arXiv subjects

Hamza Haif

Publications and source records attributed to Hamza Haif.

5 recordsLinked to original sources

arXiv2026

Channel-Aware Waveform Selection Criteria Across Different Waveform Domains

Waveform evaluation for sixth generation (6G) networks has largely relied on sparse and quasi-stationary channel models that enabled mathematical tractability, diversity gains, and Doppler robustness. However, such models obscure the propagation complexity of dense urban environments, high mobility scenarios, and heterogeneous network deployments. This paper sheds light on a generalized and scalable channel model that incorporates cluster birth-death dynamics, Doppler spectral spreading, time-varying delays, and piecewise local stationarity. Based on this model, the effective input-output relationships of the main 6G waveforms are derived, exposing waveform dependent interference structures that remain hidden under conventional sparse assumptions. Building on these effective channels, a channel-aware waveform prioritization framework is developed based on delay-Doppler resolvability, stationarity conditions, effective signal-to-interference-plus-noise ratio (SINR), and user equipment (UE) cell distribution. Simulation results under the proposed channel model using 3GPP CDL parameters confirm that affine frequency division multiplexing (AFDM) and orthogonal time frequency space (OTFS) retain their spectral efficiency advantage and path combining gains only under sparse, resolvable, stationarity conditions, whereas orthogonal frequency division multiplexing (OFDM) and discrete Fourier transform spread (DFT-s)-OFDM can be both tuned to achieve superior reliability and more stable performance under the proposed channel model.

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arXiv2026

Sparsity and Resolvability: Re-evaluating Channel Representations For Next Generation Networks

As wireless networks transition toward 6G, high mobility, clustered scattering, and hardware impairments increasingly challenge classical assumptions on channel sparsity, resolvability, and stationarity. In these regimes, performance assessments based on apparent sparsity or nominal delay and Doppler separation can be misleading, since finite observation, sampling granularity, windowing, and fractional delay or Doppler spreading introduce coupling and leakage that reshape the effective channel seen by the receiver. This article provides a signal processing centric framework that links sparsity, resolvability, and selectivity through receiver observable indicators, including the fraction of power captured by dominant coefficients, the level of coefficient correlation, the effective delay and Doppler resolving capability over the observation window, and processing induced leakage. Building on these observations, we propose an interchanged domain frame concept principle, where the representation and the degree of component separation are adapted according to the propagation regime, the effective SNR under impairments, and the application objective. Using the Extended Vehicular A channel profile as a running case study, we show how different representations lead to different equalization and detection behavior, with implications for communication, sensing, and physical layer security.

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arXiv2025

Waveform-domain NOMA: An Enabler for ISAC in Uplink Transmission

According to the recent 3GPP decisions on 6G air interface, orthogonal frequency-division multiplexing (OFDM)-based waveforms are the primary candidates for future integrated sensing and communication (ISAC) systems. In this paper, we consider a monostatic sensing scenario in which OFDM is used for the downlink and its reflected echo signal is used for sensing. OFDM and discrete Fourier transform-spread OFDM (DFT-s-OFDM) are the options for uplink transmission. When OFDM is used in the uplink, the power difference between this signal and the echo signal leads to a power-domain non-orthogonal multiple access (PD-NOMA) scenario. In contrast, adopting DFT-s-OFDM as uplink signal enables a waveform-domain NOMA(WD-NOMA). Affine frequency-division multiplexing (AFDM) and orthogonal time frequency space (OTFS) have been proven to be DFT-s-OFDM based waveforms. This work focuses on such a WD-NOMA system, where AFDM or OTFS is used as uplink waveform and OFDM is employed for downlink transmission and sensing. We show that the OFDM signal exhibits additive white Gaussian noise (AWGN)-like behavior in the affine domain, allowing it to be modeled as white noise in uplink symbol detection. To enable accurate data detection performance, an AFDM frame design and a noise power estimation (NPE) method are developed. Furthermore, a two-dimensional orthogonal matching pursuit (2D-OMP) algorithm is applied for sensing by iteratively identifying delay-Doppler components of each target. Simulation results demonstrate that the WD-NOMA ISAC system, employing either AFDM or OTFS, outperforms the PD-NOMA ISAC system that uses only the OFDM waveform in terms of bit error rate (BER) performance. Furthermore, the proposed NPE method yields additional improvements in BER.

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arXiv2025

A Unified Framework for Adaptive Waveform Processing in Next Generation Wireless Networks

The emergence of alternative multiplexing domains to the time-frequency domains, e.g., the delay-Doppler and chirp domains, offers a promising approach for addressing the challenges posed by complex propagation environments and next-generation applications. Unlike the time and frequency domains, these domains offer unique channel representations which provide additional degrees of freedom (DoF) for modeling, characterizing, and exploiting wireless channel features. This article provides a comprehensive analysis of channel characteristics, including delay, Doppler shifts, and channel coefficients across various domains, with an emphasis on their inter-domain relationships, shared characteristics, and domain-specific distinctions. We further evaluate the comparative advantages of each domain under specific channel conditions. Building on this analysis, we propose a generalized and adaptive transform domain framework that leverages the pre- and post-processing of the discrete Fourier transform (DFT) matrix, to enable dynamic transitions between various domains in response to the channel conditions and system requirements. Finally, several representative use cases are presented to demonstrate the applicability of the proposed cross-domain waveform processing framework in diverse scenarios, along with future directions and challenges.

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arXiv2025

Enabling Full Duplex ISAC Leveraging Waveform Domain Separability

Integrated sensing and communication (ISAC) in monostatic in-band full-duplex (IBFD) systems encounters significant challenges due to self-interference (SI) at the radar receiver during concurrent communication and radar operations. This paper proposes a novel waveform-domain self-interference cancellation (SIC) technique that leverages the unique properties of orthogonal frequency division multiplexing (OFDM) and affine frequency division multiplexing (AFDM) signals. The proposed approach designs the integrated dual-functionality frame to utilize OFDM for communication and AFDM for radar sensing, both generated using the same modulator block. Then, we establish the conditions under which a wide sense stationary (WSS) process in the time domain appears as WSS in the affine domain and demonstrate that the interfering OFDM signal behaves as an additive white Gaussian noise (AWGN) in this domain. Exploiting this property, the received signal is projected into the affine domain, where the SI appears as AWGN, enabling its subtraction with minimal residual interference. To further mitigate the residual SI, an iterative low-complexity windowing scheme is applied, selectively locking onto the radar signal to reduce the processed signal space. A subsequent time-domain spreading step is applied after converting the SIC-processed signal into the post-coded time domain, wherein the SI diminishes separately across the delay and Doppler axes. The proposed method demonstrates superior performance in terms of detection probability, target range and velocity root mean square error (RMSE), while maintaining high spectral efficiency and minimal computational complexity.

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