A modulation- and receive-filter-aware framework for the sensing-interference management in multi-cell OFDM-ISAC systems is developed and closed-form signal-to-interference-plus-noise ratio (SINR) expressions for each range--Doppler bin under matched filtering (MF) and reciprocal filtering (RF).
Abstract
Future integrated sensing and communication (ISAC) networks are expected to operate in dense multi-cell environments, where multiple base stations (BSs) share their time-frequency resources for communication and sensing. In such scenarios, the delay--Doppler (DD) sensing performance is strongly affected by random finite-alphabet orthogonal frequency-division multiplexing (OFDM) symbols, power allocation, receive filtering, and interference. This paper develops a modulation- and receive-filter-aware framework for the sensing-interference management in multi-cell OFDM-ISAC systems. Starting from a discrete-time OFDM sensing model, we derive closed-form signal-to-interference-plus-noise ratio (SINR) expressions for each range--Doppler bin under matched filtering (MF) and reciprocal filtering (RF). The analysis reveals distinct interference structures: MF depends on fourth-order constellation moments and power-overlap terms, whereas RF is governed by inverse-symbol-power and ratio-type interference terms. Based on these expressions, we obtain sensing-oriented power allocation structures, including a ramped water-filling solution for MF and a square-root allocation rule for RF. Furthermore, we jointly optimize the finite-alphabet constellation selection and power allocation under realistic communication and power constraints, and obtain tractable mixed-integer convex formulations for both MF and RF. Additionally, we study spectrum-overlap coordination in multi-cell scenarios and reveal the distinct MF/RF preferences for shared and orthogonalized tones. Furthermore, we extend the interference model to inter-cell propagation delays exceeding the cyclic prefix (CP), and show how the resultant delay violation redistributes the nominal interference spectrum into a delay-distorted effective spectrum...
In communication-centric integrated sensing and communication (ISAC), delay-Doppler sensing reuses data-bearing orthogonal frequency division multiplexing (OFDM) signals rather than dedicated radar probing waveforms. Consequently, the resulting range-Doppler map (RDM) is shaped not only by target parameters, but also by communication-symbol randomness and, in multi-antenna transmissions, by spatial beamforming. While existing analyses have largely focused on single-antenna OFDM-ISAC, the delay-Doppler sensing behavior of multi-antenna OFDM-ISAC remains insufficiently understood. This paper analyzes a multi-input multi-output (MIMO)-OFDM-ISAC system in which multiple data streams jointly illuminate a sensing target. We derive second-order moment expressions for the RDM under matched filtering (MF) and reciprocal filtering (RF), and use them to characterize the dynamic range (DR). The analysis reveals two key multi-stream effects. First, under MF, the random superposition of multiple beamformed streams creates an additional RDM floor beyond the modulation-dependent and receiver-noise terms; therefore, constant-modulus signaling no longer eliminates the data-induced pedestal as in single-antenna OFDM-ISAC. Second, under RF, the matched-angle data-induced floor is removed, but the noise floor is amplified according to the reciprocal-power statistics of the beamformed target illumination. These results show that the user-target angular geometry directly governs the MF/RF tradeoff: MF is more robust under weak illumination, whereas RF can achieve a higher DR when reciprocal-noise amplification is mild. Numerical results validate the analysis and demonstrate the distinct geometry-dependent behaviors of MF and RF.
Spectrally efficient frequency-division multiplexing (SEFDM) is an attractive waveform to improve communication spectral efficiency by compressing the subcarrier spacing, yet its use for integrated sensing and communication (ISAC) poses a fundamental sensing challenge. Specifically, the intentional loss of subcarrier orthogonality generates SEFDM-induced intercarrier interference (S-ICI), which combines with Doppler-induced ICI (D-ICI) from moving targets to blur range--velocity maps and severely degrade sensing accuracy. Building on multi-user multi-input-multi-output (MIMO) SEFDM systems, this paper develops a model-driven ISAC framework that supports spectrally efficient multi-user communication while mitigating both S-ICI and D-ICI in sensing. To this end, an intercarrier interference mitigation network (IMNet) is proposed, which exploits the distinct physical structures of the two interferences. A bank of Doppler correction filters first compensates the velocity-dependent D-ICI over multiple Doppler hypotheses, and an axial-attention network subsequently suppresses the residual D-ICI and the long-range S-ICI to recover reliable sensing signals. To further improve range and velocity estimation accuracy, IMNet with local refinement (IMNet-LR) is proposed, which performs maximum-likelihood refinement with nuisance projection around the IMNet detections to achieve sub-cell precision without an exhaustive global search. Simulation results show that IMNet-LR achieves near-maximum-likelihood range and velocity estimation accuracy with more than three orders of magnitude lower execution time compared to conventional detection methods.
