiency of LoRa modulation, while achieving an acceptable error performance compared to conventional LoRa modulation, especially in higher spreading factor (SF) settings. We derive the joint maximum likelihood (ML) detection rule for the SE-LoRa transmission scheme that turns out to be of high computational complexity. To overcome this issue, and by exploiting the frequency-domain characteristics of the dechirped SE-LoRa signal, we propose a low complexity SIC-based detector with a computation complexity at the order of conventional LoRa detection. By computer simulations, we show that the proposed SE-LoRa with low complexity SIC-based detector can improve the spectral efficiency of LoRa modulation up to $445.45\%$, $1011.11\%$, and $1071.88\%$ for SF values of $7$, $9$, and $11$, respectively, while maintaining the error performance within less than $3$ dB of conventional LoRa at symbol error rate (SER) of $10^{-3}$ in Rician channel conditions.

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arXiv2025

Novel Double-Chirp Preamble Design for Multiuser Asynchronous Massive MIMO LoRa Networks

This paper proposes a novel preamble design and detection method for multiuser asynchronous massive MIMO LoRa networks. Unlike existing works, which only consider the preamble detection for a single end device (ED), we propose to simultaneously detect the preambles of multiple EDs that asynchronously transmit their uplink (UL) packets to a multiple-antenna gateway (GW). First, we show that the preamble detection in multiuser LoRa networks with the conventional single-chirp preamble suffers from the so-called preamble resemblance effect. This means that the preamble of any single ED can resemble the preambles of all EDs in the network and make it impossible to determine to which ED a preamble belongs. To address this problem, a novel double-chirp preamble design and a preamble assignment method are proposed, which can mitigate the preamble resemblance effect by making the preamble of each ED unique and recognizable. Next, a maximum-likelihood (ML) based detection scheme for the proposed double-chirp preamble is derived. Finally, since the proposed algorithm requires the calculation of the discrete Fourier transform (DFT) every sampling period, we propose a low-complexity technique to calculate the DFT recursively to reduce the complexity of our proposed design. Simulation shows that the proposed preamble design and detection require just about 2 dB more power to increase the number of EDs from one to 15 in the Rayleigh fading channel while achieving the same preamble detection error performance.

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arXiv2025

Analysis and Compensation of Receiver IQ Imbalance and Residual CFO Error for AFDM

Affine frequency division multiplexing (AFDM) is a promising waveform for future wireless communication systems. In this paper, we analyze the impact of receiver in-phase and quadrature (IQ) imbalance and residual carrier frequency offset (CFO) error on AFDM signals. Our analysis shows that the receiver IQ imbalance may not preserve the sparsity of the AFDM effective channel matrix because of the complex-conjugate operator of the discrete affine Fourier transform (DAFT). Moreover, the residual CFO error causes energy leakage in the effective channel matrix in the affine domain. To mitigate these effects, we extend the linear minimum mean-square error (LMMSE) detector to handle the improper Gaussian noise arising from the receiver IQ imbalance. Simulation results demonstrate that the proposed LMMSE detector effectively compensates for the receiver hardware impairments.

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arXiv2025

A Novel CNN Based Standalone Detector for Faster-than-Nyquist Signaling

This paper presents a novel convolutional neural network (CNN)-based detector for faster-than-Nyquist (FTN) signaling, introducing structured fixed kernel layers with domain-informed masking to effectively mitigate intersymbol interference (ISI). Unlike standard CNN architectures that rely on moving kernels, the proposed approach employs fixed convolutional kernels at predefined positions to explicitly learn ISI patterns at varying distances from the central symbol. To enhance feature extraction, a hierarchical filter allocation strategy is employed, assigning more filters to earlier layers for stronger ISI components and fewer to later layers for weaker components. This structured design improves feature representation, eliminates redundant computations, and enhances detection accuracy while maintaining computational efficiency. Simulation results demonstrate that the proposed detector achieves near-optimal bit error rate (BER) performance, comparable to the BCJR algorithm for the compression factor $\tau \geq 0.7$, while offering up to $46\%$ and $84\%$ computational cost reduction over M-BCJR for BPSK and QPSK, respectively. Additional evaluations confirm the method's adaptability to high-order modulations (up to 64-QAM), resilience in quasi-static multipath Rayleigh fading channels, and effectiveness under LDPC-coded FTN transmission, highlighting its robustness and practicality.

