arXiv subjects

Yousef Kloob

Publications and source records attributed to Yousef Kloob.

3 recordsLinked to original sources

arXiv2026

A Unified KLD Framework for Duplexity and Deployment Paradigms in Cell-Free mMIMO-ISAC

This paper presents a comparative study of four potential operating configurations for distributed cell-free massive multiple-input multiple-output (CF-mMIMO) ISAC, spanning separated (SE) and shared (SH) access point (AP) deployment with half-duplex (HD) and full-duplex (FD) paradigms. The system comprises distributed APs serving multiple downlink (DL) and uplink (UL) users while simultaneously detecting radar targets. The configurations incorporate realistic impairments at the AP receivers: residual self-interference (SI) from transmit--receive leakage under FD operation, imperfect interference cancellation (IC) of the known radar and DL waveforms due to channel-estimation errors, and environmental clutter. To establish a common analytical scale for communication and sensing, the Kullback--Leibler divergence (KLD) is adopted as a unifying measure that represents both subsystems in comparable quantities, thereby enabling consistent comparison between error-rate and detection metrics. A generalised likelihood ratio test (GLRT) framework is developed, yielding closed-form expressions that link the KLD to the detection probability. Our results confirm the derived KLD-to-symbol error rate (SER) and KLD-to-detection links: with adequate SI suppression and IC quality, FD attains substantial communication gains over HD while preserving strong radar detection, and SH deployment raises both communication and radar performance through its larger effective aperture, though its radar gain then depends on cancellation quality, which SE deployment avoids by isolating the subsystems. These trends persist under imperfect channel state information (CSI) and sensing estimation, and a complexity analysis attributes the SH deployment and FD gains to a higher per-configuration processing cost, yielding deployment guidelines and quantitative design thresholds for next-generation CF-mMIMO ISAC systems.

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arXiv2024

A Framework for Holistic KLD-based Waveform Design for Multi-User-Multi-Target ISAC Systems

This paper introduces a novel framework aimed at designing integrated waveforms for robust integrated sensing and communication (ISAC) systems. The system model consists of a multiple-input multiple-output (MIMO) base station that simultaneously serves communication user equipments (UEs) and detects multiple targets using a shared-antenna deployment scenario. By leveraging Kullback-Leibler divergence (KLD) to holistically characterise both communication and sensing subsystems, three optimisation problems are formulated: (i) radar waveform KLD maximisation under communication constraints, (ii) communication waveform KLD maximisation subject to radar KLD requirements, and (iii) an integrated waveform KLD-based optimisation for ISAC that jointly balances both subsystems. The first two problems are solved using a projected gradient method with adaptive penalties for the radar waveforms and a gradient-assisted interior point method (IPM) for the communication waveforms. The third, integrated waveform optimisation approach adopts an alternating direction method of multipliers (ADMM) framework to unify radar and communication waveform designs into a single integrated optimisation, thereby synergising sensing and communication objectives and achieving higher overall performance than either radar- or communication-only techniques. Unlike most existing ISAC waveform designs that regard communication signals solely as interference for sensing, the proposed framework utilises the holistic ISAC waveform-that is, the superimposed communication and sensing signals-to boost detection performance in the radar subsystem. Simulation results show significant improvements in both radar detection and communication reliability compared with conventional zero-forcing beamforming, identity-covariance radar baselines, and traditional optimisation approaches,..

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arXiv2023

Novel KLD-based Resource Allocation for Integrated Sensing and Communication

In this paper, we introduce a novel resource allocation approach for integrated sensing-communication (ISAC) using the Kullback-Leibler divergence (KLD) metric. Specifically, we consider a base-station with limited power and antenna resources serving a number of communication users and detecting multiple targets simultaneously. First, we analyze the KLD for two possible antenna deployments, which are the separated and shared deployments, then use the results to optimize the resources of the base-station through minimising the average KLD for the network while satisfying a minimum predefined KLD requirement for each user equipment (UE) and target. To this end, the optimisation is formulated and presented as a mixed integer nonlinear programming (MINLP) problem and then solved using two approaches. In the first approach, we employ a genetic algorithm, which offers remarkable performance but demands substantial computational resources; and in the second approach, we propose a rounding-based interior-point method (RIPM) that provides a more computationally-efficient alternative solution at a negligible performance loss. The results demonstrate that the KLD metric can be an effective means for optimising ISAC networks, and that both optimisation solutions presented offer superior performance compared to uniform power and antenna allocation.

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