This paper investigates joint subcarrier and power allocation for a multi-user Orthogonal Frequency Division Multiplexing (OFDM)-based Integrated Sensing and Communication (ISAC) system in Vehicle-to-Everything (V2X) environments. The goal is to maximize a weighted sum of the capped effective radar Signal-to-Noise Ratio (SNR) and aggregate communication rate, under per-user constraints on minimum effective radar SNR, communication rate, and range resolution. The problem is formulated as a Mixed-Integer Nonlinear Programming (MINLP) model. To address its non-convexity, we develop a Block Coordinate Descent–based Joint Resource Allocation (BCD-JRA) algorithm that alternates between nonlinear power allocation and mixed-integer subcarrier assignment and is used as a benchmark in our study. To support real-time V2X operation, we further propose a low-complexity two-stage heuristic, termed Phased Constraint Satisfaction and Greedy Allocation (PSGA). PSGA first allocates the minimum resources needed to satisfy the Quality of Service (QoS) constraints, and then greedily assigns remaining resources based on marginal utility gains while accounting for effective radar SNR capping. The simulation results show that PSGA attains utility close to the BCD-JRA benchmark with millisecond-level latency and satisfies all QoS constraints in the reported experiments.
Jiahao Zheng, Xinhao Chen, Linyu Huang et al.· IEEE Transactions on Wireles...· 0 citations
Channel time dispersion causes inter-symbol interference (ISI) which is mitigated by the Orthogonal Frequency Division Multiplexing (OFDM) symbol cyclic prefix (CP). However, CP is an overhead which reduces spectral efficiency and increases energy per delivered bit. In Long Term Evolution (LTE), the widely deployed normal CP corresponds to a fixed overhead of about 7% (4.69 μs), which is conservative for many practical environments and is equivalent to path-length variations on the order of 1.4 km. This paper address CP sizing from an energy-efficiency viewpoint for OFDM-based 4G/5G radio networks. We combine an analytical model based on delay spread statistics with link-level simulations to determine a reduced CP that remains effective for ISI mitigation across indoor-to-urban scenarios. Optimal CP intervals are derived for the LTE M-ary Quadrature Amplitude Modulation formats (4-QAM, 16-QAM, and 64-QAM) and validated using standard delay-dispersive mobile radio channels. Results indicate that CP can be reduced by 70–95% relative to the LTE normal CP in typical deployments, yielding measurable net-throughput improvements and energy savings without compromising error-rate targets, supporting greener wireless communications.
Adriana Lipovac, Vlatko Lipovac, Mario Miličević et al.· Applied Sciences· 0 citations
To address the challenges of inter-cell interference/reflection and static clutter, a clutter-aware waveform design for a multi-cell multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system is proposed. Various levels of coordination among base stations (BSs) are investigated to enhance target detectability in cluttered environments while maintaining the quality of service (QoS) for communication users. Specifically, two coordination schemes are investigated: 1) coordinated beamforming (CBF), where only channel state information (CSI) is shared, and 2) coordinated multipoint (CoMP), where both CSI and user data are exchanged among BSs. The waveform design problem is formulated as a non-convex optimization that maximizes the radar output signal-to-clutter-plus-interference-plus-noise ratio (SCINR), subject to robust symbol-level QoS and constant-modulus power constraints to ensure uncertainty in shared and estimated CSI. To tackle this problem, the single-ratio SCINR objective is decoupled via Dinkelbach’s transform (or a quadratic transform for multiple-ratio objectives) and reformulated on a Riemannian manifold to accommodate the constant-modulus constraint guarantees a practical peak-to-average-power ratio (PAPR). The resulting problem is further converted into an unconstrained form using the augmented Lagrangian method (ALM) and solved through a Riemannian conjugate gradient (RCG) algorithm. Simulation results demonstrate that the proposed designs achieve superior radar and communication performance compared to baseline schemes that underestimate the effects of multi-cell deployment.
Yves Fidele Aikoun, Gordon Owusu Boateng, Zhao-Jie Wang et al.· IEEE Transactions on Wireles...· 0 citations
Integrated Sensing and Communication (ISAC) has emerged as a key enabling technology for future sixth-generation (6G) wireless networks by enabling sensing and communication functionalities to share spectrum, hardware resources, and signal processing infrastructure. However, practical ISAC systems are affected by self-interference, mutual interference between sensing and communication signals, and environmental clutter, which jointly degrade communication reliability and sensing performance. To address these challenges, this paper proposes a novel three-slot interference mitigation framework for downlink ISAC systems. Unlike conventional ISAC approaches that perform joint sensing and communication within a single transmission stage, the proposed framework separates directional sensing, parameter acquisition, and interference-aware joint transmission into three coordinated slots, enabling transmit-side pre-cancellation of sensing-induced mutual interference using estimated interference parameters. Furthermore, joint convex optimization-based beamforming is employed to mitigate self-interference through sidelobe minimization and suppress environmental clutter through spatial null steering while maintaining the desired sensing and communication links. Simulation results demonstrate beam steering, parameter recovery, communication performance after interference cancellation, and target range, velocity, and angle estimation using Range-Doppler and Multiple Signal Classification (MUSIC) processing. The proposed framework presents an interference-aware ISAC architecture that combines a three-slot transmission protocol for mitigating sensing-induced mutual interference with joint beamforming for suppressing self-interference and environmental clutter while supporting simultaneous sensing and communication.
Sanjai Arul, Yin-Wei Hsu, Juinn-Horng Deng et al.· Electronics· 0 citations
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