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arXiv2025

A Novel Domain-Aware CNN Architecture for Faster-than-Nyquist Signaling Detection

This paper proposes a convolutional neural network (CNN)-based detector for faster-than-Nyquist (FTN) signaling that employs structured fixed kernel layers with domain-informed masking to mitigate intersymbol interference (ISI). Unlike standard CNNs with sliding kernels, the proposed method utilizes fixed-position kernels to directly capture ISI effects at varying distances from the central symbol. A hierarchical filter allocation strategy is also introduced, assigning more filters to earlier layers for strong ISI patterns and fewer to later layers for weaker ones. This design improves detection accuracy while reducing redundant operations. Simulation results show that the detector achieves near-optimal bit error rate (BER) performance for $\tau \geq 0.7$, closely matching the BCJR algorithm, and offers computational gains of up to $46\%$ and $84\%$ over M-BCJR for BPSK and QPSK, respectively. Comparative analysis with other methods further highlights the efficiency and effectiveness of the proposed approach. To the best of our knowledge, this is the first application of a fixed-kernel CNN architecture tailored for FTN detection in the literature.

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arXiv2025

Ambiguity Function Analysis of Affine Frequency Division Multiplexing for Integrated Sensing and Communication

Affine frequency division multiplexing (AFDM) is a chirp-based multicarrier waveform that was recently proposed for communication over doubly dispersive channels. Given its chirp nature, AFDM is expected to have superior sensing capabilities compared to orthogonal frequency division multiplexing (OFDM) and is thus a promising candidate for integrated sensing and communication (ISAC) applications. In this paper, we derive a closed-form expression for the ambiguity function of AFDM waveforms modulated with $M$-ary quadrature amplitude modulation (QAM) data symbols. We determine the condition on the chirp rate of the AFDM waveform that minimizes the sidelobes in the delay/range domain in the presence of random $M$-ary QAM symbols, thereby improving overall sensing performance. Additionally, we find an approximate statistical distribution for the magnitude of the derived ambiguity function. Simulation results are presented to evaluate the sensing performance of the AFDM waveform for various system parameters and to compare its peak-to-sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR) with those of OFDM.

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arXiv2025

Joint Superimposed Pilot-aided Channel Estimation and Data Detection for FTN Signaling over Doubly-Selective Channels

Faster-than-Nyquist (FTN) signaling and superimposed pilot (SP) techniques are effective solutions for significantly enhancing the spectral efficiency (SE) in next-generation wireless communication systems. This paper proposes an innovative SP-aided channel estimation method for FTN signaling enhancing the SE over doubly-selective (i.e., time- and frequency-selective) channels. To avoid complex channel tracking, we utilize a basis expansion model (BEM) to characterize doubly-selective channel variations. We propose a frame structure that superimposes a known periodic pilot sequence onto the information sequence, avoiding SE loss by eliminating the additional overhead of multiplexed pilot (MP). Additionally, we find the optimal FTN signaling SP sequence that minimizes the mean square error (MSE) of the channel estimation. Expanding on our proposed SP-aided channel estimation method, we propose two detection methods: (1) an SP-aided separate channel estimation and data detection (SCEDD) method performing a single channel estimation followed by iterative data detection via a turbo equalizer, serving as a baseline for evaluating the SP-aided channel estimation method, and (2) an SP-aided joint channel estimation and data detection (JCEDD) method, which extends the SCEDD by updating the channel estimate in each turbo equalization iteration, becoming our primary focus for its superior performance. At equivalent SE and a higher fading rate on the order of $10^{-3}$, our simulations show that SP-aided SCEDD method outperforms MP-aided techniques in both MSE and BER, while the SP-aided JCEDD method delivers remarkable performance, where reference approaches fail to track rapid channel variations.

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arXiv2024

Improved Soft-k-Means Clustering Algorithm for Balancing Energy Consumption in Wireless Sensor Networks

Energy load balancing is an essential issue in designing wireless sensor networks (WSNs). Clustering techniques are utilized as energy-efficient methods to balance the network energy and prolong its lifetime. In this paper, we propose an improved soft-k-means (IS-k-means) clustering algorithm to balance the energy consumption of nodes in WSNs. First, we use the idea of ``clustering by fast search and find of density peaks'' (CFSFDP) and kernel density estimation (KDE) to improve the selection of the initial cluster centers of the soft k-means clustering algorithm. Then, we utilize the flexibility of the soft-k-means and reassign member nodes considering their membership probabilities at the boundary of clusters to balance the number of nodes per cluster. Furthermore, the concept of multi-cluster heads is employed to balance the energy consumption within clusters. {Extensive simulation results under different network scenarios demonstrate that for small-scale WSNs with single-hop transmission}, the proposed algorithm can postpone the first node death, the half of nodes death, and the last node death on average when compared to various clustering algorithms from the literature.

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arXiv2024

IM-based Pilot-assisted Channel Estimation for FTN Signaling HF Communications

This paper investigates doubly-selective (i.e., time- and frequency-selective) channel estimation in faster-than-Nyquist (FTN) signaling HF communications. In particular, we propose a novel IM-based channel estimation algorithm for FTN signaling HF communications including pilot sequence placement (PSP) and pilot sequence location identification (PSLI) algorithms. At the transmitter, we propose the PSP algorithm that utilizes the locations of pilot sequences to carry additional information bits, thereby improving the SE of HF communications. HF channels have two non-zero independent fading paths with specific fixed delay spread and frequency spread characteristics as outlined in the Union Radio communication Sector (ITU-R) F.1487 and F.520. Having said that, based on the aforementioned properties of the HF channels and the favorable auto-correlation characteristics of the optimal pilot sequence, we propose a novel PSLI algorithm that effectively identifies the pilot sequence location within a given frame at the receiver. This is achieved by showing that the square of the absolute value of the cross-correlation between the received symbols and the pilot sequence consists of a scaled version of the square of the absolute value of the auto-correlation of the pilot sequence weighted by the gain of the corresponding HF channel path. Simulation results show very low pilot sequence location identification errors for HF channels. Our simulation results show a 6 dB improvement in the MSE of the channel estimation as well as about 3.5 dB BER improvement of FTN signaling along with an enhancement in SE compared to the method in [1]. We also achieved an enhancement in SE compared to the work in [2] while maintaining comparable MSE of the channel estimation and BER performance.

cs.IT↗

arXiv2023

UAV Trajectory Planning for AoI-Minimal Data Collection in UAV-Aided IoT Networks by Transformer

Maintaining freshness of data collection in Internet-of-Things (IoT) networks has attracted increasing attention. By taking into account age-of-information (AoI), we investigate the trajectory planning problem of an unmanned aerial vehicle (UAV) that is used to aid a cluster-based IoT network. An optimization problem is formulated to minimize the total AoI of the collected data by the UAV from the ground IoT network. Since the total AoI of the IoT network depends on the flight time of the UAV and the data collection time at hovering points, we jointly optimize the selection of hovering points and the visiting order to these points. We exploit the state-of-the-art transformer and the weighted A*, which is a path search algorithm, to design a machine learning algorithm to solve the formulated problem. The whole UAV-IoT system is fed into the encoder network of the proposed algorithm, and the algorithm's decoder network outputs the visiting order to ground clusters. Then, the weighted A* is used to find the hovering point for each cluster in the ground IoT network. Simulation results show that the trained model by the proposed algorithm has a good generalization ability to generate solutions for IoT networks with different numbers of ground clusters, without the need to retrain the model. Furthermore, results show that our proposed algorithm can find better UAV trajectories with the minimum total AoI when compared to other algorithms.

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arXiv2023

A Tutorial on Chirp Spread Spectrum for LoRaWAN: Basics and Key Advances

Chirps spread spectrum (CSS) modulation is the heart of long-range (LoRa) modulation used in the context of long-range wide area network (LoRaWAN) in internet of things (IoT) scenarios. Despite being a proprietary technology owned by Semtech Corp., LoRa modulation has drawn much attention from the research and industry communities in recent years. However, to the best of our knowledge, a comprehensive tutorial, investigating the CSS modulation in the LoRaWAN application, is missing in the literature. Therefore, in the first part of this paper, we provide a thorough analysis and tutorial of CSS modulation modified by LoRa specifications, discussing various aspects such as signal generation, detection, error performance, and spectral characteristics. Moreover, a summary of key recent advances in the context of CSS modulation applications in IoT networks is presented in the second part of this paper under four main categories of transceiver configuration and design, data rate improvement, interference modeling, and synchronization algorithms.

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